A model of human decision making in multiple process monitoring situations
NASA Technical Reports Server (NTRS)
Greenstein, J. S.; Rouse, W. B.
1982-01-01
Human decision making in multiple process monitoring situations is considered. It is proposed that human decision making in many multiple process monitoring situations can be modeled in terms of the human's detection of process related events and his allocation of attention among processes once he feels event have occurred. A mathematical model of human event detection and attention allocation performance in multiple process monitoring situations is developed. An assumption made in developing the model is that, in attempting to detect events, the human generates estimates of the probabilities that events have occurred. An elementary pattern recognition technique, discriminant analysis, is used to model the human's generation of these probability estimates. The performance of the model is compared to that of four subjects in a multiple process monitoring situation requiring allocation of attention among processes.
Modelling decision-making by pilots
NASA Technical Reports Server (NTRS)
Patrick, Nicholas J. M.
1993-01-01
Our scientific goal is to understand the process of human decision-making. Specifically, a model of human decision-making in piloting modern commercial aircraft which prescribes optimal behavior, and against which we can measure human sub-optimality is sought. This model should help us understand such diverse aspects of piloting as strategic decision-making, and the implicit decisions involved in attention allocation. Our engineering goal is to provide design specifications for (1) better computer-based decision-aids, and (2) better training programs for the human pilot (or human decision-maker, DM).
[Clinical decision making and critical thinking in the nursing diagnostic process].
Müller-Staub, Maria
2006-10-01
The daily routine requires complex thinking processes of nurses, but clinical decision making and critical thinking are underestimated in nursing. A great demand for educational measures in clinical judgement related with the diagnostic process was found in nurses. The German literature hardly describes nursing diagnoses as clinical judgements about human reactions on health problems / life processes. Critical thinking is described as an intellectual, disciplined process of active conceptualisation, application and synthesis of information. It is gained through observation, experience, reflection and communication and leads thinking and action. Critical thinking influences the aspects of clinical decision making a) diagnostic judgement, b) therapeutic reasoning and c) ethical decision making. Human reactions are complex processes and in their course, human behavior is interpreted in the focus of health. Therefore, more attention should be given to the nursing diagnostic process. This article presents the theoretical framework of the paper "Clinical decision making: Fostering critical thinking in the nursing diagnostic process through case studies".
Proctor, Robert W; Chen, Jing
2015-08-01
The overarching goal is to convey the concept of science of security and the contributions that a scientifically based, human factors approach can make to this interdisciplinary field. Rather than a piecemeal approach to solving cybersecurity problems as they arise, the U.S. government is mounting a systematic effort to develop an approach grounded in science. Because humans play a central role in security measures, research on security-related decisions and actions grounded in principles of human information-processing and decision-making is crucial to this interdisciplinary effort. We describe the science of security and the role that human factors can play in it, and use two examples of research in cybersecurity--detection of phishing attacks and selection of mobile applications--to illustrate the contribution of a scientific, human factors approach. In these research areas, we show that systematic information-processing analyses of the decisions that users make and the actions they take provide a basis for integrating the human component of security science. Human factors specialists should utilize their foundation in the science of applied information processing and decision making to contribute to the science of cybersecurity. © 2015, Human Factors and Ergonomics Society.
Humans Optimize Decision-Making by Delaying Decision Onset
Teichert, Tobias; Ferrera, Vincent P.; Grinband, Jack
2014-01-01
Why do humans make errors on seemingly trivial perceptual decisions? It has been shown that such errors occur in part because the decision process (evidence accumulation) is initiated before selective attention has isolated the relevant sensory information from salient distractors. Nevertheless, it is typically assumed that subjects increase accuracy by prolonging the decision process rather than delaying decision onset. To date it has not been tested whether humans can strategically delay decision onset to increase response accuracy. To address this question we measured the time course of selective attention in a motion interference task using a novel variant of the response signal paradigm. Based on these measurements we estimated time-dependent drift rate and showed that subjects should in principle be able trade speed for accuracy very effectively by delaying decision onset. Using the time-dependent estimate of drift rate we show that subjects indeed delay decision onset in addition to raising response threshold when asked to stress accuracy over speed in a free reaction version of the same motion-interference task. These findings show that decision onset is a critical aspect of the decision process that can be adjusted to effectively improve decision accuracy. PMID:24599295
Weber
1998-12-01
For the past 33 years, Organizational Behavior and Human Decision Processes has thrived under a single editor. That editor, James C. Naylor, is retiring from his long stewardship. This article chronicles the course of the journal under Jim's direction and marks some of the accomplishments and changes over the past three decades that go to his credit. Copyright 1998 Academic Press.
Information processing. [in human performance
NASA Technical Reports Server (NTRS)
Wickens, Christopher D.; Flach, John M.
1988-01-01
Theoretical models of sensory-information processing by the human brain are reviewed from a human-factors perspective, with a focus on their implications for aircraft and avionics design. The topics addressed include perception (signal detection and selection), linguistic factors in perception (context provision, logical reversals, absence of cues, and order reversals), mental models, and working and long-term memory. Particular attention is given to decision-making problems such as situation assessment, decision formulation, decision quality, selection of action, the speed-accuracy tradeoff, stimulus-response compatibility, stimulus sequencing, dual-task performance, task difficulty and structure, and factors affecting multiple task performance (processing modalities, codes, and stages).
The Effect of Decision-Making Skill Training Programs on Self-Esteem and Decision-Making Styles
ERIC Educational Resources Information Center
Colakkadioglu, Oguzhan; Celik, D. Billur
2016-01-01
Problem Statement: Decision making is a critical cognitive process in every area of human life. In this process, the individuals play an active role and obtain outputs with their functional use of decision-making skills. Therefore, the decision-making process can affect the course of life, life satisfaction, and the social relations of an…
Striatal BOLD Response Reflects the Impact of Herd Information on Financial Decisions
Burke, Christopher J.; Tobler, Philippe N.; Schultz, Wolfram; Baddeley, Michelle
2010-01-01
Like other species, humans are sensitive to the decisions and actions of conspecifics, which can lead to herd behavior and undesirable outcomes such as stock market bubbles and bank runs. However, how the brain processes this socially derived influence is only poorly understood. Using functional magnetic resonance imaging (fMRI), we scanned participants as they made decisions on whether to buy stocks after observing others’ buying decisions. We demonstrate that activity in the ventral striatum, an area heavily implicated in reward processing, tracked the degree of influence on participants’ decisions arising from the observation of other peoples’ decisions. The signal did not track non-human, non-social control decisions. These findings lend weight to the notion that the ventral striatum is involved in the processing of complex social aspects of decision making and identify a possible neural basis for herd behavior. PMID:20589242
Dissociating sensory from decision processes in human perceptual decision making.
Mostert, Pim; Kok, Peter; de Lange, Floris P
2015-12-15
A key question within systems neuroscience is how the brain translates physical stimulation into a behavioral response: perceptual decision making. To answer this question, it is important to dissociate the neural activity underlying the encoding of sensory information from the activity underlying the subsequent temporal integration into a decision variable. Here, we adopted a decoding approach to empirically assess this dissociation in human magnetoencephalography recordings. We used a functional localizer to identify the neural signature that reflects sensory-specific processes, and subsequently traced this signature while subjects were engaged in a perceptual decision making task. Our results revealed a temporal dissociation in which sensory processing was limited to an early time window and consistent with occipital areas, whereas decision-related processing became increasingly pronounced over time, and involved parietal and frontal areas. We found that the sensory processing accurately reflected the physical stimulus, irrespective of the eventual decision. Moreover, the sensory representation was stable and maintained over time when it was required for a subsequent decision, but unstable and variable over time when it was task-irrelevant. In contrast, decision-related activity displayed long-lasting sustained components. Together, our approach dissects neuro-anatomically and functionally distinct contributions to perceptual decisions.
Dissociating sensory from decision processes in human perceptual decision making
Mostert, Pim; Kok, Peter; de Lange, Floris P.
2015-01-01
A key question within systems neuroscience is how the brain translates physical stimulation into a behavioral response: perceptual decision making. To answer this question, it is important to dissociate the neural activity underlying the encoding of sensory information from the activity underlying the subsequent temporal integration into a decision variable. Here, we adopted a decoding approach to empirically assess this dissociation in human magnetoencephalography recordings. We used a functional localizer to identify the neural signature that reflects sensory-specific processes, and subsequently traced this signature while subjects were engaged in a perceptual decision making task. Our results revealed a temporal dissociation in which sensory processing was limited to an early time window and consistent with occipital areas, whereas decision-related processing became increasingly pronounced over time, and involved parietal and frontal areas. We found that the sensory processing accurately reflected the physical stimulus, irrespective of the eventual decision. Moreover, the sensory representation was stable and maintained over time when it was required for a subsequent decision, but unstable and variable over time when it was task-irrelevant. In contrast, decision-related activity displayed long-lasting sustained components. Together, our approach dissects neuro-anatomically and functionally distinct contributions to perceptual decisions. PMID:26666393
Human Factors of CC-130 Operations. Volume 5: Human Factors in Decision Making
1998-02-01
known about human information processing and decision making. Topics for HFDM training come directly from this theoretical framework . The proposed...The proposed training can be distinguished from other approaches with similar goals (either explicit or implicit) by its base within a theoretical ... framework of human information processing. The differences lie less in the content than in the way the material is organized and shaped by theory. The
Coding Theory Information Theory and Radar
2005-01-01
the design and synthesis of artificial multiagent systems and for the understanding of human decision-making processes. This... altruism that may exist in a complex society. SGT derives its ability to account simultaneously for both group and individual interests from the structure of ...satisficing decision theory as a model of human decision mak- ing. 2 Multi-Attribute Decision Making Many decision problems involve the consideration of
Improving Team Performance: Proceedings of the Rand Team Performance Workshop.
1980-08-01
organization theory, small group processes, cognitive psychologi training and instruction , decision theory, artificial intelligence, and human engineering...theory, small group processes, cognitive psy- chology, training and instruction , heuristic modeling, decision theory, and human engineering. Within...interact with. The operators are taught about the equipment and how it works; the actual job is left to be learned aboard ship. The cognitive processes the
ERIC Educational Resources Information Center
Roets, Arne; Van Hiel, Alain
2011-01-01
This article aims to integrate the findings from various research traditions on human judgment and decision making, focusing on four process variables: arousal, affect, motivation, and cognitive capacity/ability. We advocate a broad perspective referred to as the integrative process approach (IPA) of decision making, in which these process…
An experimental paradigm for team decision processes
NASA Technical Reports Server (NTRS)
Serfaty, D.; Kleinman, D. L.
1986-01-01
The study of distributed information processing and decision making is presently hampered by two factors: (1) The inherent complexity of the mathematical formulation of decentralized problems has prevented the development of models that could be used to predict performance in a distributed environment; and (2) The lack of comprehensive scientific empirical data on human team decision making has hindered the development of significant descriptive models. As a part of a comprehensive effort to find a new framework for multihuman decision making problems, a novel experimental research paradigm was developed involving human terms in decision making tasks. Attempts to construct parts of an integrated model with ideas from queueing networks, team theory, distributed estimation and decentralized resource management are described.
NASA Astrophysics Data System (ADS)
Roy, Jean; Breton, Richard; Paradis, Stephane
2001-08-01
Situation Awareness (SAW) is essential for commanders to conduct decision-making (DM) activities. Situation Analysis (SA) is defined as a process, the examination of a situation, its elements, and their relations, to provide and maintain a product, i.e., a state of SAW for the decision maker. Operational trends in warfare put the situation analysis process under pressure. This emphasizes the need for a real-time computer-based Situation analysis Support System (SASS) to aid commanders in achieving the appropriate situation awareness, thereby supporting their response to actual or anticipated threats. Data fusion is clearly a key enabler for SA and a SASS. Since data fusion is used for SA in support of dynamic human decision-making, the exploration of the SA concepts and the design of data fusion techniques must take into account human factor aspects in order to ensure a cognitive fit of the fusion system with the decision-maker. Indeed, the tight human factor aspects in order to ensure a cognitive fit of the fusion system with the decision-maker. Indeed, the tight integration of the human element with the SA technology is essential. Regarding these issues, this paper provides a description of CODSI (Command Decision Support Interface), and operational- like human machine interface prototype for investigations in computer-based SA and command decision support. With CODSI, one objective was to apply recent developments in SA theory and information display technology to the problem of enhancing SAW quality. It thus provides a capability to adequately convey tactical information to command decision makers. It also supports the study of human-computer interactions for SA, and methodologies for SAW measurement.
Error-associated behaviors and error rates for robotic geology
NASA Technical Reports Server (NTRS)
Anderson, Robert C.; Thomas, Geb; Wagner, Jacob; Glasgow, Justin
2004-01-01
This study explores human error as a function of the decision-making process. One of many models for human decision-making is Rasmussen's decision ladder [9]. The decision ladder identifies the multiple tasks and states of knowledge involved in decision-making. The tasks and states of knowledge can be classified by the level of cognitive effort required to make the decision, leading to the skill, rule, and knowledge taxonomy (Rasmussen, 1987). Skill based decisions require the least cognitive effort and knowledge based decisions require the greatest cognitive effort. Errors can occur at any of the cognitive levels.
5 CFR 9701.222 - Reconsideration of classification decisions.
Code of Federal Regulations, 2010 CFR
2010-01-01
... decisions. 9701.222 Section 9701.222 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...
Empirically derived guidance for social scientists to influence environmental policy
Brown, Katrina; Crissman, Charles; De Young, Cassandra; Gooch, Margaret; James, Craig; Jessen, Sabine; Johnson, Dave; Marshall, Paul; Wachenfeld, Dave; Wrigley, Damian
2017-01-01
Failure to stem trends of ecological disruption and associated loss of ecosystem services worldwide is partly due to the inadequate integration of the human dimension into environmental decision-making. Decision-makers need knowledge of the human dimension of resource systems and of the social consequences of decision-making if environmental management is to be effective and adaptive. Social scientists have a central role to play, but little guidance exists to help them influence decision-making processes. We distil 348 years of cumulative experience shared by 31 environmental experts across three continents into advice for social scientists seeking to increase their influence in the environmental policy arena. Results focus on the importance of process, engagement, empathy and acumen and reveal the importance of understanding and actively participating in policy processes through co-producing knowledge and building trust. The insights gained during this research might empower a science-driven cultural change in science-policy relations for the routine integration of the human dimension in environmental decision making; ultimately for an improved outlook for earth’s ecosystems and the billions of people that depend on them. PMID:28278238
2017-09-01
AVAILABILITY STATEMENT Approved for public release. Distribution is unlimited. 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) Test and...ambiguities and identify high -value decision points? This thesis explores how formalization of these experience-based decisions as a process model...representing a T&E event may reveal high -value decision nodes where certain decisions carry more weight or potential for impacts to a successful test. The
Decision Science Challenges for C2 Agility
2014-06-01
decision -making effectiveness , but also the adaptive capacities needed to assure the resilience of the decision -making process itself. New methods are... effectiveness , but also the adaptive capacities needed to assure the resilience of the decision -making process itself. New methods are needed to help...of the literature on human biases and limitations, and hence it has been formative of entire programs of resarch and development on
ERIC Educational Resources Information Center
Ryan, Brendan M.
2017-01-01
This paper will apply the work of Amos Tversky and Daniel Kahneman in Prospect theory to the college recruiting process. Prospect theory challenges one of the fundamental ideas of Economics; humans are rational creatures and make rational decisions. The theory demonstrates that in fact, often humans do not make rational decisions and are instead…
Regret and Responsibility Resolved? Evaluating Ordóñez and Connolly's (2000) Conclusions.
Zeelenberg; van Dijk WW; Manstead
2000-01-01
T. Connolly, L. D. Ordo;aan;atez, and R. Coughlan (1997, Organizational Behavior and Human Decision Processes, 70, 73-85) argued, on the basis of 5 experiments, that regret need not be related to a sense of responsibility for the regretted outcome. We (M. Zeelenberg, W. W. van Dijk, & A. S. R. Manstead, 1998, Organizational Behavior and Human Decision Processes, 74, 254-272) showed in 2 experiments that this conclusion was premature, because it was based on an indirect measure of regret (i.e., overall happiness with the decision outcome). When regret was directly measured, the predicted effects of responsibility were found. L. D. Ordo;aan;atez and T. Connolly (2000, Organizational Behavior and Human Decision Processes, 81, 132-142) replicated our findings in 2 experiments. Based on their findings they arrived at 4 conclusions. In this rejoinder we first discuss Ordóñez and Connolly's new studies and we then discuss the validity of their 4 conclusions. Copyright 2000 Academic Press.
NASA Astrophysics Data System (ADS)
Sliva, Amy L.; Gorman, Joe; Voshell, Martin; Tittle, James; Bowman, Christopher
2016-05-01
The Dual Node Decision Wheels (DNDW) architecture concept was previously described as a novel approach toward integrating analytic and decision-making processes in joint human/automation systems in highly complex sociotechnical settings. In this paper, we extend the DNDW construct with a description of components in this framework, combining structures of the Dual Node Network (DNN) for Information Fusion and Resource Management with extensions on Rasmussen's Decision Ladder (DL) to provide guidance on constructing information systems that better serve decision-making support requirements. The DNN takes a component-centered approach to system design, decomposing each asset in terms of data inputs and outputs according to their roles and interactions in a fusion network. However, to ensure relevancy to and organizational fitment within command and control (C2) processes, principles from cognitive systems engineering emphasize that system design must take a human-centered systems view, integrating information needs and decision making requirements to drive the architecture design and capabilities of network assets. In the current work, we present an approach for structuring and assessing DNDW systems that uses a unique hybrid DNN top-down system design with a human-centered process design, combining DNN node decomposition with artifacts from cognitive analysis (i.e., system abstraction decomposition models, decision ladders) to provide work domain and task-level insights at different levels in an example intelligence, surveillance, and reconnaissance (ISR) system setting. This DNDW structure will ensure not only that the information fusion technologies and processes are structured effectively, but that the resulting information products will align with the requirements of human decision makers and be adaptable to different work settings .
Emotion-affected decision making in human simulation.
Zhao, Y; Kang, J; Wright, D K
2006-01-01
Human modelling is an interdisciplinary research field. The topic, emotion-affected decision making, was originally a cognitive psychology issue, but is now recognized as an important research direction for both computer science and biomedical modelling. The main aim of this paper is to attempt to bridge the gap between psychology and bioengineering in emotion-affected decision making. The work is based on Ortony's theory of emotions and bounded rationality theory, and attempts to connect the emotion process with decision making. A computational emotion model is proposed, and the initial framework of this model in virtual human simulation within the platform of Virtools is presented.
Rationality in Human Movement.
O'Brien, Megan K; Ahmed, Alaa A
2016-01-01
It long has been appreciated that humans behave irrationally in economic decisions under risk: they fail to objectively consider uncertainty, costs, and rewards and instead exhibit risk-seeking or risk-averse behavior. We hypothesize that poor estimates of motor variability (influenced by motor task) and distorted probability weighting (influenced by relevant emotional processes) contribute to characteristic irrationality in human movement decisions.
The Insertion of Human Factors Concerns into NextGen Programmatic Decisions
NASA Technical Reports Server (NTRS)
Beard, Bettina L.; Holbrook, Jon Brian; Seely, Rachel
2013-01-01
Since the costs of proposed improvements in air traffic management exceed available funding, FAA decision makers must select and prioritize what actually gets implemented. We discuss a set of methods to help forecast operational and human performance issues and benefits before new automation is introduced. This strategy could minimize the impact of politics, assist decision makers in selecting and prioritizing potential improvements, make the process more transparent and strengthen the link between the engineering and human factors domains.
2014-11-18
this research was to characterize the naturalistic decision making process used in Naval Aviation acquisition to assess cost, schedule and...Naval Aviation acquisitions can be identified, which can support the future development of new processes and tools for training and decision making...part of Department of Defense acquisition processes , HSI ensures that operator, maintainer and sustainer considerations are incorporated into
ERIC Educational Resources Information Center
Hantula, Donald A.
1995-01-01
Clinical applications of statistical process control (SPC) in human service organizations are considered. SPC is seen as providing a standard set of criteria that serves as a common interface for data-based decision making, which may bring decision making under the control of established contingencies rather than the immediate contingencies of…
Absolutely relative or relatively absolute: violations of value invariance in human decision making.
Teodorescu, Andrei R; Moran, Rani; Usher, Marius
2016-02-01
Making decisions based on relative rather than absolute information processing is tied to choice optimality via the accumulation of evidence differences and to canonical neural processing via accumulation of evidence ratios. These theoretical frameworks predict invariance of decision latencies to absolute intensities that maintain differences and ratios, respectively. While information about the absolute values of the choice alternatives is not necessary for choosing the best alternative, it may nevertheless hold valuable information about the context of the decision. To test the sensitivity of human decision making to absolute values, we manipulated the intensities of brightness stimuli pairs while preserving either their differences or their ratios. Although asked to choose the brighter alternative relative to the other, participants responded faster to higher absolute values. Thus, our results provide empirical evidence for human sensitivity to task irrelevant absolute values indicating a hard-wired mechanism that precedes executive control. Computational investigations of several modelling architectures reveal two alternative accounts for this phenomenon, which combine absolute and relative processing. One account involves accumulation of differences with activation dependent processing noise and the other emerges from accumulation of absolute values subject to the temporal dynamics of lateral inhibition. The potential adaptive role of such choice mechanisms is discussed.
Recognition Decisions From Visual Working Memory Are Mediated by Continuous Latent Strengths.
Ricker, Timothy J; Thiele, Jonathan E; Swagman, April R; Rouder, Jeffrey N
2017-08-01
Making recognition decisions often requires us to reference the contents of working memory, the information available for ongoing cognitive processing. As such, understanding how recognition decisions are made when based on the contents of working memory is of critical importance. In this work we examine whether recognition decisions based on the contents of visual working memory follow a continuous decision process of graded information about the correct choice or a discrete decision process reflecting only knowing and guessing. We find a clear pattern in favor of a continuous latent strength model of visual working memory-based decision making, supporting the notion that visual recognition decision processes are impacted by the degree of matching between the contents of working memory and the choices given. Relation to relevant findings and the implications for human information processing more generally are discussed. Copyright © 2016 Cognitive Science Society, Inc.
The Future of Computerized Decision Making
2014-12-01
complex, historically reserved for governing bodies or market places where the collective human experience and intelligence come to play. Other decision...access. In all cases, we should think about this carefully first: what data are really important for our goals and what data should be ignored or not even...stored? The answer to these questions involves human intelligence and understanding before the data-to-decision process begins.
Hirarchical emotion calculation model for virtual human modellin - biomed 2010.
Zhao, Yue; Wright, David
2010-01-01
This paper introduces a new emotion generation method for virtual human modelling. The method includes a novel hierarchical emotion structure, a group of emotion calculation equations and a simple heuristics decision making mechanism, which enables virtual humans to perform emotionally in real-time according to their internal and external factors. Emotion calculation equations used in this research were derived from psychologic emotion measurements. Virtual humans can utilise the information in virtual memory and emotion calculation equations to generate their own numerical emotion states within the hierarchical emotion structure. Those emotion states are important internal references for virtual humans to adopt appropriate behaviours and also key cues for their decision making. A simple heuristics theory is introduced and integrated into decision making process in order to make the virtual humans decision making more like a real human. A data interface which connects the emotion calculation and the decision making structure together has also been designed and simulated to test the method in Virtools environment.
General Formalism of Decision Making Based on Theory of Open Quantum Systems
NASA Astrophysics Data System (ADS)
Asano, M.; Ohya, M.; Basieva, I.; Khrennikov, A.
2013-01-01
We present the general formalism of decision making which is based on the theory of open quantum systems. A person (decision maker), say Alice, is considered as a quantum-like system, i.e., a system which information processing follows the laws of quantum information theory. To make decision, Alice interacts with a huge mental bath. Depending on context of decision making this bath can include her social environment, mass media (TV, newspapers, INTERNET), and memory. Dynamics of an ensemble of such Alices is described by Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) equation. We speculate that in the processes of evolution biosystems (especially human beings) designed such "mental Hamiltonians" and GKSL-operators that any solution of the corresponding GKSL-equation stabilizes to a diagonal density operator (In the basis of decision making.) This limiting density operator describes population in which all superpositions of possible decisions has already been resolved. In principle, this approach can be used for the prediction of the distribution of possible decisions in human populations.
Human Decision Processes: Implications for SSA Support Tools
NASA Astrophysics Data System (ADS)
Picciano, P.
2013-09-01
Despite significant advances in computing power and artificial intelligence (AI), few critical decisions are made without a human decision maker in the loop. Space Situational Awareness (SSA) missions are both critical and complex, typically adhering to the human-in-the-loop (HITL) model. The collection of human operators injects a needed diversity of expert knowledge, experience, and authority required to successfully fulfill SSA tasking. A wealth of literature on human decision making exists citing myriad empirical studies and offering a varied set of prescriptive and descriptive models of judgment and decision making (Hastie & Dawes, 2001; Baron, 2000). Many findings have been proven sufficiently robust to allow information architects or system/interface designers to take action to improve decision processes. For the purpose of discussion, these concepts are bifurcated in two groups: 1) vulnerabilities to mitigate, and 2) capabilities to augment. These vulnerabilities and capabilities refer specifically to the decision process and should not be confused with a shortcoming or skill of a specific human operator. Thus the framing of questions and orders, the automated tools with which to collaborate, priming and contextual data, and the delivery of information all play a critical role in human judgment and choice. Evaluating the merits of any decision can be elusive; in order to constrain this discussion, ‘rational choice' will tend toward the economic model characteristics such as maximizing utility and selection consistency (e.g., if A preferred to B, and B preferred to C, than A should be preferred to C). Simple decision models often encourage one to list the pros and cons of a decision, perhaps use a weighting schema, but one way or another weigh the future benefit (or harm) of making a selection. The result (sought by the rationalist models) should drive toward higher utility. Despite notable differences in researchers' theses (to be discussed in the full paper), one opinion shared is that the rational, economic, deliberate listing/evaluation of all options is NOT representative of how many decision are made. A framework gaining interest lately describes two systems predominantly at work: intuition and reasoning (Kahneman, 2003). Intuition is fast, automatic, and parallel contrasted with the more effortful, deliberative, and sequential reasoning. One of the issues of contention is that considerable research is stacked supporting both sides claiming that intuition is: • A hallmark of expertise responsible for rapid, optimal decisions in the face of adversity • A vulnerability where biases serve as decision traps leading to wrong choices Using seminal studies from a range of domains and tasking, potential solutions for SSA decision support will be offered. Important issues such as managing uncertainty, framing inquiries, and information architecture, and contextual cues will be discussed. The purpose is to provide awareness of the human limitations and capabilities in complex decision making so engineers and designers can consider such factors in their development of SSA tools.
Modelling human decision-making in coupled human and natural systems
NASA Astrophysics Data System (ADS)
Feola, G.
2012-12-01
A solid understanding of human decision-making is essential to analyze the complexity of coupled human and natural systems (CHANS) and inform policies to promote resilience in the face of environmental change. Human decisions drive and/or mediate the interactions and feedbacks, and contribute to the heterogeneity and non-linearity that characterize CHANS. However, human decision-making is usually over-simplistically modeled, whereby human agents are represented deterministically either as dumb or clairvoyant decision-makers. Decision-making models fall short in the integration of both environmental and human behavioral drivers, and concerning the latter, tend to focus on only one category, e.g. economic, cultural, or psychological. Furthermore, these models render a linear decision-making process and therefore fail to account for the recursive co-evolutionary dynamics in CHANS. As a result, these models constitute only a weak basis for policy-making. There is therefore scope and an urgent need for better approaches to human decision-making, to produce the knowledge that can inform vulnerability reduction policies in the face of environmental change. This presentation synthesizes the current state-of-the-art of modelling human decision-making in CHANS, with particular reference to agricultural systems, and delineates how the above mentioned shortcomings can be overcome. Through examples from research on pesticide use and adaptation to climate change, both based on the integrative agent-centered framework (Feola and Binder, 2010), the approach for an improved understanding of human agents in CHANS are illustrated. This entails: integrative approach, focus on behavioral dynamics more than states, feedbacks between individual and system levels, and openness to heterogeneity.
Military Medical Decision Support for Homeland Defense During Emergency
2004-12-01
abstraction hierarchy, three levels of information requirement for designing emergency training interface are recognized. These are epistemological ...support human decision making process is considered to be decision-centric. A typical decision-centric interface is supported by at least four design ... Designing Emergency Training Interface ......................................................................................... 5 Epistemological
ERIC Educational Resources Information Center
FRANKLIN, PAULA; FRANKLIN, RICHARD
THIS NATIONAL TRAINING LABORATORIES (NTL) CONFERENCE, DEPARTING SOMEWHAT FROM ITS USUAL EXPERIENCE-BASED LEARNING PROGRAMS, FOCUSED LABORATORY TRAINING METHODS ON THE DECISION-MAKING PROCESS IN URBAN COMMUNITY PROBLEM SOLVING. THE CONFERENCE PRESENTED THEORY, INFORMATION, AND OPINION ON THE NATURE OF CITIES AND THEIR DECISION-MAKING PROCESSES.…
Quantum stochastic walks on networks for decision-making.
Martínez-Martínez, Ismael; Sánchez-Burillo, Eduardo
2016-03-31
Recent experiments report violations of the classical law of total probability and incompatibility of certain mental representations when humans process and react to information. Evidence shows promise of a more general quantum theory providing a better explanation of the dynamics and structure of real decision-making processes than classical probability theory. Inspired by this, we show how the behavioral choice-probabilities can arise as the unique stationary distribution of quantum stochastic walkers on the classical network defined from Luce's response probabilities. This work is relevant because (i) we provide a very general framework integrating the positive characteristics of both quantum and classical approaches previously in confrontation, and (ii) we define a cognitive network which can be used to bring other connectivist approaches to decision-making into the quantum stochastic realm. We model the decision-maker as an open system in contact with her surrounding environment, and the time-length of the decision-making process reveals to be also a measure of the process' degree of interplay between the unitary and irreversible dynamics. Implementing quantum coherence on classical networks may be a door to better integrate human-like reasoning biases in stochastic models for decision-making.
Satisficing in split-second decision making is characterized by strategic cue discounting.
Oh, Hanna; Beck, Jeffrey M; Zhu, Pingping; Sommer, Marc A; Ferrari, Silvia; Egner, Tobias
2016-12-01
Much of our real-life decision making is bounded by uncertain information, limitations in cognitive resources, and a lack of time to allocate to the decision process. It is thought that humans overcome these limitations through satisficing, fast but "good-enough" heuristic decision making that prioritizes some sources of information (cues) while ignoring others. However, the decision-making strategies we adopt under uncertainty and time pressure, for example during emergencies that demand split-second choices, are presently unknown. To characterize these decision strategies quantitatively, the present study examined how people solve a novel multicue probabilistic classification task under varying time pressure, by tracking shifts in decision strategies using variational Bayesian inference. We found that under low time pressure, participants correctly weighted and integrated all available cues to arrive at near-optimal decisions. With increasingly demanding, subsecond time pressures, however, participants systematically discounted a subset of the cue information by dropping the least informative cue(s) from their decision making process. Thus, the human cognitive apparatus copes with uncertainty and severe time pressure by adopting a "drop-the-worst" cue decision making strategy that minimizes cognitive time and effort investment while preserving the consideration of the most diagnostic cue information, thus maintaining "good-enough" accuracy. This advance in our understanding of satisficing strategies could form the basis of predicting human choices in high time pressure scenarios. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
DOE Office of Scientific and Technical Information (OSTI.GOV)
RAYBOURN,ELAINE M.; FORSYTHE,JAMES C.
2001-08-01
This report documents an exploratory FY 00 LDRD project that sought to demonstrate the first steps toward a realistic computational representation of the variability encountered in individual human behavior. Realism, as conceptualized in this project, required that the human representation address the underlying psychological, cultural, physiological, and environmental stressors. The present report outlines the researchers' approach to representing cognitive, cultural, and physiological variability of an individual in an ambiguous situation while faced with a high-consequence decision that would greatly impact subsequent events. The present project was framed around a sensor-shooter scenario as a soldier interacts with an unexpected target (twomore » young Iraqi girls). A software model of the ''Sensor Shooter'' scenario from Desert Storm was developed in which the framework consisted of a computational instantiation of Recognition Primed Decision Making in the context of a Naturalistic Decision Making model [1]. Recognition Primed Decision Making was augmented with an underlying foundation based on our current understanding of human neurophysiology and its relationship to human cognitive processes. While the Gulf War scenario that constitutes the framework for the Sensor Shooter prototype is highly specific, the human decision architecture and the subsequent simulation are applicable to other problems similar in concept, intensity, and degree of uncertainty. The goal was to provide initial steps toward a computational representation of human variability in cultural, cognitive, and physiological state in order to attain a better understanding of the full depth of human decision-making processes in the context of ambiguity, novelty, and heightened arousal.« less
Analysis of the decision-making process of nurse managers: a collective reflection.
Eduardo, Elizabete Araujo; Peres, Aida Maris; de Almeida, Maria de Lourdes; Roglio, Karina de Dea; Bernardino, Elizabeth
2015-01-01
to analyze the decision-making model adopted by nurses from the perspective of some decision-making process theories. qualitative approach, based on action research. Semi-structured questionnaires and seminars were conducted from April to June 2012 in order to understand the nature of decisions and the decision-making process of nine nurses in position of managers at a public hospital in Southern Brazil. Data were subjected to content analysis. data were classified in two categories: the current situation of decision-making, which showed a lack of systematization; the construction and collective decision-making, which emphasizes the need to develop a decision-making model. the decision-making model used by nurses is limited because it does not consider two important factors: the limits of human rationality, and the external and internal organizational environments that influence and determine right decisions.
Insect pest management decisions in food processing facilities
USDA-ARS?s Scientific Manuscript database
Pest management decision making in food processing facilities such as flour mills, rice mills, human and pet food manufacturing facilities, distribution centers and warehouses, and retail stores is a challenging undertaking. Insect pest management programs require an understanding of the food facili...
The Neuropsychology of Ventral Prefrontal Cortex: Decision-Making and Reversal Learning
ERIC Educational Resources Information Center
Clark, L.; Cools, R.; Robbins, T. W.
2004-01-01
Converging evidence from human lesion, animal lesion, and human functional neuroimaging studies implicates overlapping neural circuitry in ventral prefrontal cortex in decision-making and reversal learning. The ascending 5-HT and dopamine neurotransmitter systems have a modulatory role in both processes. There is accumulating evidence that…
[Factors behind action, emotion, and decision making].
Watanabe, Katsumi
2009-12-01
Human actions, emotions, and decision making are products of complex interactions between explicit and implicit processes at various levels of spatial and temporal scales. Although it may not be possible to obtain to experimental data for all the complexity of human behavioral and emotional processes in our everyday life, recent studies have investigated the effects of social contexts on actions, emotions, and decision making; these studies include those in the fields of experimental psychology, cognitive science, and neuroscience. In this paper, we review several empirical studies that exemplify how our actions, social emotions, and decision making are influenced by the presence of implicit external, rather than internal factors, particularly by presence of other individuals. The following are the main principles identified. (1) Unconscious behavioral contagion: Individuals tend to mimic others' actions. This tendency occurs unconsciously even when the observed and the to-be-executed movements are unrelated at various levels and aspects of behaviors (e. g., behavioral tempo and speed). (2) Neural substrates of social emotions: Various social emotions, including admiration, compassion, envy, and schadenfreude, are represented in neuronal networks that are similar to those of basic emotional processes. (3) Evasive nature of human decision making: Individuals tend to overrate their own subjective impression of and emotional reaction in forecasting affective reaction to events in the future, even though the predictive power of information from peer group is much larger in this regard. Individuals are seldom aware of the dissociation between their intended choice and excuted actions and are willing to give elaborate explanations for the choices they, in fact, did not make. Using these empirical examples, I will illustrate the considerable influences of implicit, unconscious processes on human actions, emotions, and decision making.
Explaining Enhanced Logical Consistency during Decision Making in Autism
De Martino, Benedetto; Harrison, Neil A.; Knafo, Steven; Bird, Geoff; Dolan, Raymond J.
2009-01-01
The emotional responses elicited by the way options are framed often results in lack of logical consistency in human decision making. In this study, we investigated subjects with autism spectrum disorder (ASD) using a financial task in which the monetary prospects were presented as either loss or gain. We report both behavioral evidence that ASD subjects show a reduced susceptibility to the framing effect and psycho-physiological evidence that they fail to incorporate emotional context into the decision-making process. On this basis, we suggest that this insensitivity to contextual frame, although enhancing choice consistency in ASD, may also underpin core deficits in this disorder. These data highlight both benefits and costs arising from multiple decision processes in human cognition. PMID:18923049
Explaining enhanced logical consistency during decision making in autism.
De Martino, Benedetto; Harrison, Neil A; Knafo, Steven; Bird, Geoff; Dolan, Raymond J
2008-10-15
The emotional responses elicited by the way options are framed often results in lack of logical consistency in human decision making. In this study, we investigated subjects with autism spectrum disorder (ASD) using a financial task in which the monetary prospects were presented as either loss or gain. We report both behavioral evidence that ASD subjects show a reduced susceptibility to the framing effect and psycho-physiological evidence that they fail to incorporate emotional context into the decision-making process. On this basis, we suggest that this insensitivity to contextual frame, although enhancing choice consistency in ASD, may also underpin core deficits in this disorder. These data highlight both benefits and costs arising from multiple decision processes in human cognition.
A model of the human observer and decision maker
NASA Technical Reports Server (NTRS)
Wewerinke, P. H.
1981-01-01
The decision process is described in terms of classical sequential decision theory by considering the hypothesis that an abnormal condition has occurred by means of a generalized likelihood ratio test. For this, a sufficient statistic is provided by the innovation sequence which is the result of the perception an information processing submodel of the human observer. On the basis of only two model parameters, the model predicts the decision speed/accuracy trade-off and various attentional characteristics. A preliminary test of the model for single variable failure detection tasks resulted in a very good fit of the experimental data. In a formal validation program, a variety of multivariable failure detection tasks was investigated and the predictive capability of the model was demonstrated.
Lattanzi, Nicola; Menicagli, Dario; Dal Maso, Lorenzo
2016-04-01
Globalization phenomena and Information Communication Technology (ICT) are producing deep changes worldwide. The economic environment and society where firms both cooperate and compete with each other are rapidly changing leading firms towards recognizing the role of intangible resources as a source of fresh competitive advantage. Experience, innovation and the ability to create new knowledge completely arise from the act of human resources inviting firms to focus on how to generate and shape knowledge. Therefore, the future of firms depends greatly on how managers are able to explore and exploit human resources. However, without a clear understanding of the nature of human beings and the complexity behind human interactions, we cannot understand the theory of organizational knowledge creation. Thus, how can firms discover, manage and valorize this "human advantage"? Neuroscience can increase the understanding of how cognitive and emotional processes work; in doing so, we may be able to better understand how individuals involved in a business organization make decisions and how external factors influence their behavior, especially in terms of commitment activation and engagement level. In this respect, a neuroscientific approach to business can support managers in decision-making processes. In a scenario where economic humanism plays a central role in the process of fostering firms' competitiveness and emerging strategies, we believe that a neuroscience approach in a business organization could be a valid source of value and inspiration for manager decision-making processes.
Human Judgment and Decision Making: Models and Applications.
ERIC Educational Resources Information Center
Loke, Wing Hong
This document notes that researchers study the processes involved in judgment and decision making and prescribe theories and models that reflect the behavior of the decision makers. It addresses the various models that are used to represent judgment and decision making, with particular interest in models that more accurately represent human…
Searching Choices: Quantifying Decision-Making Processes Using Search Engine Data.
Moat, Helen Susannah; Olivola, Christopher Y; Chater, Nick; Preis, Tobias
2016-07-01
When making a decision, humans consider two types of information: information they have acquired through their prior experience of the world, and further information they gather to support the decision in question. Here, we present evidence that data from search engines such as Google can help us model both sources of information. We show that statistics from search engines on the frequency of content on the Internet can help us estimate the statistical structure of prior experience; and, specifically, we outline how such statistics can inform psychological theories concerning the valuation of human lives, or choices involving delayed outcomes. Turning to information gathering, we show that search query data might help measure human information gathering, and it may predict subsequent decisions. Such data enable us to compare information gathered across nations, where analyses suggest, for example, a greater focus on the future in countries with a higher per capita GDP. We conclude that search engine data constitute a valuable new resource for cognitive scientists, offering a fascinating new tool for understanding the human decision-making process. Copyright © 2016 The Authors. Topics in Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.
King, L A; Lévy-Bruhl, D; O'Flanagan, D; Bacci, S; Lopalco, P L; Kudjawu, Y; Salmaso, S
2008-08-14
The European Union Member States are simultaneously considering introducing HPV vaccination into their national immunisation schedules. The Vaccine European New Integrated Collaboration Effort (VENICE) project aims to develop a collaborative European vaccination network. A survey was undertaken to describe the decision status and the decision-making process regarding the potential introduction of human papillomavirus (HPV) vaccination in to their national immunisation schedules. A web-based questionnaire was developed and completed online in 2007 by 28 countries participating in VENICE. As of 31 October 2007,five countries had decided to introduce HPV vaccination into the national immunisation schedule, while another seven had started the decision-making process with a recommendation favouring introduction. Varying target populations were selected by the five countries which had introduced the vaccination. Half of the surveyed countries had undertaken at least one ad hoc study to support the decision-making process. According to an update of the decision-status from January 2008, the number of countries which had made a decision or recommendation changed to 10 and 5 respectively. This survey demonstrates the rapidly evolving nature of HPV vaccine introduction in Europe and the existence of expertise and experience among EU Member States. The VENICE network is capable of following this process and supporting countries in making vaccine introduction decisions. A VENICE collaborative web-space is being developed as a European resource for the decision-making process for vaccine introduction.
Workload Capacity: A Response Time-Based Measure of Automation Dependence.
Yamani, Yusuke; McCarley, Jason S
2016-05-01
An experiment used the workload capacity measure C(t) to quantify the processing efficiency of human-automation teams and identify operators' automation usage strategies in a speeded decision task. Although response accuracy rates and related measures are often used to measure the influence of an automated decision aid on human performance, aids can also influence response speed. Mean response times (RTs), however, conflate the influence of the human operator and the automated aid on team performance and may mask changes in the operator's performance strategy under aided conditions. The present study used a measure of parallel processing efficiency, or workload capacity, derived from empirical RT distributions as a novel gauge of human-automation performance and automation dependence in a speeded task. Participants performed a speeded probabilistic decision task with and without the assistance of an automated aid. RT distributions were used to calculate two variants of a workload capacity measure, COR(t) and CAND(t). Capacity measures gave evidence that a diagnosis from the automated aid speeded human participants' responses, and that participants did not moderate their own decision times in anticipation of diagnoses from the aid. Workload capacity provides a sensitive and informative measure of human-automation performance and operators' automation dependence in speeded tasks. © 2016, Human Factors and Ergonomics Society.
NASA Technical Reports Server (NTRS)
Williams-Byrd, Julie; Arney, Dale C.; Hay, Jason; Reeves, John D.; Craig, Douglas
2016-01-01
NASA is transforming human spaceflight. The Agency is shifting from an exploration-based program with human activities in low Earth orbit (LEO) and targeted robotic missions in deep space to a more sustainable and integrated pioneering approach. Through pioneering, NASA seeks to address national goals to develop the capacity for people to work, learn, operate, live, and thrive safely beyond Earth for extended periods of time. However, pioneering space involves daunting technical challenges of transportation, maintaining health, and enabling crew productivity for long durations in remote, hostile, and alien environments. Prudent investments in capability and technology developments, based on mission need, are critical for enabling a campaign of human exploration missions. There are a wide variety of capabilities and technologies that could enable these missions, so it is a major challenge for NASA's Human Exploration and Operations Mission Directorate (HEOMD) to make knowledgeable portfolio decisions. It is critical for this pioneering initiative that these investment decisions are informed with a prioritization process that is robust and defensible. It is NASA's role to invest in targeted technologies and capabilities that would enable exploration missions even though specific requirements have not been identified. To inform these investments decisions, NASA's HEOMD has supported a variety of analysis activities that prioritize capabilities and technologies. These activities are often based on input from subject matter experts within the NASA community who understand the technical challenges of enabling human exploration missions. This paper will review a variety of processes and methods that NASA has used to prioritize and rank capabilities and technologies applicable to human space exploration. The paper will show the similarities in the various processes and showcase instances were customer specified priorities force modifications to the process. Specifically, this paper will describe the processes that the NASA Langley Research Center (LaRC) Technology Assessment and Integration Team (TAIT) has used for several years and how those processes have been customized to meet customer needs while staying robust and defensible. This paper will show how HEOMD uses these analyses results to assist with making informed portfolio investment decisions. The paper will also highlight which human exploration capabilities and technologies typically rank high regardless of the specific design reference mission. The paper will conclude by describing future capability and technology ranking activities that will continue o leverage subject matter experts (SME) input while also incorporating more model-based analysis.
Identifying the Complexities within Clients' Thinking and Decision Making.
ERIC Educational Resources Information Center
Heppner, P. Paul
1989-01-01
Responds to Gelatt's conception of decision making in counseling. Concurs with need for a broader view of human reasoning that includes complex processes, both rational and intuitive. Advocates examination of how clients think, feel, and behave as they process information during counseling. (Author/TE)
Processing of social and monetary rewards in the human striatum.
Izuma, Keise; Saito, Daisuke N; Sadato, Norihiro
2008-04-24
Despite an increasing focus on the neural basis of human decision making in neuroscience, relatively little attention has been paid to decision making in social settings. Moreover, although human social decision making has been explored in a social psychology context, few neural explanations for the observed findings have been considered. To bridge this gap and improve models of human social decision making, we investigated whether acquiring a good reputation, which is an important incentive in human social behaviors, activates the same reward circuitry as monetary rewards. In total, 19 subjects participated in functional magnetic resonance imaging (fMRI) experiments involving monetary and social rewards. The acquisition of one's good reputation robustly activated reward-related brain areas, notably the striatum, and these overlapped with the areas activated by monetary rewards. Our findings support the idea of a "common neural currency" for rewards and represent an important first step toward a neural explanation for complex human social behaviors.
Exploring Effective Decision Making through Human-Centered and Computational Intelligence Methods
DOE Office of Scientific and Technical Information (OSTI.GOV)
Han, Kyungsik; Cook, Kristin A.; Shih, Patrick C.
Decision-making has long been studied to understand a psychological, cognitive, and social process of selecting an effective choice from alternative options. Its studies have been extended from a personal level to a group and collaborative level, and many computer-aided decision-making systems have been developed to help people make right decisions. There has been significant research growth in computational aspects of decision-making systems, yet comparatively little effort has existed in identifying and articulating user needs and requirements in assessing system outputs and the extent to which human judgments could be utilized for making accurate and reliable decisions. Our research focus ismore » decision-making through human-centered and computational intelligence methods in a collaborative environment, and the objectives of this position paper are to bring our research ideas to the workshop, and share and discuss ideas.« less
Chimpanzees and Bonobos Exhibit Emotional Responses to Decision Outcomes
Rosati, Alexandra G.; Hare, Brian
2013-01-01
The interface between cognition, emotion, and motivation is thought to be of central importance in understanding complex cognitive functions such as decision-making and executive control in humans. Although nonhuman apes have complex repertoires of emotional expression, little is known about the role of affective processes in ape decision-making. To illuminate the evolutionary origins of human-like patterns of choice, we investigated decision-making in humans' closest phylogenetic relatives, chimpanzees (Pan troglodytes) and bonobos (Pan paniscus). In two studies, we examined these species' temporal and risk preferences, and assessed whether apes show emotional and motivational responses in decision-making contexts. We find that (1) chimpanzees are more patient and more risk-prone than are bonobos, (2) both species exhibit affective and motivational responses following the outcomes of their decisions, and (3) some emotional and motivational responses map onto species-level and individual-differences in decision-making. These results indicate that apes do exhibit emotional responses to decision-making, like humans. We explore the hypothesis that affective and motivational biases may underlie the psychological mechanisms supporting value-based preferences in these species. PMID:23734175
Cogenerating a Competency-based HRM Degree: A Model and Some Lessons from Experience.
ERIC Educational Resources Information Center
Wooten, Kevin C.; Elden, Max
2001-01-01
A competency-based degree program in human resource management was co-generated by six groups of stakeholders who synthesized competency models using group decision support software. The program focuses on core human resource processes, general business management, strategic decision making and problem solving, change management, and personal…
An Investigation of Data Overload in Team-Based Distributed Cognition Systems
ERIC Educational Resources Information Center
Hellar, David Benjamin
2009-01-01
The modern military command center is a hybrid system of computer automated surveillance and human oriented decision making. In these distributed cognition systems, data overload refers simultaneously to the glut of raw data processed by information technology systems and the dearth of actionable knowledge useful to human decision makers.…
Design of a Production System for Cognitive Modeling #1. Technical Report 77-2.
ERIC Educational Resources Information Center
Anderson, John R.; Kline, Paul J.
This report describes several of the design decisions underlying ACT, a production system model of human cognition. ACT can be considered a high level computer programming language as well as a theory of the cognitive mechanisms underlying human information processing. ACT design decisions were based on both psychological and artificial…
Decision insight into stakeholder conflict for ERN.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Siirola, John; Tidwell, Vincent Carroll; Benz, Zachary O.
Participatory modeling has become an important tool in facilitating resource decision making and dispute resolution. Approaches to modeling that are commonly used in this context often do not adequately account for important human factors. Current techniques provide insights into how certain human activities and variables affect resource outcomes; however, they do not directly simulate the complex variables that shape how, why, and under what conditions different human agents behave in ways that affect resources and human interactions related to them. Current approaches also do not adequately reveal how the effects of individual decisions scale up to have systemic level effectsmore » in complex resource systems. This lack of integration prevents the development of more robust models to support decision making and dispute resolution processes. Development of integrated tools is further hampered by the fact that collection of primary data for decision-making modeling is costly and time consuming. This project seeks to develop a new approach to resource modeling that incorporates both technical and behavioral modeling techniques into a single decision-making architecture. The modeling platform is enhanced by use of traditional and advanced processes and tools for expedited data capture. Specific objectives of the project are: (1) Develop a proof of concept for a new technical approach to resource modeling that combines the computational techniques of system dynamics and agent based modeling, (2) Develop an iterative, participatory modeling process supported with traditional and advance data capture techniques that may be utilized to facilitate decision making, dispute resolution, and collaborative learning processes, and (3) Examine potential applications of this technology and process. The development of this decision support architecture included both the engineering of the technology and the development of a participatory method to build and apply the technology. Stakeholder interaction with the model and associated data capture was facilitated through two very different modes of engagement, one a standard interface involving radio buttons, slider bars, graphs and plots, while the other utilized an immersive serious gaming interface. The decision support architecture developed through this project was piloted in the Middle Rio Grande Basin to examine how these tools might be utilized to promote enhanced understanding and decision-making in the context of complex water resource management issues. Potential applications of this architecture and its capacity to lead to enhanced understanding and decision-making was assessed through qualitative interviews with study participants who represented key stakeholders in the basin.« less
Leveraging human decision making through the optimal management of centralized resources
NASA Astrophysics Data System (ADS)
Hyden, Paul; McGrath, Richard G.
2016-05-01
Combining results from mixed integer optimization, stochastic modeling and queuing theory, we will advance the interdisciplinary problem of efficiently and effectively allocating centrally managed resources. Academia currently fails to address this, as the esoteric demands of each of these large research areas limits work across traditional boundaries. The commercial space does not currently address these challenges due to the absence of a profit metric. By constructing algorithms that explicitly use inputs across boundaries, we are able to incorporate the advantages of using human decision makers. Key improvements in the underlying algorithms are made possible by aligning decision maker goals with the feedback loops introduced between the core optimization step and the modeling of the overall stochastic process of supply and demand. A key observation is that human decision-makers must be explicitly included in the analysis for these approaches to be ultimately successful. Transformative access gives warfighters and mission owners greater understanding of global needs and allows for relationships to guide optimal resource allocation decisions. Mastery of demand processes and optimization bottlenecks reveals long term maximum marginal utility gaps in capabilities.
Satisficing in Split-Second Decision Making Is Characterized by Strategic Cue Discounting
ERIC Educational Resources Information Center
Oh, Hanna; Beck, Jeffrey M.; Zhu, Pingping; Sommer, Marc A.; Ferrari, Silvia; Egner, Tobias
2016-01-01
Much of our real-life decision making is bounded by uncertain information, limitations in cognitive resources, and a lack of time to allocate to the decision process. It is thought that humans overcome these limitations through "satisficing," fast but "good-enough" heuristic decision making that prioritizes some sources of…
The value of decision models: Using ecologically based invasive plant management as an example
USDA-ARS?s Scientific Manuscript database
Humans have both fast and slow thought processes which influence our judgment and decision-making. The fast system is intuitive and valuable for decisions which do not require multiple steps or the application of logic or statistics. However, many decisions in natural resources are complex and req...
ERIC Educational Resources Information Center
Jazby, Dan
2014-01-01
Research into human decision making (DM) processes from outside of education paint a different picture of DM than current DM models in education. This pilot study assesses the use of critical decision method (CDM)--developed from observations of firefighters' DM -- in the context of primary mathematics teachers' in-class DM. Preliminary results…
Issues in Developing a Normative Descriptive Model for Dyadic Decision Making
NASA Technical Reports Server (NTRS)
Serfaty, D.; Kleinman, D. L.
1984-01-01
Most research in modelling human information processing and decision making has been devoted to the case of the single human operator. In the present effort, concepts from the fields of organizational behavior, engineering psychology, team theory and mathematical modelling are merged in an attempt to consider first the case of two cooperating decisionmakers (the Dyad) in a multi-task environment. Rooted in the well-known Dynamic Decision Model (DDM), the normative descriptive approach brings basic cognitive and psychophysical characteristics inherent to human behavior into a team theoretic analytic framework. An experimental paradigm, involving teams in dynamic decision making tasks, is designed to produce the data with which to build the theoretical model.
Variables, Decisions, and Scripting in Construct
2009-09-01
grounded in sociology and cognitive science which seeks to model the processes and situations by which humans interact and share information...Construct is an embodiment of constructuralism (Carley 1986), a theory which posits that human social structures and cognitive structures co-evolve so that...human cognition reflects human social behavior, and that human social behavior simultaneously influences cognitive processes. Recent work with
A model of human event detection in multiple process monitoring situations
NASA Technical Reports Server (NTRS)
Greenstein, J. S.; Rouse, W. B.
1978-01-01
It is proposed that human decision making in many multi-task situations might be modeled in terms of the manner in which the human detects events related to his tasks and the manner in which he allocates his attention among his tasks once he feels events have occurred. A model of human event detection performance in such a situation is presented. An assumption of the model is that, in attempting to detect events, the human generates the probability that events have occurred. Discriminant analysis is used to model the human's generation of these probabilities. An experimental study of human event detection performance in a multiple process monitoring situation is described and the application of the event detection model to this situation is addressed. The experimental study employed a situation in which subjects simulataneously monitored several dynamic processes for the occurrence of events and made yes/no decisions on the presence of events in each process. Input to the event detection model of the information displayed to the experimental subjects allows comparison of the model's performance with the performance of the subjects.
The Effect of Shared Information on Pilot/Controller And Controller/Controller Interactions
NASA Technical Reports Server (NTRS)
Hansman, R. John
1999-01-01
In order to respond to the increasing demand on limited airspace system resources, a number of applications of information technology have been proposed, or are under investigation, to improve the efficiency, capacity and reliability of ATM (Asynchronous Transfer Mode) operations. Much of the attention in advanced ATM technology has focused on advanced automation systems or decision aiding systems to improve the performance of individual Pilots or Controllers. However, the most significant overall potential for information technology appears to he in increasing the shared information between human agents such as Pilots, Controllers or between interacting Controllers or traffic flow managers. Examples of proposed shared information systems in the US include; Controller Pilot Databank Communication (CPDLC), Traffic Management Advisor (TMA); Automatic Dependent Surveillance (ADS); Collaborative Decision Making (CDM) and NAS Level Common Information Exchange. Air Traffic Management is fundamentally a human centered process consisting of the negotiation, execution and monitoring of contracts between human agents for the allocation of limited airspace, runway and airport surface resources. The decision processes within ATM tend to be Semistructured. Many of the routine elements in ATM decision making on the part of the Controllers or Pilots are well Structured and can be represented by well defined rules or procedures. However in disrupted conditions, the ATM decision processes are often Unstructured and cannot be reduced to a set of discrete rules. As a consequence, the ability to automate ATM processes will be limited and ATM will continue to be a human centric process where the responsibility and the authority for the negotiation will continue to rest with human Controllers and Pilots. The use of information technology to support the human decision process will therefore be an important aspect of ATM modernization. The premise of many of the proposed shared information systems is that the performance of ATM operations will improve with an increase in Shared Situation Awareness between agents (Pilots, Controller, Dispatchers). This will allow better informed control decisions and an improved ability to negotiate between agents. A common information basis may reduce communication load and may increase the level of collaboration in the decision process. In general, information sharing is expected to have advantages for all agents within the system. However there are important questions which remain to be,addressed. For example: What shared information is most important for developing effective Shared Situation Awareness? Are there issues of information saturation? Does information parity create ambiguity in control authority? Will information sharing induce undesirable or unstable gaming behavior between agents? This paper will explore the effect of current and proposed information sharing between different ATM agents. The paper will primarily concentrate on bilateral tactical interactions between specific agents (Pilot/Controller; Controller/Controller; Pilot/Dispatcher; Controller/Dispatcher) however it will also briefly discuss multilateral interaction and more strategic interactions.
Human-provided waters for desert wildlife: What is the problem?
Mattson, D.J.; Chambers, N.
2009-01-01
Conflict persists in southwestern deserts of the United States over management of human-constructed devices to provide wildlife with water. We appraised decision processes in this case relative to the goal of human dignity and by the standards of civility and common interest outcomes. Our analysis suggested that conflict was scientized, rooted in worldviews, and aggravated by use of inflammatory symbols such as "wilderness" and "bighorn sheep." Contested problem definitions, framed as matters of science, advanced factional interests largely by allocating the burden of proof and failing to disclose private concerns about well-being, affection, respect, skill and power. Decision processes were shaped by precepts of scientific management, and thus largely failed to foster civility, common ground, and a focus on common interests, and instead tended to exacerbate deprivations of dignity and respect. If the status quo continues, we foresee further erosion of human dignity because there are likely to be increases in system stressors, such as climate change and human population growth. The prognosis would be more hopeful if alternatives were adopted that entailed authoritative, equitable, and collaborative public decision-making processes that took into consideration national-level common interests such as the U.S. Endangered Species Act. ?? Springer Science+Business Media, LLC. 2008.
Cognitive processes in anesthesiology decision making.
Stiegler, Marjorie Podraza; Tung, Avery
2014-01-01
The quality and safety of health care are under increasing scrutiny. Recent studies suggest that medical errors, practice variability, and guideline noncompliance are common, and that cognitive error contributes significantly to delayed or incorrect diagnoses. These observations have increased interest in understanding decision-making psychology.Many nonrational (i.e., not purely based in statistics) cognitive factors influence medical decisions and may lead to error. The most well-studied include heuristics, preferences for certainty, overconfidence, affective (emotional) influences, memory distortions, bias, and social forces such as fairness or blame.Although the extent to which such cognitive processes play a role in anesthesia practice is unknown, anesthesia care frequently requires rapid, complex decisions that are most susceptible to decision errors. This review will examine current theories of human decision behavior, identify effects of nonrational cognitive processes on decision making, describe characteristic anesthesia decisions in this context, and suggest strategies to improve decision making.
Multiple Transient Signals in Human Visual Cortex Associated with an Elementary Decision
Nolte, Guido
2017-01-01
The cerebral cortex continuously undergoes changes in its state, which are manifested in transient modulations of the cortical power spectrum. Cortical state changes also occur at full wakefulness and during rapid cognitive acts, such as perceptual decisions. Previous studies found a global modulation of beta-band (12–30 Hz) activity in human and monkey visual cortex during an elementary visual decision: reporting the appearance or disappearance of salient visual targets surrounded by a distractor. The previous studies disentangled neither the motor action associated with behavioral report nor other secondary processes, such as arousal, from perceptual decision processing per se. Here, we used magnetoencephalography in humans to pinpoint the factors underlying the beta-band modulation. We found that disappearances of a salient target were associated with beta-band suppression, and target reappearances with beta-band enhancement. This was true for both overt behavioral reports (immediate button presses) and silent counting of the perceptual events. This finding indicates that the beta-band modulation was unrelated to the execution of the motor act associated with a behavioral report of the perceptual decision. Further, changes in pupil-linked arousal, fixational eye movements, or gamma-band responses were not necessary for the beta-band modulation. Together, our results suggest that the beta-band modulation was a top-down signal associated with the process of converting graded perceptual signals into a categorical format underlying flexible behavior. This signal may have been fed back from brain regions involved in decision processing to visual cortex, thus enforcing a “decision-consistent” cortical state. SIGNIFICANCE STATEMENT Elementary visual decisions are associated with a rapid state change in visual cortex, indexed by a modulation of neural activity in the beta-frequency range. Such decisions are also followed by other events that might affect the state of visual cortex, including the motor command associated with the report of the decision, an increase in pupil-linked arousal, fixational eye movements, and fluctuations in bottom-up sensory processing. Here, we ruled out the necessity of these events for the beta-band modulation of visual cortex. We propose that the modulation reflects a decision-related state change, which is induced by the conversion of graded perceptual signals into a categorical format underlying behavior. The resulting decision signal may be fed back to visual cortex. PMID:28495972
Code of Federal Regulations, 2010 CFR
2010-07-01
... decision-making reflect Army environmental values, such as compliance with environmental policy, laws, and... early as possible to avoid potential delays. (b) All Army decision-making that may impact the human... ENVIRONMENTAL ANALYSIS OF ARMY ACTIONS (AR 200-2) National Environmental Policy Act and the Decision Process...
Incorporating BDI Agents into Human-Agent Decision Making Research
NASA Astrophysics Data System (ADS)
Kamphorst, Bart; van Wissen, Arlette; Dignum, Virginia
Artificial agents, people, institutes and societies all have the ability to make decisions. Decision making as a research area therefore involves a broad spectrum of sciences, ranging from Artificial Intelligence to economics to psychology. The Colored Trails (CT) framework is designed to aid researchers in all fields in examining decision making processes. It is developed both to study interaction between multiple actors (humans or software agents) in a dynamic environment, and to study and model the decision making of these actors. However, agents in the current implementation of CT lack the explanatory power to help understand the reasoning processes involved in decision making. The BDI paradigm that has been proposed in the agent research area to describe rational agents, enables the specification of agents that reason in abstract concepts such as beliefs, goals, plans and events. In this paper, we present CTAPL: an extension to CT that allows BDI software agents that are written in the practical agent programming language 2APL to reason about and interact with a CT environment.
Decision Support Model for Introduction of Gamification Solution Using AHP
2014-01-01
Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform. PMID:24892075
Decision support model for introduction of gamification solution using AHP.
Kim, Sangkyun
2014-01-01
Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform.
NASA Technical Reports Server (NTRS)
Frankel, M. S.
1972-01-01
The policy making process which led to development of the Public Health Service Guidelines governing research involving human subjects is outlined. Part 1 examines the evolution of PHS Guidelines, tracing (1) evolution of thought and legal interpretation regarding research using human subjects; (2) initial involvement of the Federal government; (3) development of the government's research program; (4) the social-political environment in which formal government policy was developed; and (5) various policy statements issued by the government. Part 2 analyzes the process by which PHS Guidelines were developed and examines the values and other underlying factors which contributed to their development. It was concluded that the evolution of the Guidelines is best understood within the context of a mixed-scanning strategy. In such a strategy, policy makers make fundamental decisions regarding the basic direction of policy and subsequent decisions are made incrementally and within the contexts set by the original fundamental decisions.
Nonrational processes in ethical decision making.
Rogerson, Mark D; Gottlieb, Michael C; Handelsman, Mitchell M; Knapp, Samuel; Younggren, Jeffrey
2011-10-01
Most current ethical decision-making models provide a logical and reasoned process for making ethical judgments, but these models are empirically unproven and rely upon assumptions of rational, conscious, and quasilegal reasoning. Such models predominate despite the fact that many nonrational factors influence ethical thought and behavior, including context, perceptions, relationships, emotions, and heuristics. For example, a large body of behavioral research has demonstrated the importance of automatic intuitive and affective processes in decision making and judgment. These processes profoundly affect human behavior and lead to systematic biases and departures from normative theories of rationality. Their influence represents an important but largely unrecognized component of ethical decision making. We selectively review this work; provide various illustrations; and make recommendations for scientists, trainers, and practitioners to aid them in integrating the understanding of nonrational processes with ethical decision making.
Incorporating affective bias in models of human decision making
NASA Technical Reports Server (NTRS)
Nygren, Thomas E.
1991-01-01
Research on human decision making has traditionally focused on how people actually make decisions, how good their decisions are, and how their decisions can be improved. Recent research suggests that this model is inadequate. Affective as well as cognitive components drive the way information about relevant outcomes and events is perceived, integrated, and used in the decision making process. The affective components include how the individual frames outcomes as good or bad, whether the individual anticipates regret in a decision situation, the affective mood state of the individual, and the psychological stress level anticipated or experienced in the decision situation. A focus of the current work has been to propose empirical studies that will attempt to examine in more detail the relationships between the latter two critical affective influences (mood state and stress) on decision making behavior.
Quantum stochastic walks on networks for decision-making
NASA Astrophysics Data System (ADS)
Martínez-Martínez, Ismael; Sánchez-Burillo, Eduardo
2016-03-01
Recent experiments report violations of the classical law of total probability and incompatibility of certain mental representations when humans process and react to information. Evidence shows promise of a more general quantum theory providing a better explanation of the dynamics and structure of real decision-making processes than classical probability theory. Inspired by this, we show how the behavioral choice-probabilities can arise as the unique stationary distribution of quantum stochastic walkers on the classical network defined from Luce’s response probabilities. This work is relevant because (i) we provide a very general framework integrating the positive characteristics of both quantum and classical approaches previously in confrontation, and (ii) we define a cognitive network which can be used to bring other connectivist approaches to decision-making into the quantum stochastic realm. We model the decision-maker as an open system in contact with her surrounding environment, and the time-length of the decision-making process reveals to be also a measure of the process’ degree of interplay between the unitary and irreversible dynamics. Implementing quantum coherence on classical networks may be a door to better integrate human-like reasoning biases in stochastic models for decision-making.
Quantum stochastic walks on networks for decision-making
Martínez-Martínez, Ismael; Sánchez-Burillo, Eduardo
2016-01-01
Recent experiments report violations of the classical law of total probability and incompatibility of certain mental representations when humans process and react to information. Evidence shows promise of a more general quantum theory providing a better explanation of the dynamics and structure of real decision-making processes than classical probability theory. Inspired by this, we show how the behavioral choice-probabilities can arise as the unique stationary distribution of quantum stochastic walkers on the classical network defined from Luce’s response probabilities. This work is relevant because (i) we provide a very general framework integrating the positive characteristics of both quantum and classical approaches previously in confrontation, and (ii) we define a cognitive network which can be used to bring other connectivist approaches to decision-making into the quantum stochastic realm. We model the decision-maker as an open system in contact with her surrounding environment, and the time-length of the decision-making process reveals to be also a measure of the process’ degree of interplay between the unitary and irreversible dynamics. Implementing quantum coherence on classical networks may be a door to better integrate human-like reasoning biases in stochastic models for decision-making. PMID:27030372
A Hyperknowledge Framework of Decision Support Systems.
ERIC Educational Resources Information Center
Chang, Ai-Mei; And Others
1994-01-01
Presents a hyperknowledge framework of decision support systems (DSS). This framework formalizes specifics about system functionality, representation of knowledge, navigation of the knowledge system, and user-interface traits as elements of a DSS environment that conforms closely to human cognitive processes in decision making. (Contains 52…
Decision Making: Rational, Nonrational, and Irrational.
ERIC Educational Resources Information Center
Simon, Herbert A.
1993-01-01
Describes the current state of knowledge about human decision-making and problem-solving processes, explaining recent developments and their implications for management and management training. Rational goal-setting is the key to effective decision making and accomplishment. Bounded rationality is a realistic orientation, because the world is too…
NASA Astrophysics Data System (ADS)
Rimland, Jeffrey; McNeese, Michael; Hall, David
2013-05-01
Although the capability of computer-based artificial intelligence techniques for decision-making and situational awareness has seen notable improvement over the last several decades, the current state-of-the-art still falls short of creating computer systems capable of autonomously making complex decisions and judgments in many domains where data is nuanced and accountability is high. However, there is a great deal of potential for hybrid systems in which software applications augment human capabilities by focusing the analyst's attention to relevant information elements based on both a priori knowledge of the analyst's goals and the processing/correlation of a series of data streams too numerous and heterogeneous for the analyst to digest without assistance. Researchers at Penn State University are exploring ways in which an information framework influenced by Klein's (Recognition Primed Decision) RPD model, Endsley's model of situational awareness, and the Joint Directors of Laboratories (JDL) data fusion process model can be implemented through a novel combination of Complex Event Processing (CEP) and Multi-Agent Software (MAS). Though originally designed for stock market and financial applications, the high performance data-driven nature of CEP techniques provide a natural compliment to the proven capabilities of MAS systems for modeling naturalistic decision-making, performing process adjudication, and optimizing networked processing and cognition via the use of "mobile agents." This paper addresses the challenges and opportunities of such a framework for augmenting human observational capability as well as enabling the ability to perform collaborative context-aware reasoning in both human teams and hybrid human / software agent teams.
TMS affects moral judgment, showing the role of DLPFC and TPJ in cognitive and emotional processing.
Jeurissen, Danique; Sack, Alexander T; Roebroeck, Alard; Russ, Brian E; Pascual-Leone, Alvaro
2014-01-01
Decision-making involves a complex interplay of emotional responses and reasoning processes. In this study, we use TMS to explore the neurobiological substrates of moral decisions in humans. To examining the effects of TMS on the outcome of a moral-decision, we compare the decision outcome of moral-personal and moral-impersonal dilemmas to each other and examine the differential effects of applying TMS over the right DLPFC or right TPJ. In this comparison, we find that the TMS-induced disruption of the DLPFC during the decision process, affects the outcome of the moral-personal judgment, while TMS-induced disruption of TPJ affects only moral-impersonal conditions. In other words, we find a double-dissociation between DLPFC and TPJ in the outcome of a moral decision. Furthermore, we find that TMS-induced disruption of the DLPFC during non-moral, moral-impersonal, and moral-personal decisions lead to lower ratings of regret about the decision. Our results are in line with the dual-process theory and suggest a role for both the emotional response and cognitive reasoning process in moral judgment. Both the emotional and cognitive processes were shown to be involved in the decision outcome.
Cognitive continuum theory in interprofessional healthcare: A critical analysis.
Parker-Tomlin, Michelle; Boschen, Mark; Morrissey, Shirley; Glendon, Ian
2017-07-01
Effective clinical decision making is among the most important skills required by healthcare practitioners. Making sound decisions while working collaboratively in interprofessional healthcare teams is essential for modern healthcare planning, successful interventions, and patient care. The cognitive continuum theory (CCT) is a model of human judgement and decision making aimed at orienting decision-making processes. CCT has the potential to improve both individual health practitioner, and interprofessional team understanding about, and communication of, clinical decision-making processes. Examination of the current application of CCT indicates that this theory could strengthen interprofessional team clinical decision making (CDM). However, further research is needed before extending the use of this theoretical framework to a wider range of interprofessional healthcare team processes. Implications for research, education, practice, and policy are addressed.
A conceptual and computational model of moral decision making in human and artificial agents.
Wallach, Wendell; Franklin, Stan; Allen, Colin
2010-07-01
Recently, there has been a resurgence of interest in general, comprehensive models of human cognition. Such models aim to explain higher-order cognitive faculties, such as deliberation and planning. Given a computational representation, the validity of these models can be tested in computer simulations such as software agents or embodied robots. The push to implement computational models of this kind has created the field of artificial general intelligence (AGI). Moral decision making is arguably one of the most challenging tasks for computational approaches to higher-order cognition. The need for increasingly autonomous artificial agents to factor moral considerations into their choices and actions has given rise to another new field of inquiry variously known as Machine Morality, Machine Ethics, Roboethics, or Friendly AI. In this study, we discuss how LIDA, an AGI model of human cognition, can be adapted to model both affective and rational features of moral decision making. Using the LIDA model, we will demonstrate how moral decisions can be made in many domains using the same mechanisms that enable general decision making. Comprehensive models of human cognition typically aim for compatibility with recent research in the cognitive and neural sciences. Global workspace theory, proposed by the neuropsychologist Bernard Baars (1988), is a highly regarded model of human cognition that is currently being computationally instantiated in several software implementations. LIDA (Franklin, Baars, Ramamurthy, & Ventura, 2005) is one such computational implementation. LIDA is both a set of computational tools and an underlying model of human cognition, which provides mechanisms that are capable of explaining how an agent's selection of its next action arises from bottom-up collection of sensory data and top-down processes for making sense of its current situation. We will describe how the LIDA model helps integrate emotions into the human decision-making process, and we will elucidate a process whereby an agent can work through an ethical problem to reach a solution that takes account of ethically relevant factors. Copyright © 2010 Cognitive Science Society, Inc.
Expert Systems: A Conceptual Analysis and Prospects for Their Library Applications.
ERIC Educational Resources Information Center
Dubey, Yogendra P.
This paper begins with a discussion of the decision-making process. The application of operations research technologies to managerial decision-making is noted, and the development of management information systems in organizations and some limitations of these systems are discussed. An overview of the Human Information Processing System (HIPS)…
Making decisions to increase community or regional sustainability requires a comprehensive understanding of the linkages between environmental, social, and economic systems. We present a visualization tool that can improve decision processes and improve interdisciplinary research...
Mitchell, Michael S.; Cooley, Hilary; Gude, Justin A.; Kolbe, Jay; Nowak, J. Joshua; Proffitt, Kelly M.; Sells, Sarah N.; Thompson, Mike
2018-01-01
The relative roles of science and human values can be difficult to distinguish when informal processes are used to make complex and contentious decisions in wildlife management. Structured Decision Making (SDM) offers a formal process for making such decisions, where scientific results and concepts can be disentangled from the values of differing stakeholders. We used SDM to formally integrate science and human values for a citizen working group of ungulate hunting advocates, lion hunting advocates, and outfitters convened to address the contentious allocation of harvest quotas for mountain lions (Puma concolor) in west‐central Montana, USA, during 2014. A science team consisting of mountain lion biologists and population ecologists convened to support the working group. The science team used integrated population models that incorporated 4 estimates of mountain lion density to estimate population trajectories for 5 alternative harvest quotas developed by the working group. Results of the modeling predicted that effects of each harvest quota were consistent across the 4 density estimates; harvest quotas affected predicted population trajectories for 5 years after implementation but differences were not strong. Based on these results, the focus of the working group changed to differences in values among stakeholders that were the true impediment to allocating harvest quotas. By distinguishing roles of science and human values in this process, the working group was able to collaboratively recommend a compromise solution. This solution differed little from the status quo that had been the focus of debate, but the SDM process produced understanding and buy‐in among stakeholders involved, reducing disagreements, misunderstanding, and unproductive arguments founded on informal application of scientific data and concepts. Whereas investments involved in conducting SDM may be unnecessary for many decisions in wildlife management, the investment may be beneficial for complex, contentious, and multiobjective decisions that integrate science and human values.
The Contribution of Cognitive Engineering to the Effective Design and Use of Information Systems.
ERIC Educational Resources Information Center
Garg-Janardan, Chaya; Salvendy, Gavriel
1986-01-01
Examines the role of human information processing and decision-making capabilities and limitations in the design of effective human-computer interfaces. Several cognitive engineering principles that should guide the design process are outlined. (48 references) (Author/CLB)
2010-01-01
Background Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. Discussion We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. Summary In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the EBDM/EBPM process can be improved. PMID:20504357
McCaughey, Deirdre; Bruning, Nealia S
2010-05-26
Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the EBDM/EBPM process can be improved.
[Decision Making and Electrodermal Activity].
Kobayakawa, Mutsutaka
2016-08-01
Decision making is aided by emotions. Bodily responses, such as sweating, heartbeat, and visceral sensation, are used to monitor the emotional state during decision making. Because decision making in dairy life is complicated and cognitively demanding, these bodily signals are thought to facilitate the decision making process by assigning positive or negative values for each of the behavioral options. The sweat response in a decision making task is measured by skin conductance response (SCR). SCR in decision making is divided into two categories: anticipatory SCR is observed before making decisions, and reward/punishment SCR is observed after the outcome of the decision is perceived. Brain lesion studies in human revealed that the amygdala and ventromedial prefrontal cortex are important in decision making. Patients with lesinon in the amygdala exhibit neither the anticipatory nor reward/punishment SCRs, while patients with the ventromedial prefrontal lesions have deficits only in the anticipatory SCRs. Decision making tasks and SCR analysis have contributed to reveal the implicit aspects of decision making. Further research is necessary for clarifying the role of explicit process of decision making and its relationship with the implicit process.
Van Wensem, Joke; Calow, Peter; Dollacker, Annik; Maltby, Lorraine; Olander, Lydia; Tuvendal, Magnus; Van Houtven, George
2017-01-01
The presumption is that ecosystem services (ES) approaches provide a better basis for environmental decision making than do other approaches because they make explicit the connection between human well-being and ecosystem structures and processes. However, the existing literature does not provide a precise description of ES approaches for environmental policy and decision making, nor does it assess whether these applications will make a difference in terms of changing decisions and improving outcomes. We describe 3 criteria that can be used to identify whether and to what extent ES approaches are being applied: 1) connect impacts all the way from ecosystem changes to human well-being, 2) consider all relevant ES affected by the decision, and 3) consider and compare the changes in well-being of different stakeholders. As a demonstration, we then analyze retrospectively whether and how the criteria were met in different decision-making contexts. For this assessment, we have developed an analysis format that describes the type of policy, the relevant scales, the decisions or questions, the decision maker, and the underlying documents. This format includes a general judgment of how far the 3 ES criteria have been applied. It shows that the criteria can be applied to many different decision-making processes, ranging from the supranational to the local scale and to different parts of decision-making processes. In conclusion we suggest these criteria could be used for assessments of the extent to which ES approaches have been and should be applied, what benefits and challenges arise, and whether using ES approaches made a difference in the decision-making process, decisions made, or outcomes of those decisions. Results from such studies could inform future use and development of ES approaches, draw attention to where the greatest benefits and challenges are, and help to target integration of ES approaches into policies, where they can be most effective. Integr Environ Assess Manag 2017;13:41-51. © 2016 SETAC. © 2016 SETAC.
Human-like machines: Transparency and comprehensibility.
Patrzyk, Piotr M; Link, Daniela; Marewski, Julian N
2017-01-01
Artificial intelligence algorithms seek inspiration from human cognitive systems in areas where humans outperform machines. But on what level should algorithms try to approximate human cognition? We argue that human-like machines should be designed to make decisions in transparent and comprehensible ways, which can be achieved by accurately mirroring human cognitive processes.
Selective attention increases choice certainty in human decision making.
Zizlsperger, Leopold; Sauvigny, Thomas; Haarmeier, Thomas
2012-01-01
Choice certainty is a probabilistic estimate of past performance and expected outcome. In perceptual decisions the degree of confidence correlates closely with choice accuracy and reaction times, suggesting an intimate relationship to objective performance. Here we show that spatial and feature-based attention increase human subjects' certainty more than accuracy in visual motion discrimination tasks. Our findings demonstrate for the first time a dissociation of choice accuracy and certainty with a significantly stronger influence of voluntary top-down attention on subjective performance measures than on objective performance. These results reveal a so far unknown mechanism of the selection process implemented by attention and suggest a unique biological valence of choice certainty beyond a faithful reflection of the decision process.
The importance of imagination (or lack thereof) in artificial, human and quantum decision making.
Gustafson, Karl
2016-01-13
Enlarging upon experiments and analysis that I did jointly some years ago, in which artificial (symbolic, neural-net and pattern) learning and generalization were compared with that of humans, I will emphasize the role of imagination (or lack thereof) in artificial, human and quantum cognition and decision-making processes. Then I will look in more detail at some of the 'engineering details' of its implementation (or lack thereof) in each of these settings. In other words, the question posed is: What is actually happening? For example, we previously found that humans overwhelmingly seek, create or imagine context in order to provide meaning when presented with abstract, apparently incomplete, contradictory or otherwise untenable decision-making situations. Humans are intolerant of contradiction and will greatly simplify to avoid it. They can partially correlate but do not average. Human learning is not Boolean. These and other human reasoning properties will then be taken to critique how well artificial intelligence methods and quantum mechanical modelling might compete with them in decision-making tasks within psychology and economics. © 2015 The Author(s).
Sütfeld, Leon R; Gast, Richard; König, Peter; Pipa, Gordon
2017-01-01
Self-driving cars are posing a new challenge to our ethics. By using algorithms to make decisions in situations where harming humans is possible, probable, or even unavoidable, a self-driving car's ethical behavior comes pre-defined. Ad hoc decisions are made in milliseconds, but can be based on extensive research and debates. The same algorithms are also likely to be used in millions of cars at a time, increasing the impact of any inherent biases, and increasing the importance of getting it right. Previous research has shown that moral judgment and behavior are highly context-dependent, and comprehensive and nuanced models of the underlying cognitive processes are out of reach to date. Models of ethics for self-driving cars should thus aim to match human decisions made in the same context. We employed immersive virtual reality to assess ethical behavior in simulated road traffic scenarios, and used the collected data to train and evaluate a range of decision models. In the study, participants controlled a virtual car and had to choose which of two given obstacles they would sacrifice in order to spare the other. We randomly sampled obstacles from a variety of inanimate objects, animals and humans. Our model comparison shows that simple models based on one-dimensional value-of-life scales are suited to describe human ethical behavior in these situations. Furthermore, we examined the influence of severe time pressure on the decision-making process. We found that it decreases consistency in the decision patterns, thus providing an argument for algorithmic decision-making in road traffic. This study demonstrates the suitability of virtual reality for the assessment of ethical behavior in humans, delivering consistent results across subjects, while closely matching the experimental settings to the real world scenarios in question.
Sütfeld, Leon R.; Gast, Richard; König, Peter; Pipa, Gordon
2017-01-01
Self-driving cars are posing a new challenge to our ethics. By using algorithms to make decisions in situations where harming humans is possible, probable, or even unavoidable, a self-driving car's ethical behavior comes pre-defined. Ad hoc decisions are made in milliseconds, but can be based on extensive research and debates. The same algorithms are also likely to be used in millions of cars at a time, increasing the impact of any inherent biases, and increasing the importance of getting it right. Previous research has shown that moral judgment and behavior are highly context-dependent, and comprehensive and nuanced models of the underlying cognitive processes are out of reach to date. Models of ethics for self-driving cars should thus aim to match human decisions made in the same context. We employed immersive virtual reality to assess ethical behavior in simulated road traffic scenarios, and used the collected data to train and evaluate a range of decision models. In the study, participants controlled a virtual car and had to choose which of two given obstacles they would sacrifice in order to spare the other. We randomly sampled obstacles from a variety of inanimate objects, animals and humans. Our model comparison shows that simple models based on one-dimensional value-of-life scales are suited to describe human ethical behavior in these situations. Furthermore, we examined the influence of severe time pressure on the decision-making process. We found that it decreases consistency in the decision patterns, thus providing an argument for algorithmic decision-making in road traffic. This study demonstrates the suitability of virtual reality for the assessment of ethical behavior in humans, delivering consistent results across subjects, while closely matching the experimental settings to the real world scenarios in question. PMID:28725188
Function allocation for humans and automation in the context of team dynamics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jeffrey C. Joe; John O'Hara; Jacques Hugo
Within Human Factors Engineering, a decision-making process called function allocation (FA) is used during the design life cycle of complex systems to distribute the system functions, often identified through a functional requirements analysis, to all human and automated machine agents (or teammates) involved in controlling the system. Most FA methods make allocation decisions primarily by comparing the capabilities of humans and automation, but then also by considering secondary factors such as cost, regulations, and the health and safety of workers. The primary analysis of the strengths and weaknesses of humans and machines, however, is almost always considered in terms ofmore » individual human or machine capabilities. Yet, FA is fundamentally about teamwork in that the goal of the FA decision-making process is to determine what are the optimal allocations of functions among agents. Given this framing of FA, and the increasing use of and sophistication of automation, there are two related social psychological issues that current FA methods need to address more thoroughly. First, many principles for effective human teamwork are not considered as central decision points or in the iterative hypothesis and testing phase in most FA methods, when it is clear that social factors have numerous positive and negative effects on individual and team capabilities. Second, social psychological factors affecting team performance and can be difficult to translate to automated agents, and most FA methods currently do not account for this effect. The implications for these issues are discussed.« less
Blank, Helen; Biele, Guido; Heekeren, Hauke R; Philiastides, Marios G
2013-02-27
Perceptual decision making is the process by which information from sensory systems is combined and used to influence our behavior. In addition to the sensory input, this process can be affected by other factors, such as reward and punishment for correct and incorrect responses. To investigate the temporal dynamics of how monetary punishment influences perceptual decision making in humans, we collected electroencephalography (EEG) data during a perceptual categorization task whereby the punishment level for incorrect responses was parametrically manipulated across blocks of trials. Behaviorally, we observed improved accuracy for high relative to low punishment levels. Using multivariate linear discriminant analysis of the EEG, we identified multiple punishment-induced discriminating components with spatially distinct scalp topographies. Compared with components related to sensory evidence, components discriminating punishment levels appeared later in the trial, suggesting that punishment affects primarily late postsensory, decision-related processing. Crucially, the amplitude of these punishment components across participants was predictive of the size of the behavioral improvements induced by punishment. Finally, trial-by-trial changes in prestimulus oscillatory activity in the alpha and gamma bands were good predictors of the amplitude of these components. We discuss these findings in the context of increased motivation/attention, resulting from increases in punishment, which in turn yields improved decision-related processing.
The Role of Intuition and Deliberative Thinking in Experts' Superior Tactical Decision-Making
ERIC Educational Resources Information Center
Moxley, Jerad H.; Ericsson, K. Anders; Charness, Neil; Krampe, Ralf T.
2012-01-01
Current theories argue that human decision making is largely based on quick, automatic, and intuitive processes that are occasionally supplemented by slow controlled deliberation. Researchers, therefore, predominantly studied the heuristics of the automatic system in everyday decision making. Our study examines the role of slow deliberation for…
Predicting Sentencing for Low-Level Crimes: Comparing Models of Human Judgment
ERIC Educational Resources Information Center
von Helversen, Bettina; Rieskamp, Jorg
2009-01-01
Laws and guidelines regulating legal decision making are often imposed without taking the cognitive processes of the legal decision maker into account. In the case of sentencing, this raises the question of whether the sentencing decisions of prosecutors and judges are consistent with legal policy. Especially in handling low-level crimes, legal…
Perceptual Decision Making in Rodents, Monkeys, and Humans.
Hanks, Timothy D; Summerfield, Christopher
2017-01-04
Perceptual decision making is the process by which animals detect, discriminate, and categorize information from the senses. Over the past two decades, understanding how perceptual decisions are made has become a central theme in the neurosciences. Exceptional progress has been made by recording from single neurons in the cortex of the macaque monkey and using computational models from mathematical psychology to relate these neural data to behavior. More recently, however, the range of available techniques and paradigms has dramatically broadened, and researchers have begun to harness new approaches to explore how rodents and humans make perceptual decisions. The results have illustrated some striking convergences with findings from the monkey, but also raised new questions and provided new theoretical insights. In this review, we summarize key findings, and highlight open challenges, for understanding perceptual decision making in rodents, monkeys, and humans. Copyright © 2017 Elsevier Inc. All rights reserved.
Regret and Responsibility: A Reply to Zeelenberg et al. (1998).
Ordóñez; Connolly
2000-01-01
M. Zeelenberg, W. W. van Dijk, and A. S. R. Manstead (1998, Organizational Behavior and Human Decision Processes, 74, 254-272) recently reported an altered replication of our earlier study (T. Connolly, L. D. Ordóñez, & R. Coughlan, 1997, Organizational Behavior and Human Decision Processes, 70, 73-85) concerning the effects of decision agency on regret and outcome evaluation. Our earlier study had found no such effect, but Zeelenberg et al. did. In two new experiments, we have largely confirmed Zeelenberg et al.'s result but have shown that, contrary to most theory, regret (a) can appear even in the absence of decision agency, (b) can be unrelated to outcome evaluations, and (c) may be more influenced by the experience of gains or losses from the status quo than by any decisional responsibility for those changes. Copyright 2000 Academic Press.
Eaton, Mitchell J.; Martin, Julien; Nichols, James D.; McIntyre, Carol; McCluskie, Maggie C.; Schmutz, Joel A.; Lubow, Bruce L.; Runge, Michael C.; Edited by Guntenspergen, Glenn R.
2014-01-01
In this chapter, we demonstrate the application of the various classes of thresholds, detailed in earlier chapters and elsewhere, via an actual but simplified natural resource management case study. We intend our example to provide the reader with the ability to recognize and apply the theoretical concepts of utility, ecological and decision thresholds to management problems through a formalized decision-analytic process. Our case study concerns the management of human recreational activities in Alaska’s Denali National Park, USA, and the possible impacts of such activities on nesting Golden Eagles, Aquila chrysaetos. Managers desire to allow visitors the greatest amount of access to park lands, provided that eagle nesting-site occupancy is maintained at a level determined to be acceptable by the managers themselves. As these two management objectives are potentially at odds, we treat minimum desired occupancy level as a utility threshold which, then, serves to guide the selection of annual management alternatives in the decision process. As human disturbance is not the only factor influencing eagle occupancy, we model nesting-site dynamics as a function of both disturbance and prey availability. We incorporate uncertainty in these dynamics by considering several hypotheses, including a hypothesis that site occupancy is affected only at a threshold level of prey abundance (i.e., an ecological threshold effect). By considering competing management objectives and accounting for two forms of thresholds in the decision process, we are able to determine the optimal number of annual nesting-site restrictions that will produce the greatest long-term benefits for both eagles and humans. Setting a utility threshold of 75 occupied sites, out of a total of 90 potential nesting sites, the optimization specified a decision threshold at approximately 80 occupied sites. At the point that current occupancy falls below 80 sites, the recommended decision is to begin restricting access to humans; above this level, it is recommended that all eagle territories be opened to human recreation. We evaluated the sensitivity of the decision threshold to uncertainty in system dynamics and to management objectives (i.e., to the utility threshold).
ERIC Educational Resources Information Center
Cathcart, Stephen Michael
2016-01-01
This mixed method study examines HRD professionals' decision-making processes when making an organizational purchase of training. The study uses a case approach with a degrees of freedom analysis. The data to analyze will examine how HRD professionals in manufacturing select outside vendors human resource development programs for training,…
The Role of Intuition in Risk/Benefit Decision-Making in Human Subjects Research
Resnik, David B.
2016-01-01
One of the key principles of ethical research involving human subjects is that the risks of research to should be acceptable in relation to expected benefits. Institutional review board (IRB) members often rely on intuition to make risk/benefit decisions concerning proposed human studies. Some have objected to using intuition to make these decisions because intuition is unreliable and biased and lacks transparency. In this paper, I examine the role of intuition in IRB risk/benefit decision-making and argue that there are practical and philosophical limits to our ability to reduce our reliance on intuition in this process. The fact that IRB risk/benefit decision-making involves intuition need not imply that it is hopelessly subjective or biased, however, since there are strategies that IRBs can employ to improve their decisions, such as using empirical data to estimate the probability of potential harms and benefits, developing classification systems to guide the evaluation of harms and benefits, and engaging in moral reasoning concerning the acceptability of risks. PMID:27294429
The Role of Intuition in Risk/Benefit Decision-Making in Human Subjects Research.
Resnik, David B
2017-01-01
One of the key principles of ethical research involving human subjects is that the risks of research to should be acceptable in relation to expected benefits. Institutional review board (IRB) members often rely on intuition to make risk/benefit decisions concerning proposed human studies. Some have objected to using intuition to make these decisions because intuition is unreliable and biased and lacks transparency. In this article, I examine the role of intuition in IRB risk/benefit decision-making and argue that there are practical and philosophical limits to our ability to reduce our reliance on intuition in this process. The fact that IRB risk/benefit decision-making involves intuition need not imply that it is hopelessly subjective or biased, however, since there are strategies that IRBs can employ to improve their decisions, such as using empirical data to estimate the probability of potential harms and benefits, developing classification systems to guide the evaluation of harms and benefits, and engaging in moral reasoning concerning the acceptability of risks.
Evidence Accumulation and Choice Maintenance Are Dissociated in Human Perceptual Decision Making
Pedersen, Mads Lund; Endestad, Tor; Biele, Guido
2015-01-01
Perceptual decision making in monkeys relies on decision neurons, which accumulate evidence and maintain choices until a response is given. In humans, several brain regions have been proposed to accumulate evidence, but it is unknown if these regions also maintain choices. To test if accumulator regions in humans also maintain decisions we compared delayed and self-paced responses during a face/house discrimination decision making task. Computational modeling and fMRI results revealed dissociated processes of evidence accumulation and decision maintenance, with potential accumulator activations found in the dorsomedial prefrontal cortex, right inferior frontal gyrus and bilateral insula. Potential maintenance activation spanned the frontal pole, temporal gyri, precuneus and the lateral occipital and frontal orbital cortices. Results of a quantitative reverse inference meta-analysis performed to differentiate the functions associated with the identified regions did not narrow down potential accumulation regions, but suggested that response-maintenance might rely on a verbalization of the response. PMID:26510176
NASA Astrophysics Data System (ADS)
Gorman, J.; Voshell, M.; Sliva, A.
2016-09-01
The United States is highly dependent on space resources to support military, government, commercial, and research activities. Satellites operate at great distances, observation capacity is limited, and operator actions and observations can be significantly delayed. Safe operations require support systems that provide situational understanding, enhance decision making, and facilitate collaboration between human operators and system automation both in-the-loop, and on-the-loop. Joint cognitive systems engineering (JCSE) provides a rich set of methods for analyzing and informing the design of complex systems that include both human decision-makers and autonomous elements as coordinating teammates. While, JCSE-based systems can enhance a system analysts' understanding of both existing and new system processes, JCSE activities typically occur outside of traditional systems engineering (SE) methods, providing sparse guidance about how systems should be implemented. In contrast, the Joint Director's Laboratory (JDL) information fusion model and extensions, such as the Dual Node Network (DNN) technical architecture, provide the means to divide and conquer such engineering and implementation complexity, but are loosely coupled to specialized organizational contexts and needs. We previously describe how Dual Node Decision Wheels (DNDW) extend the DNN to integrate JCSE analysis and design with the practicalities of system engineering and implementation using the DNN. Insights from Rasmussen's JCSE Decision Ladders align system implementation with organizational structures and processes. In the current work, we present a novel approach to assessing system performance based on patterns occurring in operational decisions that are documented by JCSE processes as traces in a decision ladder. In this way, system assessment is closely tied not just to system design, but the design of the joint cognitive system that includes human operators, decision-makers, information systems, and automated processes. Such operationally relevant and integrated testing provides a sound foundation for operator trust in system automation that is required to safely operate satellite systems.
White, Eoin J; McMahon, Muireann; Walsh, Michael T; Coffey, J Calvin; O Sullivan, Leonard
To create a human information-processing model for laparoscopic surgery based on already established literature and primary research to enhance laparoscopic surgical education in this context. We reviewed the literature for information-processing models most relevant to laparoscopic surgery. Our review highlighted the necessity for a model that accounts for dynamic environments, perception, allocation of attention resources between the actions of both hands of an operator, and skill acquisition and retention. The results of the literature review were augmented through intraoperative observations of 7 colorectal surgical procedures, supported by laparoscopic video analysis of 12 colorectal procedures. The Wickens human information-processing model was selected as the most relevant theoretical model to which we make adaptions for this specific application. We expanded the perception subsystem of the model to involve all aspects of perception during laparoscopic surgery. We extended the decision-making system to include dynamic decision-making to account for case/patient-specific and surgeon-specific deviations. The response subsystem now includes dual-task performance and nontechnical skills, such as intraoperative communication. The memory subsystem is expanded to include skill acquisition and retention. Surgical decision-making during laparoscopic surgery is the result of a highly complex series of processes influenced not only by the operator's knowledge, but also patient anatomy and interaction with the surgical team. Newer developments in simulation-based education must focus on the theoretically supported elements and events that underpin skill acquisition and affect the cognitive abilities of novice surgeons. The proposed human information-processing model builds on established literature regarding information processing, accounting for a dynamic environment of laparoscopic surgery. This revised model may be used as a foundation for a model describing robotic surgery. Copyright © 2017 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.
Do humans make good decisions?
Summerfield, Christopher; Tsetsos, Konstantinos
2014-01-01
Human performance on perceptual classification tasks approaches that of an ideal observer, but economic decisions are often inconsistent and intransitive, with preferences reversing according to the local context. We discuss the view that suboptimal choices may result from the efficient coding of decision-relevant information, a strategy that allows expected inputs to be processed with higher gain than unexpected inputs. Efficient coding leads to ‘robust’ decisions that depart from optimality but maximise the information transmitted by a limited-capacity system in a rapidly-changing world. We review recent work showing that when perceptual environments are variable or volatile, perceptual decisions exhibit the same suboptimal context-dependence as economic choices, and propose a general computational framework that accounts for findings across the two domains. PMID:25488076
ERIC Educational Resources Information Center
Dunn, Patricia C.; Marple, Jennifer; Knight, Sharon M.
2000-01-01
Explains the responsibilities of the United Network for Organ Sharing (UNOS) and its decision making process as to who receives an organ for transplant. Presents an activity exploring ethics, human values, and human anatomy. (YDS)
Quantum decision-maker theory and simulation
NASA Astrophysics Data System (ADS)
Zak, Michail; Meyers, Ronald E.; Deacon, Keith S.
2000-07-01
A quantum device simulating the human decision making process is introduced. It consists of quantum recurrent nets generating stochastic processes which represent the motor dynamics, and of classical neural nets describing the evolution of probabilities of these processes which represent the mental dynamics. The autonomy of the decision making process is achieved by a feedback from the mental to motor dynamics which changes the stochastic matrix based upon the probability distribution. This feedback replaces unavailable external information by an internal knowledge- base stored in the mental model in the form of probability distributions. As a result, the coupled motor-mental dynamics is described by a nonlinear version of Markov chains which can decrease entropy without an external source of information. Applications to common sense based decisions as well as to evolutionary games are discussed. An example exhibiting self-organization is computed using quantum computer simulation. Force on force and mutual aircraft engagements using the quantum decision maker dynamics are considered.
Sinclair, Shane; Hagen, Neil A; Chambers, Carole; Manns, Braden; Simon, Anita; Browman, George P
2008-05-01
Drug decision-makers are involved in developing and implementing policy, procedure and processes to support health resource allocation regarding drug treatment formularies. A variety of approaches to decision-making, including formal decision-making frameworks, have been developed to support transparent and fair priority setting. Recently, a decision tool, 'The 6-STEPPPs Tool', was developed to assist in making decisions about new cancer drugs within the public health care system. We conducted a qualitative study, utilizing focus groups and participant observation, in order to investigate the internal frameworks that supported and challenged individual participants as they applied this decision tool within a multi-stakeholder decision process. We discovered that health care resource allocation engaged not only the minds of decision-makers but profoundly called on the often conflicting values of the heart. Objective decision-making frameworks for new drug therapies need to consider the subjective internal frameworks of decision-makers that affect decisions. Understanding the very human, internal turmoil experienced by individuals involved in health care resource allocation, sheds additional insight into how to account for reasonableness and how to better support difficult decisions through transparent, values-based resource allocation policy, procedures and processes.
Warfighter decision making performance analysis as an investment priority driver
NASA Astrophysics Data System (ADS)
Thornley, David J.; Dean, David F.; Kirk, James C.
2010-04-01
Estimating the relative value of alternative tactics, techniques and procedures (TTP) and information systems requires measures of the costs and benefits of each, and methods for combining and comparing those measures. The NATO Code of Best Practice for Command and Control Assessment explains that decision making quality would ideally be best assessed on outcomes. Lessons learned in practice can be assessed statistically to support this, but experimentation with alternate measures in live conflict is undesirable. To this end, the development of practical experimentation to parameterize effective constructive simulation and analytic modelling for system utility prediction is desirable. The Land Battlespace Systems Department of Dstl has modeled human development of situational awareness to support constructive simulation by empirically discovering how evidence is weighed according to circumstance, personality, training and briefing. The human decision maker (DM) provides the backbone of the information processing activity associated with military engagements because of inherent uncertainty associated with combat operations. To develop methods for representing the process in order to assess equipment and non-technological interventions such as training and TTPs we are developing componentized or modularized timed analytic stochastic model components and instruments as part of a framework to support quantitative assessment of intelligence production and consumption methods in a human decision maker-centric mission space. In this paper, we formulate an abstraction of the human intelligence fusion process from the Defence Science and Technology Laboratory's (Dstl's) INCIDER model to include in our framework, and synthesize relevant cost and benefit characteristics.
Bounded Rationality, Emotions and Older Adult Decision Making: Not so Fast and yet so Frugal
ERIC Educational Resources Information Center
Hanoch, Yaniv; Wood, Stacey; Rice, Thomas
2007-01-01
Herbert Simon's work on bounded rationality has had little impact on researchers studying older adults' decision making. This omission is surprising, as human constraints on computation and memory are exacerbated in older adults. The study of older adults' decision-making processes could benefit from employing a bounded rationality perspective,…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stern, Marc J., E-mail: mjstern@vt.ed; Predmore, S. Andrew, E-mail: sapredmo@vt.ed
2011-04-15
The National Environmental Policy Act (NEPA) dictates a process of analyzing and disclosing the likely impacts of proposed agency actions on the human environment. This study addresses two key questions related to NEPA implementation in the U.S. Forest Service: 1) how do Interdisciplinary (ID) team leaders and decision makers conceptualize the outcomes of NEPA processes? And 2), how does NEPA relate to agency decision making? We address these questions through two separate online surveys that posed questions about recently completed NEPA processes - the first with the ID team leaders tasked with carrying out the processes, and the second withmore » the line officers responsible for making the processes' final decisions. Outcomes of NEPA processes include impacts on public relations, on employee morale and team functioning, on the achievement of agency goals, and on the achievement of NEPA's procedural requirements (disclosure) and substantive intent (minimizing negative environmental impacts). Although both tended to view public relations outcomes as important, decision makers' perceptions of favorable outcomes were more closely linked to the achievement of agency goals and process efficiency than was the case for ID team leaders. While ID team leaders' responses suggest that they see decision making closely integrated with the NEPA process, decision makers more commonly decoupled decision making from the NEPA process. These findings suggest a philosophical difference between ID team leaders and decision makers that may pose challenges for both the implementation and the evaluation of agency NEPA. We discuss the pros and cons of integrating NEPA with decision making or separating the two. We conclude that detaching NEPA from decision making poses greater risks than integrating them.« less
2005-06-01
cognitive task analysis , organizational information dissemination and interaction, systems engineering, collaboration and communications processes, decision-making processes, and data collection and organization. By blending these diverse disciplines command centers can be designed to support decision-making, cognitive analysis, information technology, and the human factors engineering aspects of Command and Control (C2). This model can then be used as a baseline when dealing with work in areas of business processes, workflow engineering, information management,
Dynamic Decision Making in Complex Task Environments: Principles and Neural Mechanisms
2013-03-01
Dynamical models of cognition . Mathematical models of mental processes. Human performance optimization. U U U U Dr. Jay Myung 703-696-8487 Reset 1...we have continued to develop a neurodynamic theory of decision making, using a combination of computational and experimental approaches, to address...a long history in the field of human cognitive psychology. The theoretical foundations of this research can be traced back to signal detection
Understanding the Science behind EPA’s Pesticide Decisions
Science is key to EPA’s decision-making. EPA scientists review these data to determine whether to register a pesticide product or use and any need for specific restrictions. EPA maintains a transparent, public process in assessing potential human health ri
7 CFR 1940.303 - General policy.
Code of Federal Regulations, 2010 CFR
2010-01-01
... other relevant factors in program development and decision-making processes. (b) In assessing the... SERVICE, RURAL UTILITIES SERVICE, AND FARM SERVICE AGENCY, DEPARTMENT OF AGRICULTURE (CONTINUED) PROGRAM... decision-makers with both the technical and human aspects of environmental planning. (c) When adverse...
Optimal policy for value-based decision-making.
Tajima, Satohiro; Drugowitsch, Jan; Pouget, Alexandre
2016-08-18
For decades now, normative theories of perceptual decisions, and their implementation as drift diffusion models, have driven and significantly improved our understanding of human and animal behaviour and the underlying neural processes. While similar processes seem to govern value-based decisions, we still lack the theoretical understanding of why this ought to be the case. Here, we show that, similar to perceptual decisions, drift diffusion models implement the optimal strategy for value-based decisions. Such optimal decisions require the models' decision boundaries to collapse over time, and to depend on the a priori knowledge about reward contingencies. Diffusion models only implement the optimal strategy under specific task assumptions, and cease to be optimal once we start relaxing these assumptions, by, for example, using non-linear utility functions. Our findings thus provide the much-needed theory for value-based decisions, explain the apparent similarity to perceptual decisions, and predict conditions under which this similarity should break down.
Optimal policy for value-based decision-making
Tajima, Satohiro; Drugowitsch, Jan; Pouget, Alexandre
2016-01-01
For decades now, normative theories of perceptual decisions, and their implementation as drift diffusion models, have driven and significantly improved our understanding of human and animal behaviour and the underlying neural processes. While similar processes seem to govern value-based decisions, we still lack the theoretical understanding of why this ought to be the case. Here, we show that, similar to perceptual decisions, drift diffusion models implement the optimal strategy for value-based decisions. Such optimal decisions require the models' decision boundaries to collapse over time, and to depend on the a priori knowledge about reward contingencies. Diffusion models only implement the optimal strategy under specific task assumptions, and cease to be optimal once we start relaxing these assumptions, by, for example, using non-linear utility functions. Our findings thus provide the much-needed theory for value-based decisions, explain the apparent similarity to perceptual decisions, and predict conditions under which this similarity should break down. PMID:27535638
Use of Inverse Reinforcement Learning for Identity Prediction
NASA Technical Reports Server (NTRS)
Hayes, Roy; Bao, Jonathan; Beling, Peter; Horowitz, Barry
2011-01-01
We adopt Markov Decision Processes (MDP) to model sequential decision problems, which have the characteristic that the current decision made by a human decision maker has an uncertain impact on future opportunity. We hypothesize that the individuality of decision makers can be modeled as differences in the reward function under a common MDP model. A machine learning technique, Inverse Reinforcement Learning (IRL), was used to learn an individual's reward function based on limited observation of his or her decision choices. This work serves as an initial investigation for using IRL to analyze decision making, conducted through a human experiment in a cyber shopping environment. Specifically, the ability to determine the demographic identity of users is conducted through prediction analysis and supervised learning. The results show that IRL can be used to correctly identify participants, at a rate of 68% for gender and 66% for one of three college major categories.
Basnyat, Iccha; Lim, Cheryl
2017-07-06
Human papillomavirus (HPV) vaccination uptake in Singapore is low among young women. Low uptake has been found to be linked to low awareness. Thus, this study aimed to understand active and passive vaccine information-seeking behavior. Furthermore, guided by the Elaboration Likelihood Model (ELM), this study examined young women's (aged 21-26 years) processing of information they acquired in their decision to get vaccinated. ELM postulates that information processing could be through the central (i.e., logic-based) or peripheral (i.e., heuristic-based) route. Twenty-six in-depth interviews were conducted from January to March 2016. Data were analyzed using thematic analysis. Two meta-themes-information acquisition and vaccination decision-revealed the heuristic-based information processing was employed. These young women acquired information passively within their social network and actively in healthcare settings. However, they used heuristic cues, such as closeness and trust, to process the information. Similarly, vaccination decisions revealed that women relied on heuristic cues, such as sense of belonging and validation among peers and source credibility and likability in medical settings, in their decision to get vaccinated. The findings of this study highlight that intervention efforts should focus on strengthening social support among personal networks to increase the uptake of the vaccine.
Decision making in a human population living sustainably.
Hicks, John S; Burgman, Mark A; Marewski, Julian N; Fidler, Fiona; Gigerenzer, Gerd
2012-10-01
The Tiwi people of northern Australia have managed natural resources continuously for 6000-8000 years. Tiwi management objectives and outcomes may reflect how they gather information about the environment. We qualitatively analyzed Tiwi documents and management techniques to examine the relation between the social and physical environment of decision makers and their decision-making strategies. We hypothesized that principles of bounded rationality, namely, the use of efficient rules to navigate complex decision problems, explain how Tiwi managers use simple decision strategies (i.e., heuristics) to make robust decisions. Tiwi natural resource managers reduced complexity in decision making through a process that gathers incomplete and uncertain information to quickly guide decisions toward effective outcomes. They used management feedback to validate decisions through an information loop that resulted in long-term sustainability of environmental use. We examined the Tiwi decision-making processes relative to management of barramundi (Lates calcarifer) fisheries and contrasted their management with the state government's management of barramundi. Decisions that enhanced the status of individual people and their attainment of aspiration levels resulted in reliable resource availability for Tiwi consumers. Different decision processes adopted by the state for management of barramundi may not secure similarly sustainable outcomes. ©2012 Society for Conservation Biology.
Modeling Human-Computer Decision Making with Covariance Structure Analysis.
ERIC Educational Resources Information Center
Coovert, Michael D.; And Others
Arguing that sufficient theory exists about the interplay between human information processing, computer systems, and the demands of various tasks to construct useful theories of human-computer interaction, this study presents a structural model of human-computer interaction and reports the results of various statistical analyses of this model.…
The First Flight Decision for New Human Spacecraft Vehicles - A General Approach
NASA Technical Reports Server (NTRS)
Schaible, Dawn M.; Sumrall, John Phillip
2011-01-01
Determining when it is safe to fly a crew on a launch vehicle/spacecraft for the first time, especially when the test flight is a part of the overall system certification process, has long been a challenge for program decision makers. The decision on first flight is ultimately the judgment of the program and agency management in conjunction with the design and operations team. To aid in this decision process, a NASA team undertook the task to develop a generic framework for evaluating whether any given program or commercial provider has sufficiently complete and balanced plans in place to allow crewmembers to safely fly on human spaceflight systems for the first time. It was the team s goal to establish a generic framework that could easily be applied to any new system, although the system design and intended mission would require specific assessment. Historical data shows that there are multiple approaches that have been successful in first flight with crew. These approaches have always been tailored to the specific system design, mission objectives, and launch environment. Because specific approaches may vary significantly between different system designs and situations, prescriptive instructions or thorough checklists cannot be provided ahead of time. There are, however, certain general approaches that should be applied in thinking through the decision for first flight. This paper addresses some of the most important factors to consider when developing a new system or evaluating an existing system for whether or not it is safe to fly humans to/from space. In the simplest terms, it is time to fly crew for the first time when it is safe to do so and the benefit of the crewed flight is greater than the residual risk. This is rarely a straight-forward decision. The paper describes the need for experience, sound judgment, close involvement of the technical and management teams, and established decision processes. In addition, the underlying level of confidence the manager has in making the decision will also be discussed. By applying the outlined thought processes and approaches to a specific design, test program and mission objectives, a project team will be better able to focus the debate and discussion on critical areas for consideration and added scrutiny -- allowing decision makers to adequately address the first crewed flight decision.
Drnec, Kim; Marathe, Amar R; Lukos, Jamie R; Metcalfe, Jason S
2016-01-01
Human automation interaction (HAI) systems have thus far failed to live up to expectations mainly because human users do not always interact with the automation appropriately. Trust in automation (TiA) has been considered a central influence on the way a human user interacts with an automation; if TiA is too high there will be overuse, if TiA is too low there will be disuse. However, even though extensive research into TiA has identified specific HAI behaviors, or trust outcomes, a unique mapping between trust states and trust outcomes has yet to be clearly identified. Interaction behaviors have been intensely studied in the domain of HAI and TiA and this has led to a reframing of the issues of problems with HAI in terms of reliance and compliance. We find the behaviorally defined terms reliance and compliance to be useful in their functionality for application in real-world situations. However, we note that once an inappropriate interaction behavior has occurred it is too late to mitigate it. We therefore take a step back and look at the interaction decision that precedes the behavior. We note that the decision neuroscience community has revealed that decisions are fairly stereotyped processes accompanied by measurable psychophysiological correlates. Two literatures were therefore reviewed. TiA literature was extensively reviewed in order to understand the relationship between TiA and trust outcomes, as well as to identify gaps in current knowledge. We note that an interaction decision precedes an interaction behavior and believe that we can leverage knowledge of the psychophysiological correlates of decisions to improve joint system performance. As we believe that understanding the interaction decision will be critical to the eventual mitigation of inappropriate interaction behavior, we reviewed the decision making literature and provide a synopsis of the state of the art understanding of the decision process from a decision neuroscience perspective. We forward hypotheses based on this understanding that could shape a research path toward the ability to mitigate interaction behavior in the real world.
Drnec, Kim; Marathe, Amar R.; Lukos, Jamie R.; Metcalfe, Jason S.
2016-01-01
Human automation interaction (HAI) systems have thus far failed to live up to expectations mainly because human users do not always interact with the automation appropriately. Trust in automation (TiA) has been considered a central influence on the way a human user interacts with an automation; if TiA is too high there will be overuse, if TiA is too low there will be disuse. However, even though extensive research into TiA has identified specific HAI behaviors, or trust outcomes, a unique mapping between trust states and trust outcomes has yet to be clearly identified. Interaction behaviors have been intensely studied in the domain of HAI and TiA and this has led to a reframing of the issues of problems with HAI in terms of reliance and compliance. We find the behaviorally defined terms reliance and compliance to be useful in their functionality for application in real-world situations. However, we note that once an inappropriate interaction behavior has occurred it is too late to mitigate it. We therefore take a step back and look at the interaction decision that precedes the behavior. We note that the decision neuroscience community has revealed that decisions are fairly stereotyped processes accompanied by measurable psychophysiological correlates. Two literatures were therefore reviewed. TiA literature was extensively reviewed in order to understand the relationship between TiA and trust outcomes, as well as to identify gaps in current knowledge. We note that an interaction decision precedes an interaction behavior and believe that we can leverage knowledge of the psychophysiological correlates of decisions to improve joint system performance. As we believe that understanding the interaction decision will be critical to the eventual mitigation of inappropriate interaction behavior, we reviewed the decision making literature and provide a synopsis of the state of the art understanding of the decision process from a decision neuroscience perspective. We forward hypotheses based on this understanding that could shape a research path toward the ability to mitigate interaction behavior in the real world. PMID:27445741
Process is the point: justice and human rights: priority setting and fair deliberative process.
Gruskin, Sofia; Daniels, Norman
2008-09-01
Most people responsible for setting priorities in health have considerable expertise relevant to deciding how to use resources effectively and the kinds of improvements that should be emphasized. Most are also concerned with distributing improvements equitably. Accordingly, they often invoke human rights or principles of distributive justice to legitimize choices that create winners and losers. We propose an approach that draws on the strengths of both perspectives as a way to add legitimacy to efforts to set priorities in health. Our proposal provides a process for setting priorities but is not a formula or an algorithm for generating particular priorities. We propose an approach that would do away with the process through which priorities are set and decisions made, and suggest the value of a focus on the process of legitimizing these decisions.
Jipp, Meike
2016-02-01
I explored whether different cognitive abilities (information-processing ability, working-memory capacity) are needed for expertise development when different types of automation (information vs. decision automation) are employed. It is well documented that expertise development and the employment of automation lead to improved performance. Here, it is argued that a learner's ability to reason about an activity may be hindered by the employment of information automation. Additional feedback needs to be processed, thus increasing the load on working memory and decelerating expertise development. By contrast, the employment of decision automation may stimulate reasoning, increase the initial load on information-processing ability, and accelerate expertise development. Authors of past research have not investigated the interrelations between automation assistance, individual differences, and expertise development. Sixty-one naive learners controlled simulated air traffic with two types of automation: information automation and decision automation. Their performance was captured across 16 trials. Well-established tests were used to assess information-processing ability and working-memory capacity. As expected, learners' performance benefited from expertise development and decision automation. Furthermore, individual differences moderated the effect of the type of automation on expertise development: The employment of only information automation increased the load on working memory during later expertise development. The employment of decision automation initially increased the need to process information. These findings highlight the importance of considering individual differences and expertise development when investigating human-automation interaction. The results are relevant for selecting automation configurations for expertise development. © 2015, Human Factors and Ergonomics Society.
Toward the Human Element. Beginning Handbook for Change. Volume I.
ERIC Educational Resources Information Center
Prince, Gerald; And Others
The primary aim of this handbook is to encourage and stimulate growth and renewal of the "human element" within the school environment. Four processes form the objectives that are fundamental to achieving this goal: problem solving, shared decision making, open communications, and accountability. Skills in these four processes are discussed in…
Human Dignity Through the American Experience. (Government). Grade 12.
ERIC Educational Resources Information Center
Vallejo Unified School District, CA.
The curriculum guide for twelfth grade pupils aims at helping students to understand and accept people who are different, develop a satisfactory self image, learn to think critically in the decision making process, and become familiar with the valuing process. Information on foundations in American government serves as a base for human rights and…
Adaptive automation of human-machine system information-processing functions.
Kaber, David B; Wright, Melanie C; Prinzel, Lawrence J; Clamann, Michael P
2005-01-01
The goal of this research was to describe the ability of human operators to interact with adaptive automation (AA) applied to various stages of complex systems information processing, defined in a model of human-automation interaction. Forty participants operated a simulation of an air traffic control task. Automated assistance was adaptively applied to information acquisition, information analysis, decision making, and action implementation aspects of the task based on operator workload states, which were measured using a secondary task. The differential effects of the forms of automation were determined and compared with a manual control condition. Results of two 20-min trials of AA or manual control revealed a significant effect of the type of automation on performance, particularly during manual control periods as part of the adaptive conditions. Humans appear to better adapt to AA applied to sensory and psychomotor information-processing functions (action implementation) than to AA applied to cognitive functions (information analysis and decision making), and AA is superior to completely manual control. Potential applications of this research include the design of automation to support air traffic controller information processing.
Hilbert, Martin
2012-03-01
A single coherent framework is proposed to synthesize long-standing research on 8 seemingly unrelated cognitive decision-making biases. During the past 6 decades, hundreds of empirical studies have resulted in a variety of rules of thumb that specify how humans systematically deviate from what is normatively expected from their decisions. Several complementary generative mechanisms have been proposed to explain those cognitive biases. Here it is suggested that (at least) 8 of these empirically detected decision-making biases can be produced by simply assuming noisy deviations in the memory-based information processes that convert objective evidence (observations) into subjective estimates (decisions). An integrative framework is presented to show how similar noise-based mechanisms can lead to conservatism, the Bayesian likelihood bias, illusory correlations, biased self-other placement, subadditivity, exaggerated expectation, the confidence bias, and the hard-easy effect. Analytical tools from information theory are used to explore the nature and limitations that characterize such information processes for binary and multiary decision-making exercises. The ensuing synthesis offers formal mathematical definitions of the biases and their underlying generative mechanism, which permits a consolidated analysis of how they are related. This synthesis contributes to the larger goal of creating a coherent picture that explains the relations among the myriad of seemingly unrelated biases and their potential psychological generative mechanisms. Limitations and research questions are discussed.
Parallel constraint satisfaction in memory-based decisions.
Glöckner, Andreas; Hodges, Sara D
2011-01-01
Three studies sought to investigate decision strategies in memory-based decisions and to test the predictions of the parallel constraint satisfaction (PCS) model for decision making (Glöckner & Betsch, 2008). Time pressure was manipulated and the model was compared against simple heuristics (take the best and equal weight) and a weighted additive strategy. From PCS we predicted that fast intuitive decision making is based on compensatory information integration and that decision time increases and confidence decreases with increasing inconsistency in the decision task. In line with these predictions we observed a predominant usage of compensatory strategies under all time-pressure conditions and even with decision times as short as 1.7 s. For a substantial number of participants, choices and decision times were best explained by PCS, but there was also evidence for use of simple heuristics. The time-pressure manipulation did not significantly affect decision strategies. Overall, the results highlight intuitive, automatic processes in decision making and support the idea that human information-processing capabilities are less severely bounded than often assumed.
Alterations in choice behavior by manipulations of world model.
Green, C S; Benson, C; Kersten, D; Schrater, P
2010-09-14
How to compute initially unknown reward values makes up one of the key problems in reinforcement learning theory, with two basic approaches being used. Model-free algorithms rely on the accumulation of substantial amounts of experience to compute the value of actions, whereas in model-based learning, the agent seeks to learn the generative process for outcomes from which the value of actions can be predicted. Here we show that (i) "probability matching"-a consistent example of suboptimal choice behavior seen in humans-occurs in an optimal Bayesian model-based learner using a max decision rule that is initialized with ecologically plausible, but incorrect beliefs about the generative process for outcomes and (ii) human behavior can be strongly and predictably altered by the presence of cues suggestive of various generative processes, despite statistically identical outcome generation. These results suggest human decision making is rational and model based and not consistent with model-free learning.
Integrated Risk-Informed Decision-Making for an ALMR PRISM
DOE Office of Scientific and Technical Information (OSTI.GOV)
Muhlheim, Michael David; Belles, Randy; Denning, Richard S.
Decision-making is the process of identifying decision alternatives, assessing those alternatives based on predefined metrics, selecting an alternative (i.e., making a decision), and then implementing that alternative. The generation of decisions requires a structured, coherent process, or a decision-making process. The overall objective for this work is that the generalized framework is adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or no human intervention. The overriding goal of automation is to replace ormore » supplement human decision makers with reconfigurable decision-making modules that can perform a given set of tasks rationally, consistently, and reliably. Risk-informed decision-making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The probabilistic portion of the decision-making engine of the supervisory control system is based on the control actions associated with an ALMR PRISM. Newly incorporated into the probabilistic models are the prognostic/diagnostic models developed by Pacific Northwest National Laboratory. These allow decisions to incorporate the health of components into the decision–making process. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic portion of the decision-making engine uses thermal-hydraulic modeling and components for an advanced liquid-metal reactor Power Reactor Inherently Safe Module. The deterministic multi-attribute decision-making framework uses various sensor data (e.g., reactor outlet temperature, steam generator drum level) and calculates its position within the challenge state, its trajectory, and its margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. The metrics that are evaluated are based on reactor trip set points. The integration of the deterministic calculations using multi-physics analyses and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermalhydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies, and developing a user interface to mimic display panels at a modern nuclear power plant.« less
Ito, Rutsuko; Lee, Andy C H
2016-10-15
The hippocampus (HPC) has been traditionally considered to subserve mnemonic processing and spatial cognition. Over the past decade, however, there has been increasing interest in its contributions to processes beyond these two domains. One question is whether the HPC plays an important role in decision-making under conditions of high approach-avoidance conflict, a scenario that arises when a goal stimulus is simultaneously associated with reward and punishment. This idea has its origins in rodent work conducted in the 1950s and 1960s, and has recently experienced a resurgence of interest in the literature. In this review, we will first provide an overview of classic rodent lesion data that first suggested a role for the HPC in approach-avoidance conflict processing and then proceed to describe a wide range of more recent evidence from studies conducted in rodents and humans. We will demonstrate that there is substantial, converging cross-species evidence to support the idea that the HPC, in particular the ventral (in rodents)/anterior (in humans) portion, contributes to approach-avoidance conflict decision making. Furthermore, we suggest that the seemingly disparate functions of the HPC (e.g. memory, spatial cognition, conflict processing) need not be mutually exclusive. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
O'Neil, Edward B; Newsome, Rachel N; Li, Iris H N; Thavabalasingam, Sathesan; Ito, Rutsuko; Lee, Andy C H
2015-11-11
Rodent models of anxiety have implicated the ventral hippocampus in approach-avoidance conflict processing. Few studies have, however, examined whether the human hippocampus plays a similar role. We developed a novel decision-making paradigm to examine neural activity when participants made approach/avoidance decisions under conditions of high or absent approach-avoidance conflict. Critically, our task required participants to learn the associated reward/punishment values of previously neutral stimuli and controlled for mnemonic and spatial processing demands, both important issues given approach-avoidance behavior in humans is less tied to predation and foraging compared to rodents. Participants played a points-based game where they first attempted to maximize their score by determining which of a series of previously neutral image pairs should be approached or avoided. During functional magnetic resonance imaging, participants were then presented with novel pairings of these images. These pairings consisted of images of congruent or opposing learned valences, the latter creating conditions of high approach-avoidance conflict. A data-driven partial least squares multivariate analysis revealed two reliable patterns of activity, each revealing differential activity in the anterior hippocampus, the homolog of the rodent ventral hippocampus. The first was associated with greater hippocampal involvement during trials with high as opposed to no approach-avoidance conflict, regardless of approach or avoidance behavior. The second pattern encompassed greater hippocampal activity in a more anterior aspect during approach compared to avoid responses, for conflict and no-conflict conditions. Multivoxel pattern classification analyses yielded converging findings, underlining a role of the anterior hippocampus in approach-avoidance conflict decision making. Approach-avoidance conflict has been linked to anxiety and occurs when a stimulus or situation is associated with reward and punishment. Although rodent work has implicated the hippocampus in approach-avoidance conflict processing, there is limited data on whether this role applies to learned, as opposed to innate, incentive values, and whether the human hippocampus plays a similar role. Using functional neuroimaging with a novel decision-making task that controlled for perceptual and mnemonic processing, we found that the human hippocampus was significantly active when approach-avoidance conflict was present for stimuli with learned incentive values. These findings demonstrate a role for the human hippocampus in approach-avoidance decision making that cannot be explained easily by hippocampal-dependent long-term memory or spatial cognition. Copyright © 2015 the authors 0270-6474/15/3515040-11$15.00/0.
The Bayesian reader: explaining word recognition as an optimal Bayesian decision process.
Norris, Dennis
2006-04-01
This article presents a theory of visual word recognition that assumes that, in the tasks of word identification, lexical decision, and semantic categorization, human readers behave as optimal Bayesian decision makers. This leads to the development of a computational model of word recognition, the Bayesian reader. The Bayesian reader successfully simulates some of the most significant data on human reading. The model accounts for the nature of the function relating word frequency to reaction time and identification threshold, the effects of neighborhood density and its interaction with frequency, and the variation in the pattern of neighborhood density effects seen in different experimental tasks. Both the general behavior of the model and the way the model predicts different patterns of results in different tasks follow entirely from the assumption that human readers approximate optimal Bayesian decision makers. ((c) 2006 APA, all rights reserved).
Neuroscience, moral reasoning, and the law.
Knabb, Joshua J; Welsh, Robert K; Ziebell, Joseph G; Reimer, Kevin S
2009-01-01
Modern advancements in functional magnetic resonance imaging (fMRI) technology have given neuroscientists the opportunity to more fully appreciate the brain's contribution to human behavior and decision making. Morality and moral reasoning are relative newcomers to the growing literature on decision neuroscience. With recent attention given to the salience of moral factors (e.g. moral emotions, moral reasoning) in the process of decision making, neuroscientists have begun to offer helpful frameworks for understanding the interplay between the brain, morality, and human decision making. These frameworks are relatively unfamiliar to the community of forensic psychologists, despite the fact that they offer an improved understanding of judicial decision making from a biological perspective. This article presents a framework reviewing how event-feature-emotion complexes (EFEC) are relevant to jurors and understanding complex criminal behavior. Future directions regarding converging fields of neuroscience and legal decision making are considered. Copyright 2009 John Wiley & Sons, Ltd.
Understanding human visual systems and its impact on our intelligent instruments
NASA Astrophysics Data System (ADS)
Strojnik Scholl, Marija; Páez, Gonzalo; Scholl, Michelle K.
2013-09-01
We review the evolution of machine vision and comment on the cross-fertilization from the neural sciences onto flourishing fields of neural processing, parallel processing, and associative memory in optical sciences and computing. Then we examine how the intensive efforts in mapping the human brain have been influenced by concepts in computer sciences, control theory, and electronic circuits. We discuss two neural paths that employ the input from the vision sense to determine the navigational options and object recognition. They are ventral temporal pathway for object recognition (what?) and dorsal parietal pathway for navigation (where?), respectively. We describe the reflexive and conscious decision centers in cerebral cortex involved with visual attention and gaze control. Interestingly, these require return path though the midbrain for ocular muscle control. We find that the cognitive psychologists currently study human brain employing low-spatial-resolution fMRI with temporal response on the order of a second. In recent years, the life scientists have concentrated on insect brains to study neural processes. We discuss how reflexive and conscious gaze-control decisions are made in the frontal eye field and inferior parietal lobe, constituting the fronto-parietal attention network. We note that ethical and experiential learnings impact our conscious decisions.
NASA Astrophysics Data System (ADS)
Müller-Hansen, Finn; Schlüter, Maja; Mäs, Michael; Donges, Jonathan F.; Kolb, Jakob J.; Thonicke, Kirsten; Heitzig, Jobst
2017-11-01
Today, humans have a critical impact on the Earth system and vice versa, which can generate complex feedback processes between social and ecological dynamics. Integrating human behavior into formal Earth system models (ESMs), however, requires crucial modeling assumptions about actors and their goals, behavioral options, and decision rules, as well as modeling decisions regarding human social interactions and the aggregation of individuals' behavior. Here, we review existing modeling approaches and techniques from various disciplines and schools of thought dealing with human behavior at different levels of decision making. We demonstrate modelers' often vast degrees of freedom but also seek to make modelers aware of the often crucial consequences of seemingly innocent modeling assumptions. After discussing which socioeconomic units are potentially important for ESMs, we compare models of individual decision making that correspond to alternative behavioral theories and that make diverse modeling assumptions about individuals' preferences, beliefs, decision rules, and foresight. We review approaches to model social interaction, covering game theoretic frameworks, models of social influence, and network models. Finally, we discuss approaches to studying how the behavior of individuals, groups, and organizations can aggregate to complex collective phenomena, discussing agent-based, statistical, and representative-agent modeling and economic macro-dynamics. We illustrate the main ingredients of modeling techniques with examples from land-use dynamics as one of the main drivers of environmental change bridging local to global scales.
Development of a safety decision-making scenario to measure worker safety in agriculture.
Mosher, G A; Keren, N; Freeman, S A; Hurburgh, C R
2014-04-01
Human factors play an important role in the management of occupational safety, especially in high-hazard workplaces such as commercial grain-handling facilities. Employee decision-making patterns represent an essential component of the safety system within a work environment. This research describes the process used to create a safety decision-making scenario to measure the process that grain-handling employees used to make choices in a safety-related work task. A sample of 160 employees completed safety decision-making simulations based on a hypothetical but realistic scenario in a grain-handling environment. Their choices and the information they used to make their choices were recorded. Although the employees emphasized safety information in their decision-making process, not all of their choices were safe choices. Factors influencing their choices are discussed, and implications for industry, management, and workers are shared.
NASA Astrophysics Data System (ADS)
Widianta, M. M. D.; Rizaldi, T.; Setyohadi, D. P. S.; Riskiawan, H. Y.
2018-01-01
The right decision in placing employees in an appropriate position in a company will support the quality of management and will have an impact on improving the quality of human resources of the company. Such decision-making can be assisted by an approach through the Decision Support System (DSS) to improve accuracy in the employee placement process. The purpose of this paper is to compare the four methods of Multi Criteria Decision Making (MCDM), ie Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Simple Additive Weighting (SAW), Analytic Hierarchy Process (AHP) and Preference Ranking Organization Method for Enrichment Of Evaluations (PROMETHEE) for the application of employee placement in accordance with predetermined criteria. The ranking results and the accuracy level obtained from each method are different depending on the different scaling and weighting processes in each method.
Information processing as a paradigm for decision making.
Oppenheimer, Daniel M; Kelso, Evan
2015-01-03
For decades, the dominant paradigm for studying decision making--the expected utility framework--has been burdened by an increasing number of empirical findings that question its validity as a model of human cognition and behavior. However, as Kuhn (1962) argued in his seminal discussion of paradigm shifts, an old paradigm cannot be abandoned until a new paradigm emerges to replace it. In this article, we argue that the recent shift in researcher attention toward basic cognitive processes that give rise to decision phenomena constitutes the beginning of that replacement paradigm. Models grounded in basic perceptual, attentional, memory, and aggregation processes have begun to proliferate. The development of this new approach closely aligns with Kuhn's notion of paradigm shift, suggesting that this is a particularly generative and revolutionary time to be studying decision science.
Option Generation Techniques for Command and Control.
1983-01-01
and discuss some reasons why decision making is often less than perfect. 3.2. The Process of Decision Making Figure 3.1 shows a model of the various...responses to changes in the problem context. Most of these potential reasons for poor decision making stem from the human decision maker’s cognitive...several advantages: (1) It provides a mechanism for quickly estimating the scope of the effort that should be involved in making the decison and a road map
Human Judgment and Decision Making: A Proposed Decision Model Using Sequential Processing
1985-08-01
to the issues noted above is called policy capturing ( Szilagyi and Wallace , 1983). 4 The purpose of policy capturing is to develop a decision making...papers have been written on this general subject. A concise overview of this discipline is found in Szilagyi and Wallace (1983). Basically, decision models... Szilagyi , A. and Wallace , H. Organizational Behavior and Performance (3rd Ed.), Scott, Foresman and Company, 1983. Taylor, R. L. and Wilsted, W. D
Adversarial Collaboration Decision-Making: An Overview of Social Quantum Information Processing
2002-01-01
collaborative decision - making (CDM) to solve problems is an aspect of human behavior least yielding to rational predictions. To reduce the complexity of CDM...increases. Implications for C2 decision - making are discussed. Overview of research Game theory was one of the first rational approaches to the study of...Psychologist, 36, 343-356. Lawless, W.F. (2001), The quantum of social action and the function of emotion in decision - making , Proceedings, Emotional and
Frames, biases, and rational decision-making in the human brain.
De Martino, Benedetto; Kumaran, Dharshan; Seymour, Ben; Dolan, Raymond J
2006-08-04
Human choices are remarkably susceptible to the manner in which options are presented. This so-called "framing effect" represents a striking violation of standard economic accounts of human rationality, although its underlying neurobiology is not understood. We found that the framing effect was specifically associated with amygdala activity, suggesting a key role for an emotional system in mediating decision biases. Moreover, across individuals, orbital and medial prefrontal cortex activity predicted a reduced susceptibility to the framing effect. This finding highlights the importance of incorporating emotional processes within models of human choice and suggests how the brain may modulate the effect of these biasing influences to approximate rationality.
Simulating motivated cognition
NASA Technical Reports Server (NTRS)
Gevarter, William B.
1991-01-01
A research effort to develop a sophisticated computer model of human behavior is described. A computer framework of motivated cognition was developed. Motivated cognition focuses on the motivations or affects that provide the context and drive in human cognition and decision making. A conceptual architecture of the human decision-making approach from the perspective of information processing in the human brain is developed in diagrammatic form. A preliminary version of such a diagram is presented. This architecture is then used as a vehicle for successfully constructing a computer program simulation Dweck and Leggett's findings that relate how an individual's implicit theories orient them toward particular goals, with resultant cognitions, affects, and behavior.
Forsythe, J Chris [Sandia Park, NM; Xavier, Patrick G [Albuquerque, NM; Abbott, Robert G [Albuquerque, NM; Brannon, Nathan G [Albuquerque, NM; Bernard, Michael L [Tijeras, NM; Speed, Ann E [Albuquerque, NM
2009-04-28
Digital technology utilizing a cognitive model based on human naturalistic decision-making processes, including pattern recognition and episodic memory, can reduce the dependency of human-machine interactions on the abilities of a human user and can enable a machine to more closely emulate human-like responses. Such a cognitive model can enable digital technology to use cognitive capacities fundamental to human-like communication and cooperation to interact with humans.
ERIC Educational Resources Information Center
Stoilov, Todor, Ed.
2012-01-01
The time management is worthy goal of many human activities. It concerns variety problems related to goals definition, assessment of available resources, control of management policies, scheduling of decisions. This book is an attempt to illustrate the decision making process in time management for different success stories, which can be used as…
Framework for Human Health Risk Assessment to Inform Decision Making
The purpose of this document is to describe a Framework for conducting human health risk assessments that are responsive to the needs of decision‐making processes in the U.S. Environmental Protection Agency (EPA).
Understanding Optimal Decision-Making in Wargaming
2013-09-01
of which is a better understanding of the impact of decisions as a part of combat processes. However, using wargaming to understand decision-making...Raymond, 1989). In the aviation domain, pilots exhibit different visual scanning patterns during various phases of flying under instrument flight rules ( IFR ...human neuro- science, 7, 2013. Anna Skinner, Chris Berka, Lindsay Ohara-Long, and Marc Sebrechts. Impact of virtual en- vironment fidelity on behavioral
NASA Astrophysics Data System (ADS)
Mishra, S. K.; Rapolu, U.; Ding, D.; Muste, M.; Bennett, D.; Schnoor, J. L.
2011-12-01
Human activity is intricately linked to the quality and quantity of water resources. Although many studies have examined water-human interaction, the complexity of such coupled systems is not well understood largely because of gaps in our knowledge of water-cycle processes which are heavily influenced by socio-economic drivers. Considerable research has been performed to develop an understanding of the impact of local land use decisions on field and catchment processes at an annual basis. Still less is known about the impact of economic and environmental outcomes on decision-making processes at the local and national level. Traditional geographic information management systems lack the ability to support the modeling and analysis of complex spatial processes. New frameworks are needed to track, query, and analyze the massive amounts of data generated by ensembles of simulations produced by multiple models that couple socioeconomic and natural system processes. On this context, we propose to develop an Intelligent Digital Watershed (IDW) which fuses emerging concepts of Digital Watershed (DW). DW is a comprehensive characterization of the eco hydrologic systems based on the best available digital data generated by measurements and simulations models. Prototype IDW in the form of a cyber infrastructure based engineered system will facilitate novel insights into human/environment interactions through multi-disciplinary research focused on watershed-related processes at multiple spatio-temporal scales. In ongoing effort, the prototype IDW is applied to Clear Creek watershed, an agricultural dominating catchment in Iowa, to understand water-human processes relevant to management decisions by farmers regarding agro ecosystems. This paper would also lay out the database design that stores metadata about simulation scenarios, scenario inputs and outputs, and connections among these elements- essentially the database. The paper describes the cyber infrastructure and workflows developed for connecting the IDW modeling tools: ABM, Data-Driven Modeling, and SWAT.
Context is everything or how could I have been that stupid?
Croskerry, Pat
2009-01-01
Dual Process Theory provides a useful working model of decision-making. It broadly divides decision-making into intuitive (System 1) and analytical (System 2) processes. System 1 is especially dependent on contextual cues. There appears to be a universal human tendency to contextualize information, mostly in an effort to imbue meaning but also, perhaps, to conserve cognitive energy. Most decision errors occur in System 1, and this has two major implications. The first is that insufficient account may have been taken out of context when the original decision was made. Secondly, in trying to learn from decision failures, we need the highest fidelity of context reconstruction as possible. It should be appreciated that learning from past events is inevitably an imperfect process. Retrospective investigations, such as root-cause analysis, critical incident review, morbidity and mortality rounds and legal investigations, all suffer the limitation that they cannot faithfully reconstruct the context in which decisions were made and from which actions followed.
Efficient cost-sensitive human-machine collaboration for offline signature verification
NASA Astrophysics Data System (ADS)
Coetzer, Johannes; Swanepoel, Jacques; Sabourin, Robert
2012-01-01
We propose a novel strategy for the optimal combination of human and machine decisions in a cost-sensitive environment. The proposed algorithm should be especially beneficial to financial institutions where off-line signatures, each associated with a specific transaction value, require authentication. When presented with a collection of genuine and fraudulent training signatures, produced by so-called guinea pig writers, the proficiency of a workforce of human employees and a score-generating machine can be estimated and represented in receiver operating characteristic (ROC) space. Using a set of Boolean fusion functions, the majority vote decision of the human workforce is combined with each threshold-specific machine-generated decision. The performance of the candidate ensembles is estimated and represented in ROC space, after which only the optimal ensembles and associated decision trees are retained. When presented with a questioned signature linked to an arbitrary writer, the system first uses the ROC-based cost gradient associated with the transaction value to select the ensemble that minimises the expected cost, and then uses the corresponding decision tree to authenticate the signature in question. We show that, when utilising the entire human workforce, the incorporation of a machine streamlines the authentication process and decreases the expected cost for all operating conditions.
On-line confidence monitoring during decision making.
Dotan, Dror; Meyniel, Florent; Dehaene, Stanislas
2018-02-01
Humans can readily assess their degree of confidence in their decisions. Two models of confidence computation have been proposed: post hoc computation using post-decision variables and heuristics, versus online computation using continuous assessment of evidence throughout the decision-making process. Here, we arbitrate between these theories by continuously monitoring finger movements during a manual sequential decision-making task. Analysis of finger kinematics indicated that subjects kept separate online records of evidence and confidence: finger deviation continuously reflected the ongoing accumulation of evidence, whereas finger speed continuously reflected the momentary degree of confidence. Furthermore, end-of-trial finger speed predicted the post-decisional subjective confidence rating. These data indicate that confidence is computed on-line, throughout the decision process. Speed-confidence correlations were previously interpreted as a post-decision heuristics, whereby slow decisions decrease subjective confidence, but our results suggest an adaptive mechanism that involves the opposite causality: by slowing down when unconfident, participants gain time to improve their decisions. Copyright © 2017 Elsevier B.V. All rights reserved.
Perceptual Decisions in the Presence of Relevant and Irrelevant Sensory Evidence
Anders, Ursula M.; McLean, Charlotte S.; Ouyang, Bowen; Ditterich, Jochen
2017-01-01
Perceptual decisions in the presence of decision-irrelevant sensory information require a selection of decision-relevant sensory evidence. To characterize the mechanism that is responsible for separating decision-relevant from irrelevant sensory information we asked human subjects to make judgments about one of two simultaneously present motion components in a random dot stimulus. Subjects were able to ignore the decision-irrelevant component to a large degree, but their decisions were still influenced by the irrelevant sensory information. Computational modeling revealed that this influence was not simply the consequence of subjects forgetting at times which stimulus component they had been instructed to base their decision on. Instead, residual irrelevant information always seems to be leaking through, and the decision process is captured by a net sensory evidence signal being accumulated to a decision threshold. This net sensory evidence is a linear combination of decision-relevant and irrelevant sensory information. The selection process is therefore well-described by a strong linear gain modulation, which, in our experiment, resulted in the relevant sensory evidence having at least 10 times more impact on the decision than the irrelevant evidence. PMID:29176941
Perceptual Decisions in the Presence of Relevant and Irrelevant Sensory Evidence.
Anders, Ursula M; McLean, Charlotte S; Ouyang, Bowen; Ditterich, Jochen
2017-01-01
Perceptual decisions in the presence of decision-irrelevant sensory information require a selection of decision-relevant sensory evidence. To characterize the mechanism that is responsible for separating decision-relevant from irrelevant sensory information we asked human subjects to make judgments about one of two simultaneously present motion components in a random dot stimulus. Subjects were able to ignore the decision-irrelevant component to a large degree, but their decisions were still influenced by the irrelevant sensory information. Computational modeling revealed that this influence was not simply the consequence of subjects forgetting at times which stimulus component they had been instructed to base their decision on. Instead, residual irrelevant information always seems to be leaking through, and the decision process is captured by a net sensory evidence signal being accumulated to a decision threshold. This net sensory evidence is a linear combination of decision-relevant and irrelevant sensory information. The selection process is therefore well-described by a strong linear gain modulation, which, in our experiment, resulted in the relevant sensory evidence having at least 10 times more impact on the decision than the irrelevant evidence.
Roughead, Elizabeth Ellen; Gilbert, Andrew L; Vitry, Agnes I
2008-12-01
To analyse the media and political reactions to the initial decision of the Pharmaceutical Benefits Advisory Committee (PBAC) to reject funding of the quadrivalent human papilloma virus (HPV) vaccine in Australia. A case study, informed by media reports and government documents, was utilised to examine the reactions of key stakeholders; PBAC, consumers, consumer organisations, pharmaceutical industry, politicians, health professionals and the media to the initial decision to reject funding of HPV vaccine. The initial decision to reject funding of the HPV vaccine led to unprecedented public response with over 300 newspaper articles and calls by consumers, health professionals and politicians to intervene in the decision making process. Misunderstanding of the decision making process, particularly cost-effectiveness assessments, the need for an independent process, the legislated inability of a timely and transparent response from policy makers and the lack of a risk mitigation strategy all played a role in the public outcry. Despite 15 years of implementation of cost-effectiveness assessments there is still a need for improving stakeholder understanding of the decision making process and for timely transfer of complete information. Risk mitigation strategies should be considered as part of the communication plan for all decisions.
Teaching through Trade Books: Humans and the Earth
ERIC Educational Resources Information Center
Royce, Christine Anne
2016-01-01
This column includes activities inspired by children's literature. Elementary students are beginning to understand the Earth's natural processes and humans' impact on the Earth. Humans need the natural resources that the Earth produces, use these resources to develop civilizations, and make decisions to offset the damage they cause, as well as…
Limits in decision making arise from limits in memory retrieval.
Giguère, Gyslain; Love, Bradley C
2013-05-07
Some decisions, such as predicting the winner of a baseball game, are challenging in part because outcomes are probabilistic. When making such decisions, one view is that humans stochastically and selectively retrieve a small set of relevant memories that provides evidence for competing options. We show that optimal performance at test is impossible when retrieving information in this fashion, no matter how extensive training is, because limited retrieval introduces noise into the decision process that cannot be overcome. One implication is that people should be more accurate in predicting future events when trained on idealized rather than on the actual distributions of items. In other words, we predict the best way to convey information to people is to present it in a distorted, idealized form. Idealization of training distributions is predicted to reduce the harmful noise induced by immutable bottlenecks in people's memory retrieval processes. In contrast, machine learning systems that selectively weight (i.e., retrieve) all training examples at test should not benefit from idealization. These conjectures are strongly supported by several studies and supporting analyses. Unlike machine systems, people's test performance on a target distribution is higher when they are trained on an idealized version of the distribution rather than on the actual target distribution. Optimal machine classifiers modified to selectively and stochastically sample from memory match the pattern of human performance. These results suggest firm limits on human rationality and have broad implications for how to train humans tasked with important classification decisions, such as radiologists, baggage screeners, intelligence analysts, and gamblers.
Limits in decision making arise from limits in memory retrieval
Giguère, Gyslain; Love, Bradley C.
2013-01-01
Some decisions, such as predicting the winner of a baseball game, are challenging in part because outcomes are probabilistic. When making such decisions, one view is that humans stochastically and selectively retrieve a small set of relevant memories that provides evidence for competing options. We show that optimal performance at test is impossible when retrieving information in this fashion, no matter how extensive training is, because limited retrieval introduces noise into the decision process that cannot be overcome. One implication is that people should be more accurate in predicting future events when trained on idealized rather than on the actual distributions of items. In other words, we predict the best way to convey information to people is to present it in a distorted, idealized form. Idealization of training distributions is predicted to reduce the harmful noise induced by immutable bottlenecks in people’s memory retrieval processes. In contrast, machine learning systems that selectively weight (i.e., retrieve) all training examples at test should not benefit from idealization. These conjectures are strongly supported by several studies and supporting analyses. Unlike machine systems, people’s test performance on a target distribution is higher when they are trained on an idealized version of the distribution rather than on the actual target distribution. Optimal machine classifiers modified to selectively and stochastically sample from memory match the pattern of human performance. These results suggest firm limits on human rationality and have broad implications for how to train humans tasked with important classification decisions, such as radiologists, baggage screeners, intelligence analysts, and gamblers. PMID:23610402
Evolutionary game dynamics of controlled and automatic decision-making
NASA Astrophysics Data System (ADS)
Toupo, Danielle F. P.; Strogatz, Steven H.; Cohen, Jonathan D.; Rand, David G.
2015-07-01
We integrate dual-process theories of human cognition with evolutionary game theory to study the evolution of automatic and controlled decision-making processes. We introduce a model in which agents who make decisions using either automatic or controlled processing compete with each other for survival. Agents using automatic processing act quickly and so are more likely to acquire resources, but agents using controlled processing are better planners and so make more effective use of the resources they have. Using the replicator equation, we characterize the conditions under which automatic or controlled agents dominate, when coexistence is possible and when bistability occurs. We then extend the replicator equation to consider feedback between the state of the population and the environment. Under conditions in which having a greater proportion of controlled agents either enriches the environment or enhances the competitive advantage of automatic agents, we find that limit cycles can occur, leading to persistent oscillations in the population dynamics. Critically, however, these limit cycles only emerge when feedback occurs on a sufficiently long time scale. Our results shed light on the connection between evolution and human cognition and suggest necessary conditions for the rise and fall of rationality.
Evolutionary game dynamics of controlled and automatic decision-making.
Toupo, Danielle F P; Strogatz, Steven H; Cohen, Jonathan D; Rand, David G
2015-07-01
We integrate dual-process theories of human cognition with evolutionary game theory to study the evolution of automatic and controlled decision-making processes. We introduce a model in which agents who make decisions using either automatic or controlled processing compete with each other for survival. Agents using automatic processing act quickly and so are more likely to acquire resources, but agents using controlled processing are better planners and so make more effective use of the resources they have. Using the replicator equation, we characterize the conditions under which automatic or controlled agents dominate, when coexistence is possible and when bistability occurs. We then extend the replicator equation to consider feedback between the state of the population and the environment. Under conditions in which having a greater proportion of controlled agents either enriches the environment or enhances the competitive advantage of automatic agents, we find that limit cycles can occur, leading to persistent oscillations in the population dynamics. Critically, however, these limit cycles only emerge when feedback occurs on a sufficiently long time scale. Our results shed light on the connection between evolution and human cognition and suggest necessary conditions for the rise and fall of rationality.
What Brain Sciences Reveal about Integrating Theory and Practice
ERIC Educational Resources Information Center
Patton, Michael Quinn
2014-01-01
Theory and practice are integrated in the human brain. Situation recognition and response are key to this integration. Scholars of decision making and expertise have found that people with great expertise are more adept at situational recognition and intentional about their decision-making processes. Several interdisciplinary fields of inquiry…
Prefrontal Brain Activity Predicts Temporally Extended Decision-Making Behavior
ERIC Educational Resources Information Center
Yarkoni, Tal; Braver, Todd S.; Gray, Jeremy R.; Green, Leonard
2005-01-01
Although functional neuroimaging studies of human decision-making processes are increasingly common, most of the research in this area has relied on passive tasks that generate little individual variability. Relatively little attention has been paid to the ability of brain activity to predict overt behavior. Using functional magnetic resonance…
Catalani, Caricia; Green, Eric; Owiti, Philip; Keny, Aggrey; Diero, Lameck; Yeung, Ada; Israelski, Dennis; Biondich, Paul
2014-01-01
With the aim of integrating HIV and tuberculosis care in rural Kenya, a team of researchers, clinicians, and technologists used the human-centered design approach to facilitate design, development, and deployment processes of new patient-specific TB clinical decision support system for medical providers. In Kenya, approximately 1.6 million people are living with HIV and have a 20-times higher risk of dying of tuberculosis. Although tuberculosis prevention and treatment medication is widely available, proven to save lives, and prioritized by the World Health Organization, ensuring that it reaches the most vulnerable communities remains challenging. Human-centered design, used in the fields of industrial design and information technology for decades, is an approach to improving the effectiveness and impact of innovations that has been scarcely used in the health field. Using this approach, our team followed a 3-step process, involving mixed methods assessment to (1) understand the situation through the collection and analysis of site observation sessions and key informant interviews; (2) develop a new clinical decision support system through iterative prototyping, end-user engagement, and usability testing; and, (3) implement and evaluate the system across 24 clinics in rural West Kenya. Through the application of this approach, we found that human-centered design facilitated the process of digital innovation in a complex and resource-constrained context.
Catalani, Caricia; Green, Eric; Owiti, Philip; Keny, Aggrey; Diero, Lameck; Yeung, Ada; Israelski, Dennis; Biondich, Paul
2014-01-01
With the aim of integrating HIV and tuberculosis care in rural Kenya, a team of researchers, clinicians, and technologists used the human-centered design approach to facilitate design, development, and deployment processes of new patient-specific TB clinical decision support system for medical providers. In Kenya, approximately 1.6 million people are living with HIV and have a 20-times higher risk of dying of tuberculosis. Although tuberculosis prevention and treatment medication is widely available, proven to save lives, and prioritized by the World Health Organization, ensuring that it reaches the most vulnerable communities remains challenging. Human-centered design, used in the fields of industrial design and information technology for decades, is an approach to improving the effectiveness and impact of innovations that has been scarcely used in the health field. Using this approach, our team followed a 3-step process, involving mixed methods assessment to (1) understand the situation through the collection and analysis of site observation sessions and key informant interviews; (2) develop a new clinical decision support system through iterative prototyping, end-user engagement, and usability testing; and, (3) implement and evaluate the system across 24 clinics in rural West Kenya. Through the application of this approach, we found that human-centered design facilitated the process of digital innovation in a complex and resource-constrained context. PMID:25170939
Evolution of quantum-like modeling in decision making processes
NASA Astrophysics Data System (ADS)
Khrennikova, Polina
2012-12-01
The application of the mathematical formalism of quantum mechanics to model behavioral patterns in social science and economics is a novel and constantly emerging field. The aim of the so called 'quantum like' models is to model the decision making processes in a macroscopic setting, capturing the particular 'context' in which the decisions are taken. Several subsequent empirical findings proved that when making a decision people tend to violate the axioms of expected utility theory and Savage's Sure Thing principle, thus violating the law of total probability. A quantum probability formula was devised to describe more accurately the decision making processes. A next step in the development of QL-modeling in decision making was the application of Schrödinger equation to describe the evolution of people's mental states. A shortcoming of Schrödinger equation is its inability to capture dynamics of an open system; the brain of the decision maker can be regarded as such, actively interacting with the external environment. Recently the master equation, by which quantum physics describes the process of decoherence as the result of interaction of the mental state with the environmental 'bath', was introduced for modeling the human decision making. The external environment and memory can be referred to as a complex 'context' influencing the final decision outcomes. The master equation can be considered as a pioneering and promising apparatus for modeling the dynamics of decision making in different contexts.
Flamm, Richard Owen; Reynolds, John Elliot; Harmak, Craig
2013-01-01
We used southwestern Florida as a case study to lay the groundwork for an intended and organized decision-making process for managing warm-water habitat needed by endangered manatees to survive winters in Florida. Scientists and managers have prioritized (a) projecting how the network of warm-water sites will change over the next 50 years as warmed industrial discharges may expire and as flows of natural springs are reduced through redirection of water for human uses, and (b) mitigating such changes to prevent undue consequences to manatees. Given the complexities introduced by manatee ecology; agency organizational structure; shifting public demands; fluctuating resource availability; and managing within interacting cultural, social, political, and environmental contexts, it was clear that a structured decision process was needed. To help promote such a process, we collected information relevant to future decisions including maps of known and suspected warm-water sites and prototyped a characterization of sites and networks. We propose steps that would lead to models that might serve as core tools in manatee/warm-water decision-making, and we summarized topics relevant for informed decision-making (e.g., manatee spatial cognition, risk of cold-stress morbidity and mortality, and human dimensions). A major impetus behind this effort is to ensure proactively that robust modeling tools are available well in advance of the anticipated need for a critical management decision.
NASA Astrophysics Data System (ADS)
Flamm, Richard Owen; Reynolds, John Elliot; Harmak, Craig
2013-01-01
We used southwestern Florida as a case study to lay the groundwork for an intended and organized decision-making process for managing warm-water habitat needed by endangered manatees to survive winters in Florida. Scientists and managers have prioritized (a) projecting how the network of warm-water sites will change over the next 50 years as warmed industrial discharges may expire and as flows of natural springs are reduced through redirection of water for human uses, and (b) mitigating such changes to prevent undue consequences to manatees. Given the complexities introduced by manatee ecology; agency organizational structure; shifting public demands; fluctuating resource availability; and managing within interacting cultural, social, political, and environmental contexts, it was clear that a structured decision process was needed. To help promote such a process, we collected information relevant to future decisions including maps of known and suspected warm-water sites and prototyped a characterization of sites and networks. We propose steps that would lead to models that might serve as core tools in manatee/warm-water decision-making, and we summarized topics relevant for informed decision-making (e.g., manatee spatial cognition, risk of cold-stress morbidity and mortality, and human dimensions). A major impetus behind this effort is to ensure proactively that robust modeling tools are available well in advance of the anticipated need for a critical management decision.
Evolutionary fuzzy modeling human diagnostic decisions.
Peña-Reyes, Carlos Andrés
2004-05-01
Fuzzy CoCo is a methodology, combining fuzzy logic and evolutionary computation, for constructing systems able to accurately predict the outcome of a human decision-making process, while providing an understandable explanation of the underlying reasoning. Fuzzy logic provides a formal framework for constructing systems exhibiting both good numeric performance (accuracy) and linguistic representation (interpretability). However, fuzzy modeling--meaning the construction of fuzzy systems--is an arduous task, demanding the identification of many parameters. To solve it, we use evolutionary computation techniques (specifically cooperative coevolution), which are widely used to search for adequate solutions in complex spaces. We have successfully applied the algorithm to model the decision processes involved in two breast cancer diagnostic problems, the WBCD problem and the Catalonia mammography interpretation problem, obtaining systems both of high performance and high interpretability. For the Catalonia problem, an evolved system was embedded within a Web-based tool-called COBRA-for aiding radiologists in mammography interpretation.
Cognitive Processes in Decisions Under Risk are not the Same as in Decisions Under Uncertainty
Volz, Kirsten G.; Gigerenzer, Gerd
2012-01-01
We deal with risk versus uncertainty, a distinction that is of fundamental importance for cognitive neuroscience yet largely neglected. In a world of risk (“small world”), all alternatives, consequences, and probabilities are known. In uncertain (“large”) worlds, some of this information is unknown or unknowable. Most of cognitive neuroscience studies exclusively study the neural correlates for decisions under risk (e.g., lotteries), with the tacit implication that understanding these would lead to an understanding of decision making in general. First, we show that normative strategies for decisions under risk do not generalize to uncertain worlds, where simple heuristics are often the more accurate strategies. Second, we argue that the cognitive processes for making decisions in a world of risk are not the same as those for dealing with uncertainty. Because situations with known risks are the exception rather than the rule in human evolution, it is unlikely that our brains are adapted to them. We therefore suggest a paradigm shift toward studying decision processes in uncertain worlds and provide first examples. PMID:22807893
How Awareness Changes the Relative Weights of Evidence During Human Decision-Making
Lamme, Victor A. F.; Dehaene, Stanislas
2011-01-01
Human decisions are based on accumulating evidence over time for different options. Here we ask a simple question: How is the accumulation of evidence affected by the level of awareness of the information? We examined the influence of awareness on decision-making using combined behavioral methods and magneto-encephalography (MEG). Participants were required to make decisions by accumulating evidence over a series of visually presented arrow stimuli whose visibility was modulated by masking. Behavioral results showed that participants could accumulate evidence under both high and low visibility. However, a top-down strategic modulation of the flow of incoming evidence was only present for stimuli with high visibility: once enough evidence had been accrued, participants strategically reduced the impact of new incoming stimuli. Also, decision-making speed and confidence were strongly modulated by the strength of the evidence for high-visible but not low-visible evidence, even though direct priming effects were identical for both types of stimuli. Neural recordings revealed that, while initial perceptual processing was independent of visibility, there was stronger top-down amplification for stimuli with high visibility than low visibility. Furthermore, neural markers of evidence accumulation over occipito-parietal cortex showed a strategic bias only for highly visible sensory information, speeding up processing and reducing neural computations related to the decision process. Our results indicate that the level of awareness of information changes decision-making: while accumulation of evidence already exists under low visibility conditions, high visibility allows evidence to be accumulated up to a higher level, leading to important strategical top-down changes in decision-making. Our results therefore suggest a potential role of awareness in deploying flexible strategies for biasing information acquisition in line with one's expectations and goals. PMID:22131904
How awareness changes the relative weights of evidence during human decision-making.
de Lange, Floris P; van Gaal, Simon; Lamme, Victor A F; Dehaene, Stanislas
2011-11-01
Human decisions are based on accumulating evidence over time for different options. Here we ask a simple question: How is the accumulation of evidence affected by the level of awareness of the information? We examined the influence of awareness on decision-making using combined behavioral methods and magneto-encephalography (MEG). Participants were required to make decisions by accumulating evidence over a series of visually presented arrow stimuli whose visibility was modulated by masking. Behavioral results showed that participants could accumulate evidence under both high and low visibility. However, a top-down strategic modulation of the flow of incoming evidence was only present for stimuli with high visibility: once enough evidence had been accrued, participants strategically reduced the impact of new incoming stimuli. Also, decision-making speed and confidence were strongly modulated by the strength of the evidence for high-visible but not low-visible evidence, even though direct priming effects were identical for both types of stimuli. Neural recordings revealed that, while initial perceptual processing was independent of visibility, there was stronger top-down amplification for stimuli with high visibility than low visibility. Furthermore, neural markers of evidence accumulation over occipito-parietal cortex showed a strategic bias only for highly visible sensory information, speeding up processing and reducing neural computations related to the decision process. Our results indicate that the level of awareness of information changes decision-making: while accumulation of evidence already exists under low visibility conditions, high visibility allows evidence to be accumulated up to a higher level, leading to important strategical top-down changes in decision-making. Our results therefore suggest a potential role of awareness in deploying flexible strategies for biasing information acquisition in line with one's expectations and goals.
New Directions for Military Decision Making Research in Combat and Operational Settings
1991-12-01
information; their search rules emphasize feasibility more than optimality; decisions depend on the order in which alternatives are presented...12:76-90. Easterbrook, J.A. "The effect of Emotion on Cue Utilization and the Organization of Behaviour." Psychological Review, 1959, 66:183-201...Acquisition and Affective State on Halo, Accuracy, Information Retrival , and Evaluations." Organizational Behavior and Human Decision Processes, 1988, 42:22
Corporate funding of human services agencies.
Zippay, A
1992-05-01
This article reviews national trends in the organization of corporate giving to human services agencies, examines how corporations make funding decisions, and reports the results of a case study of philanthropic giving among 29 companies in Cambridge, Massachusetts. The study found that most corporations use an informal rather than a formal process for making funding decisions, with many firms relying on tradition, social contacts, and intuition to guide allocations. Suggestions that social services administrators can use to enhance development planning at their agencies are provided.
Influence of biases in numerical magnitude allocation on human prosocial decision making.
Arshad, Qadeer; Nigmatullina, Yuliya; Siddiqui, Shuaib; Franka, Mustafa; Mediratta, Saniya; Ramachandaran, Sanjeev; Lobo, Rhannon; Malhotra, Paresh A; Roberts, R E; Bronstein, Adolfo M
2017-12-01
Over the past decade neuroscientific research has attempted to probe the neurobiological underpinnings of human prosocial decision making. Such research has almost ubiquitously employed tasks such as the dictator game or similar variations (i.e., ultimatum game). Considering the explicit numerical nature of such tasks, it is surprising that the influence of numerical cognition on decision making during task performance remains unknown. While performing these tasks, participants typically tend to anchor on a 50:50 split that necessitates an explicit numerical judgement (i.e., number-pair bisection). Accordingly, we hypothesize that the decision-making process during the dictator game recruits overlapping cognitive processes to those known to be engaged during number-pair bisection. We observed that biases in numerical magnitude allocation correlated with the formulation of decisions during the dictator game. That is, intrinsic biases toward smaller numerical magnitudes were associated with the formulation of less favorable decisions, whereas biases toward larger magnitudes were associated with more favorable choices. We proceeded to corroborate this relationship by subliminally and systematically inducing biases in numerical magnitude toward either higher or lower numbers using a visuo-vestibular stimulation paradigm. Such subliminal alterations in numerical magnitude allocation led to proportional and corresponding changes to an individual's decision making during the dictator game. Critically, no relationship was observed between neither intrinsic nor induced biases in numerical magnitude on decision making when assessed using a nonnumerical-based prosocial questionnaire. Our findings demonstrate numerical influences on decisions formulated during the dictator game and highlight the necessity to control for confounds associated with numerical cognition in human decision-making paradigms. NEW & NOTEWORTHY We demonstrate that intrinsic biases in numerical magnitude can directly predict the amount of money donated by an individual to an anonymous stranger during the dictator game. Furthermore, subliminally inducing perceptual biases in numerical-magnitude allocation can actively drive prosocial choices in the corresponding direction. Our findings provide evidence for numerical influences on decision making during performance of the dictator game. Accordingly, without the implementation of an adequate control for numerical influences, the dictator game and other tasks with an inherent numerical component (i.e., ultimatum game) should be employed with caution in the assessment of human behavior. Copyright © 2017 the American Physiological Society.
Entropy production rate as a criterion for inconsistency in decision theory
NASA Astrophysics Data System (ADS)
Dixit, Purushottam D.
2018-05-01
Individual and group decisions are complex, often involving choosing an apt alternative from a multitude of options. Evaluating pairwise comparisons breaks down such complex decision problems into tractable ones. Pairwise comparison matrices (PCMs) are regularly used to solve multiple-criteria decision-making problems, for example, using Saaty’s analytic hierarchy process (AHP) framework. However, there are two significant drawbacks of using PCMs. First, humans evaluate PCMs in an inconsistent manner. Second, not all entries of a large PCM can be reliably filled by human decision makers. We address these two issues by first establishing a novel connection between PCMs and time-irreversible Markov processes. Specifically, we show that every PCM induces a family of dissipative maximum path entropy random walks (MERW) over the set of alternatives. We show that only ‘consistent’ PCMs correspond to detailed balanced MERWs. We identify the non-equilibrium entropy production in the induced MERWs as a metric of inconsistency of the underlying PCMs. Notably, the entropy production satisfies all of the recently laid out criteria for reasonable consistency indices. We also propose an approach to use incompletely filled PCMs in AHP. Potential future avenues are discussed as well.
Clinical decision-making: heuristics and cognitive biases for the ophthalmologist.
Hussain, Ahsen; Oestreicher, James
Diagnostic errors have a significant impact on health care outcomes and patient care. The underlying causes and development of diagnostic error are complex with flaws in health care systems, as well as human error, playing a role. Cognitive biases and a failure of decision-making shortcuts (heuristics) are human factors that can compromise the diagnostic process. We describe these mechanisms, their role with the clinician, and provide clinical scenarios to highlight the various points at which biases may emerge. We discuss strategies to modify the development and influence of these processes and the vulnerability of heuristics to provide insight and improve clinical outcomes. Copyright © 2017 Elsevier Inc. All rights reserved.
Conflict Monitoring in Dual Process Theories of Thinking
ERIC Educational Resources Information Center
De Neys, Wim; Glumicic, Tamara
2008-01-01
Popular dual process theories have characterized human thinking as an interplay between an intuitive-heuristic and demanding-analytic reasoning process. Although monitoring the output of the two systems for conflict is crucial to avoid decision making errors there are some widely different views on the efficiency of the process. Kahneman…
Fuzzy, crisp, and human logic in e-commerce marketing data mining
NASA Astrophysics Data System (ADS)
Hearn, Kelda L.; Zhang, Yanqing
2001-03-01
In today's business world there is an abundance of available data and a great need to make good use of it. Many businesses would benefit from examining customer habits and trends and making marketing and product decisions based on that analysis. However, the process of manually examining data and making sound decisions based on that data is time consuming and often impractical. Intelligent systems that can make judgments similar to human judgments are sorely needed. Thus, systems based on fuzzy logic present themselves as an option to be seriously considered. The work described in this paper attempts to make an initial comparison between fuzzy logic and more traditional hard or crisp logic to see which would make a better substitute for human intervention. In this particular case study, customers are classified into categories that indicate how desirable the customer would be as a prospect for marketing. This classification is based on a small set of customer data. The results from these investigations make it clear that fuzzy logic is more able to think for itself and make decisions that more closely match human decision and is therefore significantly closer to human logic than crisp logic.
Neural mechanisms underlying human consensus decision-making
Suzuki, Shinsuke; Adachi, Ryo; Dunne, Simon; Bossaerts, Peter; O'Doherty, John P.
2015-01-01
SUMMARY Consensus building in a group is a hallmark of animal societies, yet little is known about its underlying computational and neural mechanisms. Here, we applied a novel computational framework to behavioral and fMRI data from human participants performing a consensus decision-making task with up to five other participants. We found that participants reached consensus decisions through integrating their own preferences with information about the majority of group-members’ prior choices, as well as inferences about how much each option was stuck to by the other people. These distinct decision variables were separately encoded in distinct brain areas: the ventromedial prefrontal cortex, posterior superior temporal sulcus/temporoparietal junction and intraparietal sulcus, and were integrated in the dorsal anterior cingulate cortex. Our findings provide support for a theoretical account in which collective decisions are made through integrating multiple types of inference about oneself, others and environments, processed in distinct brain modules. PMID:25864634
Neural mechanisms underlying human consensus decision-making.
Suzuki, Shinsuke; Adachi, Ryo; Dunne, Simon; Bossaerts, Peter; O'Doherty, John P
2015-04-22
Consensus building in a group is a hallmark of animal societies, yet little is known about its underlying computational and neural mechanisms. Here, we applied a computational framework to behavioral and fMRI data from human participants performing a consensus decision-making task with up to five other participants. We found that participants reached consensus decisions through integrating their own preferences with information about the majority group members' prior choices, as well as inferences about how much each option was stuck to by the other people. These distinct decision variables were separately encoded in distinct brain areas-the ventromedial prefrontal cortex, posterior superior temporal sulcus/temporoparietal junction, and intraparietal sulcus-and were integrated in the dorsal anterior cingulate cortex. Our findings provide support for a theoretical account in which collective decisions are made through integrating multiple types of inference about oneself, others, and environments, processed in distinct brain modules. Copyright © 2015 Elsevier Inc. All rights reserved.
The neural basis of belief updating and rational decision making
Achtziger, Anja; Hügelschäfer, Sabine; Steinhauser, Marco
2014-01-01
Rational decision making under uncertainty requires forming beliefs that integrate prior and new information through Bayes’ rule. Human decision makers typically deviate from Bayesian updating by either overweighting the prior (conservatism) or overweighting new information (e.g. the representativeness heuristic). We investigated these deviations through measurements of electrocortical activity in the human brain during incentivized probability-updating tasks and found evidence of extremely early commitment to boundedly rational heuristics. Participants who overweight new information display a lower sensibility to conflict detection, captured by an event-related potential (the N2) observed around 260 ms after the presentation of new information. Conservative decision makers (who overweight prior probabilities) make up their mind before new information is presented, as indicated by the lateralized readiness potential in the brain. That is, they do not inhibit the processing of new information but rather immediately rely on the prior for making a decision. PMID:22956673
The neural basis of belief updating and rational decision making.
Achtziger, Anja; Alós-Ferrer, Carlos; Hügelschäfer, Sabine; Steinhauser, Marco
2014-01-01
Rational decision making under uncertainty requires forming beliefs that integrate prior and new information through Bayes' rule. Human decision makers typically deviate from Bayesian updating by either overweighting the prior (conservatism) or overweighting new information (e.g. the representativeness heuristic). We investigated these deviations through measurements of electrocortical activity in the human brain during incentivized probability-updating tasks and found evidence of extremely early commitment to boundedly rational heuristics. Participants who overweight new information display a lower sensibility to conflict detection, captured by an event-related potential (the N2) observed around 260 ms after the presentation of new information. Conservative decision makers (who overweight prior probabilities) make up their mind before new information is presented, as indicated by the lateralized readiness potential in the brain. That is, they do not inhibit the processing of new information but rather immediately rely on the prior for making a decision.
The influence of a bystander agent's beliefs on children's and adults' decision-making process.
Buttelmann, Frances; Buttelmann, David
2017-01-01
The ability to attribute and represent others' mental states (e.g., beliefs; so-called "theory of mind") is essential for participation in human social interaction. Despite a considerable body of research using tasks in which protagonists in the participants' attentional focus held false or true beliefs, the question of automatic belief attribution to bystander agents has received little attention. In the current study, we presented adults and 6-year-olds (N=92) with an implicit computer-based avoidance false-belief task in which participants were asked to place an object into one of three boxes. While doing so, we manipulated the beliefs of an irrelevant human-like or non-human-like bystander agent who was visible on the screen. Importantly, the bystander agent's beliefs were irrelevant for solving the task. Still, children's decision making was significantly influenced by the bystander agent's beliefs even if this was a non-human-like self-propelled object. Such an influence did not become obvious in adults' deliberate decisions but occurred only in their reaction times, which suggests that they also processed the bystander agent's beliefs but were able to suppress the influence of such beliefs on their behavior regulation. The results of a control study (N=53) ruled out low-level explanations and confirmed that self-propelledness of agents is a necessary factor for belief attribution to occur. Thus, not only do humans spontaneously ascribe beliefs to self-propelled bystander agents, but those beliefs even influence meaningful decisions in children. Copyright © 2016 Elsevier Inc. All rights reserved.
Polya's bees: A model of decentralized decision-making.
Golman, Russell; Hagmann, David; Miller, John H
2015-09-01
How do social systems make decisions with no single individual in control? We observe that a variety of natural systems, including colonies of ants and bees and perhaps even neurons in the human brain, make decentralized decisions using common processes involving information search with positive feedback and consensus choice through quorum sensing. We model this process with an urn scheme that runs until hitting a threshold, and we characterize an inherent tradeoff between the speed and the accuracy of a decision. The proposed common mechanism provides a robust and effective means by which a decentralized system can navigate the speed-accuracy tradeoff and make reasonably good, quick decisions in a variety of environments. Additionally, consensus choice exhibits systemic risk aversion even while individuals are idiosyncratically risk-neutral. This too is adaptive. The model illustrates how natural systems make decentralized decisions, illuminating a mechanism that engineers of social and artificial systems could imitate.
Polya’s bees: A model of decentralized decision-making
Golman, Russell; Hagmann, David; Miller, John H.
2015-01-01
How do social systems make decisions with no single individual in control? We observe that a variety of natural systems, including colonies of ants and bees and perhaps even neurons in the human brain, make decentralized decisions using common processes involving information search with positive feedback and consensus choice through quorum sensing. We model this process with an urn scheme that runs until hitting a threshold, and we characterize an inherent tradeoff between the speed and the accuracy of a decision. The proposed common mechanism provides a robust and effective means by which a decentralized system can navigate the speed-accuracy tradeoff and make reasonably good, quick decisions in a variety of environments. Additionally, consensus choice exhibits systemic risk aversion even while individuals are idiosyncratically risk-neutral. This too is adaptive. The model illustrates how natural systems make decentralized decisions, illuminating a mechanism that engineers of social and artificial systems could imitate. PMID:26601255
Stress-induced changes in human decision-making are reversible.
Soares, J M; Sampaio, A; Ferreira, L M; Santos, N C; Marques, F; Palha, J A; Cerqueira, J J; Sousa, N
2012-07-03
Appropriate decision-making relies on the ability to shift between different behavioral strategies according to the context in which decisions are made. A cohort of subjects exposed to prolonged stress, and respective gender- and age-matched controls, performed an instrumental behavioral task to assess their decision-making strategies. The stressed cohort was reevaluated after a 6-week stress-free period. The behavioral analysis was complemented by a functional magnetic resonance imaging (fMRI) study to detect the patterns of activation in corticostriatal networks ruling goal-directed and habitual actions. Using structural MRI, the volumes of the main cortical and subcortical regions implicated in instrumental behavior were determined. Here we show that chronic stress biases decision-making strategies in humans toward habits, as choices of stressed subjects become insensitive to changes in outcome value. Using functional imaging techniques, we demonstrate that prolonged exposure to stress in humans causes an imbalanced activation of the networks that govern decision processes, shifting activation from the associative to the sensorimotor circuits. These functional changes are paralleled by atrophy of the medial prefrontal cortex and the caudate, and by an increase in the volume of the putamina. Importantly, a longitudinal assessment of the stressed individuals showed that both the structural and functional changes triggered by stress are reversible and that decisions become again goal-directed.
Some Ideas on the Microcomputer and the Information/Knowledge Workstation.
ERIC Educational Resources Information Center
Boon, J. A.; Pienaar, H.
1989-01-01
Identifies the optimal goal of knowledge workstations as the harmony of technology and human decision-making behaviors. Two types of decision-making processes are described and the application of each type to experimental and/or operational situations is discussed. Suggestions for technical solutions to machine-user interfaces are then offered.…
ERIC Educational Resources Information Center
Wen, Lei; Hao, Qian; Bu, Danlu
2015-01-01
Based on the theory of planned behavior [Ajzen, I. (1991). "The theory of planned behavior." "Organizational Behavior and Human Decision Processes," 50(2), 179-211], we examine the factors influencing the decisions of accounting students in China concerning the certified public accountant (CPA) designation. Surveying 288…
ERIC Educational Resources Information Center
Florin-Thuma, Beth C.; Boudreau, John W.
1987-01-01
Investigated the frequent but previously untested assertion that utility analysis can improve communication and decision making about human resource management programs by examining a performance feedback intervention in a small fast-food store. Results suggest substantial payoffs from performance feedback, though the store's owner-managers had…
Miller, Matthew James; McGuire, Kerry M.; Feigh, Karen M.
2016-01-01
The design and adoption of decision support systems within complex work domains is a challenge for cognitive systems engineering (CSE) practitioners, particularly at the onset of project development. This article presents an example of applying CSE techniques to derive design requirements compatible with traditional systems engineering to guide decision support system development. Specifically, it demonstrates the requirements derivation process based on cognitive work analysis for a subset of human spaceflight operations known as extravehicular activity. The results are presented in two phases. First, a work domain analysis revealed a comprehensive set of work functions and constraints that exist in the extravehicular activity work domain. Second, a control task analysis was performed on a subset of the work functions identified by the work domain analysis to articulate the translation of subject matter states of knowledge to high-level decision support system requirements. This work emphasizes an incremental requirements specification process as a critical component of CSE analyses to better situate CSE perspectives within the early phases of traditional systems engineering design. PMID:28491008
Miller, Matthew James; McGuire, Kerry M; Feigh, Karen M
2017-06-01
The design and adoption of decision support systems within complex work domains is a challenge for cognitive systems engineering (CSE) practitioners, particularly at the onset of project development. This article presents an example of applying CSE techniques to derive design requirements compatible with traditional systems engineering to guide decision support system development. Specifically, it demonstrates the requirements derivation process based on cognitive work analysis for a subset of human spaceflight operations known as extravehicular activity . The results are presented in two phases. First, a work domain analysis revealed a comprehensive set of work functions and constraints that exist in the extravehicular activity work domain. Second, a control task analysis was performed on a subset of the work functions identified by the work domain analysis to articulate the translation of subject matter states of knowledge to high-level decision support system requirements. This work emphasizes an incremental requirements specification process as a critical component of CSE analyses to better situate CSE perspectives within the early phases of traditional systems engineering design.
The Modeling of Human Intelligence in the Computer as Demonstrated in the Game of DIPLOMAT.
ERIC Educational Resources Information Center
Collins, James Edward; Paulsen, Thomas Dean
An attempt was made to develop human-like behavior in the computer. A theory of the human learning process was described. A computer game was presented which simulated the human capabilities of reasoning and learning. The program was required to make intelligent decisions based on past experiences and critical analysis of the present situation.…
Collective decision-making in microbes
Ross-Gillespie, Adin; Kümmerli, Rolf
2014-01-01
Microbes are intensely social organisms that routinely cooperate and coordinate their activities to express elaborate population level phenotypes. Such coordination requires a process of collective decision-making, in which individuals detect and collate information not only from their physical environment, but also from their social environment, in order to arrive at an appropriately calibrated response. Here, we present a conceptual overview of collective decision-making as it applies to all group-living organisms; we introduce key concepts and principles developed in the context of animal and human group decisions; and we discuss, with appropriate examples, the applicability of each of these concepts in microbial contexts. In particular, we discuss the roles of information pooling, control skew, speed vs. accuracy trade-offs, local feedbacks, quorum thresholds, conflicts of interest, and the reliability of social information. We conclude that collective decision-making in microbes shares many features with collective decision-making in higher taxa, and we call for greater integration between this fledgling field and other allied areas of research, including in the humanities and the physical sciences. PMID:24624121
Balancing Information Analysis and Decision Value: A Model to Exploit the Decision Process
2011-12-01
technical intelli- gence e.g. signals and sensors (SIGINT and MASINT), imagery (!MINT), as well and human and open source intelligence (HUMINT and OSINT ...Clark 2006). The ability to capture large amounts of da- ta and the plenitude of modem intelligence information sources provides a rich cache of...many tech- niques for managing information collected and derived from these sources , the exploitation of intelligence assets for decision-making
The design of aircraft using the decision support problem technique
NASA Technical Reports Server (NTRS)
Mistree, Farrokh; Marinopoulos, Stergios; Jackson, David M.; Shupe, Jon A.
1988-01-01
The Decision Support Problem Technique for unified design, manufacturing and maintenance is being developed at the Systems Design Laboratory at the University of Houston. This involves the development of a domain-independent method (and the associated software) that can be used to process domain-dependent information and thereby provide support for human judgment. In a computer assisted environment, this support is provided in the form of optimal solutions to Decision Support Problems.
Dual Processing Model for Medical Decision-Making: An Extension to Diagnostic Testing
Tsalatsanis, Athanasios; Hozo, Iztok; Kumar, Ambuj; Djulbegovic, Benjamin
2015-01-01
Dual Processing Theories (DPT) assume that human cognition is governed by two distinct types of processes typically referred to as type 1 (intuitive) and type 2 (deliberative). Based on DPT we have derived a Dual Processing Model (DPM) to describe and explain therapeutic medical decision-making. The DPM model indicates that doctors decide to treat when treatment benefits outweigh its harms, which occurs when the probability of the disease is greater than the so called “threshold probability” at which treatment benefits are equal to treatment harms. Here we extend our work to include a wider class of decision problems that involve diagnostic testing. We illustrate applicability of the proposed model in a typical clinical scenario considering the management of a patient with prostate cancer. To that end, we calculate and compare two types of decision-thresholds: one that adheres to expected utility theory (EUT) and the second according to DPM. Our results showed that the decisions to administer a diagnostic test could be better explained using the DPM threshold. This is because such decisions depend on objective evidence of test/treatment benefits and harms as well as type 1 cognition of benefits and harms, which are not considered under EUT. Given that type 1 processes are unique to each decision-maker, this means that the DPM threshold will vary among different individuals. We also showed that when type 1 processes exclusively dominate decisions, ordering a diagnostic test does not affect a decision; the decision is based on the assessment of benefits and harms of treatment. These findings could explain variations in the treatment and diagnostic patterns documented in today’s clinical practice. PMID:26244571
Dual Processing Model for Medical Decision-Making: An Extension to Diagnostic Testing.
Tsalatsanis, Athanasios; Hozo, Iztok; Kumar, Ambuj; Djulbegovic, Benjamin
2015-01-01
Dual Processing Theories (DPT) assume that human cognition is governed by two distinct types of processes typically referred to as type 1 (intuitive) and type 2 (deliberative). Based on DPT we have derived a Dual Processing Model (DPM) to describe and explain therapeutic medical decision-making. The DPM model indicates that doctors decide to treat when treatment benefits outweigh its harms, which occurs when the probability of the disease is greater than the so called "threshold probability" at which treatment benefits are equal to treatment harms. Here we extend our work to include a wider class of decision problems that involve diagnostic testing. We illustrate applicability of the proposed model in a typical clinical scenario considering the management of a patient with prostate cancer. To that end, we calculate and compare two types of decision-thresholds: one that adheres to expected utility theory (EUT) and the second according to DPM. Our results showed that the decisions to administer a diagnostic test could be better explained using the DPM threshold. This is because such decisions depend on objective evidence of test/treatment benefits and harms as well as type 1 cognition of benefits and harms, which are not considered under EUT. Given that type 1 processes are unique to each decision-maker, this means that the DPM threshold will vary among different individuals. We also showed that when type 1 processes exclusively dominate decisions, ordering a diagnostic test does not affect a decision; the decision is based on the assessment of benefits and harms of treatment. These findings could explain variations in the treatment and diagnostic patterns documented in today's clinical practice.
Application of a computational decision model to examine acute drug effects on human risk taking.
Lane, Scott D; Yechiam, Eldad; Busemeyer, Jerome R
2006-05-01
In 3 previous experiments, high doses of alcohol, marijuana, and alprazolam acutely increased risky decision making by adult humans in a 2-choice (risky vs. nonrisky) laboratory task. In this study, a computational modeling analysis known as the expectancy valence model (J. R. Busemeyer & J. C. Stout, 2002) was applied to individual-participant data from these studies, for the highest administered dose of all 3 drugs and corresponding placebo doses, to determine changes in decision-making processes that may be uniquely engendered by each drug. The model includes 3 parameters: responsiveness to rewards and losses (valence or motivation); the rate of updating expectancies about the value of risky alternatives (learning/memory); and the consistency with which trial-by-trial choices match expected outcomes (sensitivity). Parameter estimates revealed 3 key outcomes: Alcohol increased responsiveness to risky rewards and decreased responsiveness to risky losses (motivation) but did not alter expectancy updating (learning/memory); both marijuana and alprazolam produced increases in risk taking that were related to learning/memory but not motivation; and alcohol and marijuana (but not alprazolam) produced more random response patterns that were less consistently related to expected outcomes on the 2 choices. No significant main effects of gender or dose by gender interactions were obtained, but 2 dose by gender interactions approached significance. These outcomes underscore the utility of using a computational modeling approach to deconstruct decision-making processes and thus better understand drug effects on risky decision making in humans.
Laran, Juliano
2010-01-01
Two important forces in human behavior are action and inaction. Although action and inaction are commonly associated with the presence and the absence of behavioral activity, they can also be represented as information processing goals. Action (inaction) goals influence decision effort and increase satisfaction with environments that are structured to allow for more (less) processing (Studies 1 and 2). This increased satisfaction can transfer to the decision (Study 3) and can increase the intent to perform a decision-congruent behavior (Studies 4 and 6). Finally, the author shows escalation of action and inaction goals when they are not achieved (Study 5) and rebound of the alternative goal when the focal goal is achieved (Study 6).
ZBB--a new skill for the financial manager.
Thompson, G B; Pyhrr, P A
1979-03-01
Zero-based budgeting (ZBB) is a management decision-making tool currently gaining wide acceptance. ZBB is a budgeting approach which is useful for planning, controlling and coordinating financial and human resources. It involves the re-evaluation of all budgeted activities in terms of priorities established by the management. The traditional process of incremental budgeting differs from ZBB in that only the planned changes are evaluated in the former. In incremental budgeting, the base budget is considered authorized and required little attention. The ZBB process focuses on the whol budget. This is accomplished by: (1) identifying decision units; (2) evaluating each decision unit in terms of performance, costs, benefits, and alternate means of accomplishiing the objectives; (3) ranking the decision packages; and (4) preparing a budget for the highest priority decision packages. The effect of the ZBB approach is that new high priority programs may be funded by eliminating or reducing existing lower-priority programs. ZBB is viewed as a logical process which can combine many of the elements of good management.
Use of multicriteria decision analysis to address conservation conflicts.
Davies, A L; Bryce, R; Redpath, S M
2013-10-01
Conservation conflicts are increasing on a global scale and instruments for reconciling competing interests are urgently needed. Multicriteria decision analysis (MCDA) is a structured, decision-support process that can facilitate dialogue between groups with differing interests and incorporate human and environmental dimensions of conflict. MCDA is a structured and transparent method of breaking down complex problems and incorporating multiple objectives. The value of this process for addressing major challenges in conservation conflict management is that MCDA helps in setting realistic goals; entails a transparent decision-making process; and addresses mistrust, differing world views, cross-scale issues, patchy or contested information, and inflexible legislative tools. Overall we believe MCDA provides a valuable decision-support tool, particularly for increasing awareness of the effects of particular values and choices for working toward negotiated compromise, although an awareness of the effect of methodological choices and the limitations of the method is vital before applying it in conflict situations. © 2013 Society for Conservation Biology.
Using an ecological ethics framework to make decisions about the relocation of wildlife.
McCoy, Earl D; Berry, Kristin
2008-12-01
Relocation is an increasingly prominent conservation tool for a variety of wildlife, but the technique also is controversial, even among conservation practitioners. An organized framework for addressing the moral dilemmas often accompanying conservation actions such as relocation has been lacking. Ecological ethics may provide such a framework and appears to be an important step forward in aiding ecological researchers and biodiversity managers to make difficult moral choices. A specific application of this framework can make the reasoning process more transparent and give more emphasis to the strong sentiments about non-human organisms held by many potential users. Providing an example of the application of the framework may also increase the appeal of the reasoning process to ecological researchers and biodiversity managers. Relocation as a conservation action can be accompanied by a variety of moral dilemmas that reflect the interconnection of values, ethical positions, and conservation decisions. A model that is designed to address moral dilemmas arising from relocation of humans provides/demonstrates/illustrates a possible way to apply the ecological ethics framework and to involve practicing conservationists in the overall decision-making process.
Lin, Zi-Jing; Li, Lin; Cazzell, Mary; Liu, Hanli
2014-08-01
Diffuse optical tomography (DOT) is a variant of functional near infrared spectroscopy and has the capability of mapping or reconstructing three dimensional (3D) hemodynamic changes due to brain activity. Common methods used in DOT image analysis to define brain activation have limitations because the selection of activation period is relatively subjective. General linear model (GLM)-based analysis can overcome this limitation. In this study, we combine the atlas-guided 3D DOT image reconstruction with GLM-based analysis (i.e., voxel-wise GLM analysis) to investigate the brain activity that is associated with risk decision-making processes. Risk decision-making is an important cognitive process and thus is an essential topic in the field of neuroscience. The Balloon Analog Risk Task (BART) is a valid experimental model and has been commonly used to assess human risk-taking actions and tendencies while facing risks. We have used the BART paradigm with a blocked design to investigate brain activations in the prefrontal and frontal cortical areas during decision-making from 37 human participants (22 males and 15 females). Voxel-wise GLM analysis was performed after a human brain atlas template and a depth compensation algorithm were combined to form atlas-guided DOT images. In this work, we wish to demonstrate the excellence of using voxel-wise GLM analysis with DOT to image and study cognitive functions in response to risk decision-making. Results have shown significant hemodynamic changes in the dorsal lateral prefrontal cortex (DLPFC) during the active-choice mode and a different activation pattern between genders; these findings correlate well with published literature in functional magnetic resonance imaging (fMRI) and fNIRS studies. Copyright © 2014 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.
The effect of oxytocin on group formation and strategic thinking in men.
Aydogan, Gökhan; Jobst, Andrea; Loy, Fabian; Dehning, Sandra; Zill, Peter; Müller, Norbert; Kocher, Martin
2018-04-01
Decision-making in groups is a remarkable and decisive element of human societies. Humans are able to organize themselves in groups, engage in collaborative decision-making processes and arrive at a binding agreement, even in the absence of unanimous consent. However, the transfer of decision-making autonomy requires a willingness to deliberately expose oneself to the decisions of others. A lack of trust in the abilities of others or of the underlying decision-making process, i.e. public trust, can lead to a breakdown of organizations in political or economic domains. Recent studies indicate that the biological basis of trust on an individual level is related to Oxytocin, an endogenous neuropeptide and hormone, which is also associated with pro-social behavior and positive conflict resolution. However, little is known about the effects of Oxytocin on the inclination of individuals to form or join groups and to deliberately engage in collaborative decision-making processes. Here, we show that intranasal administration of Oxytocin (n = 60) compared to placebo (n = 60) in males causes an adverse effect on the choice for forming groups in the presence of a competitive environment. In particular, Oxytocin negatively affects the willingness to work collaboratively in a p-Beauty contest game, whereas the effect is most pronounced for participants with relatively high strategic sophistication. Since our data provide initial evidence that Oxytocin has a positive effect on strategic thinking and performance in the p-Beauty contest game, we argue that the adverse effect on group formation might be rooted in an enhanced strategic sophistication of participants treated with Oxytocin. Copyright © 2018 Elsevier Inc. All rights reserved.
Cortical topography of intracortical inhibition influences the speed of decision making.
Wilimzig, Claudia; Ragert, Patrick; Dinse, Hubert R
2012-02-21
The neocortex contains orderly topographic maps; however, their functional role remains controversial. Theoretical studies have suggested a role in minimizing computational costs, whereas empirical studies have focused on spatial localization. Using a tactile multiple-choice reaction time (RT) task before and after the induction of perceptual learning through repetitive sensory stimulation, we extend the framework of cortical topographies by demonstrating that the topographic arrangement of intracortical inhibition contributes to the speed of human perceptual decision-making processes. RTs differ among fingers, displaying an inverted U-shaped function. Simulations using neural fields show the inverted U-shaped RT distribution as an emergent consequence of lateral inhibition. Weakening inhibition through learning shortens RTs, which is modeled through topographically reorganized inhibition. Whereas changes in decision making are often regarded as an outcome of higher cortical areas, our data show that the spatial layout of interaction processes within representational maps contributes to selection and decision-making processes.
Cortical topography of intracortical inhibition influences the speed of decision making
Wilimzig, Claudia; Ragert, Patrick; Dinse, Hubert R.
2012-01-01
The neocortex contains orderly topographic maps; however, their functional role remains controversial. Theoretical studies have suggested a role in minimizing computational costs, whereas empirical studies have focused on spatial localization. Using a tactile multiple-choice reaction time (RT) task before and after the induction of perceptual learning through repetitive sensory stimulation, we extend the framework of cortical topographies by demonstrating that the topographic arrangement of intracortical inhibition contributes to the speed of human perceptual decision-making processes. RTs differ among fingers, displaying an inverted U-shaped function. Simulations using neural fields show the inverted U-shaped RT distribution as an emergent consequence of lateral inhibition. Weakening inhibition through learning shortens RTs, which is modeled through topographically reorganized inhibition. Whereas changes in decision making are often regarded as an outcome of higher cortical areas, our data show that the spatial layout of interaction processes within representational maps contributes to selection and decision-making processes. PMID:22315409
Information processing by networks of quantum decision makers
NASA Astrophysics Data System (ADS)
Yukalov, V. I.; Yukalova, E. P.; Sornette, D.
2018-02-01
We suggest a model of a multi-agent society of decision makers taking decisions being based on two criteria, one is the utility of the prospects and the other is the attractiveness of the considered prospects. The model is the generalization of quantum decision theory, developed earlier for single decision makers realizing one-step decisions, in two principal aspects. First, several decision makers are considered simultaneously, who interact with each other through information exchange. Second, a multistep procedure is treated, when the agents exchange information many times. Several decision makers exchanging information and forming their judgment, using quantum rules, form a kind of a quantum information network, where collective decisions develop in time as a result of information exchange. In addition to characterizing collective decisions that arise in human societies, such networks can describe dynamical processes occurring in artificial quantum intelligence composed of several parts or in a cluster of quantum computers. The practical usage of the theory is illustrated on the dynamic disjunction effect for which three quantitative predictions are made: (i) the probabilistic behavior of decision makers at the initial stage of the process is described; (ii) the decrease of the difference between the initial prospect probabilities and the related utility factors is proved; (iii) the existence of a common consensus after multiple exchange of information is predicted. The predicted numerical values are in very good agreement with empirical data.
Working memory retrieval as a decision process
Pearson, Benjamin; Raškevičius, Julius; Bays, Paul M.; Pertzov, Yoni; Husain, Masud
2014-01-01
Working memory (WM) is a core cognitive process fundamental to human behavior, yet the mechanisms underlying it remain highly controversial. Here we provide a new framework for understanding retrieval of information from WM, conceptualizing it as a decision based on the quality of internal evidence. Recent findings have demonstrated that precision of WM decreases with memory load. If WM retrieval uses a decision process that depends on memory quality, systematic changes in response time distribution should occur as a function of WM precision. We asked participants to view sample arrays and, after a delay, report the direction of change in location or orientation of a probe. As WM precision deteriorated with increasing memory load, retrieval time increased systematically. Crucially, the shape of reaction time distributions was consistent with a linear accumulator decision process. Varying either task relevance of items or maintenance duration influenced memory precision, with corresponding shifts in retrieval time. These results provide strong support for a decision-making account of WM retrieval based on noisy storage of items. Furthermore, they show that encoding, maintenance, and retrieval in WM need not be considered as separate processes, but may instead be conceptually unified as operations on the same noise-limited, neural representation. PMID:24492597
Working memory retrieval as a decision process.
Pearson, Benjamin; Raskevicius, Julius; Bays, Paul M; Pertzov, Yoni; Husain, Masud
2014-02-03
Working memory (WM) is a core cognitive process fundamental to human behavior, yet the mechanisms underlying it remain highly controversial. Here we provide a new framework for understanding retrieval of information from WM, conceptualizing it as a decision based on the quality of internal evidence. Recent findings have demonstrated that precision of WM decreases with memory load. If WM retrieval uses a decision process that depends on memory quality, systematic changes in response time distribution should occur as a function of WM precision. We asked participants to view sample arrays and, after a delay, report the direction of change in location or orientation of a probe. As WM precision deteriorated with increasing memory load, retrieval time increased systematically. Crucially, the shape of reaction time distributions was consistent with a linear accumulator decision process. Varying either task relevance of items or maintenance duration influenced memory precision, with corresponding shifts in retrieval time. These results provide strong support for a decision-making account of WM retrieval based on noisy storage of items. Furthermore, they show that encoding, maintenance, and retrieval in WM need not be considered as separate processes, but may instead be conceptually unified as operations on the same noise-limited, neural representation.
Uncertainty and equipoise: at interplay between epistemology, decision making and ethics.
Djulbegovic, Benjamin
2011-10-01
In recent years, various authors have proposed that the concept of equipoise be abandoned because it conflates the practice of clinical care with clinical research. At the same time, the equipoise opponents acknowledge the necessity of clinical research if there are unresolved uncertainties about the effects of proposed healthcare interventions. As equipoise represents just 1 measure of uncertainty, proposals to abandon equipoise while maintaining a requirement for addressing uncertainties are contradictory and ultimately not valid. As acknowledgment and articulation of uncertainties represent key scientific and moral requirements for human experimentation, the concept of equipoise remains the most useful framework to link the theory of human experimentation with the theory of rational choice. In this article, I show how uncertainty (equipoise) is at the intersection between epistemology, decision making and ethics of clinical research. In particular, I show how our formulation of responses to uncertainties of hoped-for benefits and unknown harms of testing is a function of the way humans cognitively process information. This approach is based on the view that considerations of ethics and rationality cannot be separated. I analyze the response to uncertainties as it relates to the dual-processing theory, which postulates that rational approach to (clinical research) decision making depends both on analytical, deliberative processes embodied in scientific method (system II), and good human intuition (system I). Ultimately, our choices can only become wiser if we understand a close and intertwined relationship between irreducible uncertainty, inevitable errors and unavoidable injustice.
Uncertainty and Equipoise: At Interplay Between Epistemology, Decision-Making and Ethics
Djulbegovic, Benjamin
2011-01-01
In recent years, various authors have proposed that the concept of equipoise be abandoned since it conflates the practice of clinical care with clinical research. At the same time, the equipoise opponents acknowledge the necessity of clinical research if there are unresolved uncertainties about the effects of proposed healthcare interventions. Since equipoise represents just one measure of uncertainty, proposals to abandon equipoise while maintaining a requirement for addressing uncertainties are contradictory and ultimately not valid. As acknowledgment and articulation of uncertainties represent key scientific and moral requirements for human experimentation, the concept of equipoise remains the most useful framework to link the theory of human experimentation with the theory of rational choice. In this paper, I show how uncertainty (equipoise) is at the intersection between epistemology, decision-making and ethics of clinical research. In particular, I show how our formulation of responses to uncertainties of hoped-for benefits and unknown harms of testing is a function of the way humans cognitively process information. This approach is based on the view that considerations of ethics and rationality cannot be separated. I analyze the response to uncertainties as it relates to the dual-processing theory, which postulates that rational approach to (clinical research) decision-making depends both on analytical, deliberative processes embodied in scientific method (system II) and “good” human intuition (system I). Ultimately, our choices can only become wiser if we understand a close and intertwined relationship between irreducible uncertainty, inevitable errors, and unavoidable injustice. PMID:21817885
Servant, Mathieu; White, Corey; Montagnini, Anna; Burle, Borís
2015-07-15
Most decisions that we make build upon multiple streams of sensory evidence and control mechanisms are needed to filter out irrelevant information. Sequential sampling models of perceptual decision making have recently been enriched by attentional mechanisms that weight sensory evidence in a dynamic and goal-directed way. However, the framework retains the longstanding hypothesis that motor activity is engaged only once a decision threshold is reached. To probe latent assumptions of these models, neurophysiological indices are needed. Therefore, we collected behavioral and EMG data in the flanker task, a standard paradigm to investigate decisions about relevance. Although the models captured response time distributions and accuracy data, EMG analyses of response agonist muscles challenged the assumption of independence between decision and motor processes. Those analyses revealed covert incorrect EMG activity ("partial error") in a fraction of trials in which the correct response was finally given, providing intermediate states of evidence accumulation and response activation at the single-trial level. We extended the models by allowing motor activity to occur before a commitment to a choice and demonstrated that the proposed framework captured the rate, latency, and EMG surface of partial errors, along with the speed of the correction process. In return, EMG data provided strong constraints to discriminate between competing models that made similar behavioral predictions. Our study opens new theoretical and methodological avenues for understanding the links among decision making, cognitive control, and motor execution in humans. Sequential sampling models of perceptual decision making assume that sensory information is accumulated until a criterion quantity of evidence is obtained, from where the decision terminates in a choice and motor activity is engaged. The very existence of covert incorrect EMG activity ("partial error") during the evidence accumulation process challenges this longstanding assumption. In the present work, we use partial errors to better constrain sequential sampling models at the single-trial level. Copyright © 2015 the authors 0270-6474/15/3510371-15$15.00/0.
Dowie, J.
2001-01-01
Most references to "leadership" and "learning" as sources of quality improvement in medical care reflect an implicit commitment to the decision technology of "clinical judgement". All attempts to sustain this waning decision technology by clinical guidelines, care pathways, "evidence based practice", problem based curricula, and other stratagems only increase the gap between what is expected of doctors in today's clinical situation and what is humanly possible, hence the morale, stress, and health problems they are increasingly experiencing. Clinical guidance programmes based on decision analysis represent the coming decision technology, and proactive adaptation will produce independent doctors who can deliver excellent evidence based and preference driven care while concentrating on the human aspects of the therapeutic relation, having been relieved of the unbearable burdens of knowledge and information processing currently laid on them. History is full of examples of the incumbents of dominant technologies preferring to die than to adapt, and medicine needs both learning and leadership if it is to avoid repeating this mistake. Key Words: decision technology; clinical guidance programmes; decision analysis PMID:11700381
Domingo, José L; Nadal, Martí
2017-07-01
In October 2015, the International Agency for Research on Cancer (IARC) issued a press release on the results of the evaluation of the carcinogenicity of red and processed meat. Based on the accumulated scientific literature, the consumption of red meat was classified as "probably carcinogenic to humans" and processed meat as "carcinogenic to humans". Given the importance of this topic, this review was aimed at revising the current state-of-the-art on the carcinogenicity of red and processed meat, some time after the IARC decision. Some new epidemiological studies and new reviews clearly supporting the IARC decision have been published during these months. However, a number of gaps still exist. It is basic to establish the mechanisms leading to the increased risk of colorectal cancer (CRC) and other cancers arising from red and processed meat consumption. Another important pending issue is to establish the role of known/suspected carcinogens contained in uncooked or unprocessed meats, as well as the influence of cooking. Finally, it would be highly recommended to conduct new epidemiological studies to elucidate whether the consumption of white meat, such as pork and/or poultry, are -positively or inversely-associated with an increased risk of CRC and other types of cancer. Copyright © 2017 Elsevier Ltd. All rights reserved.
Rogers, Robert D
2011-01-01
Neurophysiological experiments in primates, alongside neuropsychological and functional magnetic resonance investigations in humans, have significantly enhanced our understanding of the neural architecture of decision making. In this review, I consider the more limited database of experiments that have investigated how dopamine and serotonin activity influences the choices of human adults. These include those experiments that have involved the administration of drugs to healthy controls, experiments that have tested genotypic influences upon dopamine and serotonin function, and, finally, some of those experiments that have examined the effects of drugs on the decision making of clinical samples. Pharmacological experiments in humans are few in number and face considerable methodological challenges in terms of drug specificity, uncertainties about pre- vs post-synaptic modes of action, and interactions with baseline cognitive performance. However, the available data are broadly consistent with current computational models of dopamine function in decision making and highlight the dissociable roles of dopamine receptor systems in the learning about outcomes that underpins value-based decision making. Moreover, genotypic influences on (interacting) prefrontal and striatal dopamine activity are associated with changes in choice behavior that might be relevant to understanding exploratory behaviors and vulnerability to addictive disorders. Manipulations of serotonin in laboratory tests of decision making in human participants have provided less consistent results, but the information gathered to date indicates a role for serotonin in learning about bad decision outcomes, non-normative aspects of risk-seeking behavior, and social choices involving affiliation and notions of fairness. Finally, I suggest that the role played by serotonin in the regulation of cognitive biases, and representation of context in learning, point toward a role in the cortically mediated cognitive appraisal of reinforcers when selecting between actions, potentially accounting for its influence upon the processing salient aversive outcomes and social choice.
Software for rapid prototyping in the pharmaceutical and biotechnology industries.
Kappler, Michael A
2008-05-01
The automation of drug discovery methods continues to develop, especially techniques that process information, represent workflow and facilitate decision-making. The magnitude of data and the plethora of questions in pharmaceutical and biotechnology research give rise to the need for rapid prototyping software. This review describes the advantages and disadvantages of three solutions: Competitive Workflow, Taverna and Pipeline Pilot. Each of these systems processes large amounts of data, integrates diverse systems and assists novice programmers and human experts in critical decision-making steps.
NASA Astrophysics Data System (ADS)
Murphy, Elizabeth Drummond
As advances in technology are applied in complex, semi-automated domains, human controllers are distanced from the controlled process. This physical and psychological distance may both facilitate and degrade human performance. To investigate cognitive issues in spacecraft ground-control operations, the present experimental research was undertaken. The primary issue concerned the ability of operations analysts who do not monitor operations to make timely, accurate decisions when autonomous software calls for human help. Another key issue involved the potential effects of spatial-visualization ability (SVA) in environments that present data in graphical formats. Hypotheses were derived largely from previous findings and predictions in the literature. Undergraduate psychology students were assigned at random to a monitoring condition or an on-call condition in a scaled environment. The experimental task required subjects to decide on the veracity of a problem diagnosis delivered by a software process on-board a simulated spacecraft. To support decision-making, tabular and graphical data displays presented information on system status. A level of software confidence in the problem diagnosis was displayed, and subjects reported their own level of confidence in their decisions. Contrary to expectations, the performance of on-call subjects did not differ significantly from that of continuous monitors. Analysis yielded a significant interaction of sex and condition: Females in the on-call condition had the lowest mean accuracy. Results included a preference for bar charts over line graphs and faster performance with tables than with line graphs. A significant correlation was found between subjective confidence and decision accuracy. SVA was found to be predictive of accuracy but not speed; and SVA was found to be a stronger predictor of performance for males than for females. Low-SVA subjects reported that they relied more on software confidence than did medium- or high-SVA subjects. These and other findings have implications for the design of user interfaces to support human decision-making in on-call situations and to accommodate low-SVA users.
1992-07-10
a way ahead for future work to explore the cognitive nature of the whole command and control task and a decision support environment . Introduction...existing inferior approach. Second, the nature of how tasks are performed changes in a dynamic environment . For example, the decision-making process...the system must be designed to perform in its expected operational environment . It includes tasks performed by the aircraft, its systems, and each of
Modeling Common-Sense Decisions in Artificial Intelligence
NASA Technical Reports Server (NTRS)
Zak, Michail
2010-01-01
A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.
A cortical network model of cognitive and emotional influences in human decision making.
Nazir, Azadeh Hassannejad; Liljenström, Hans
2015-10-01
Decision making (DM)(2) is a complex process that appears to involve several brain structures. In particular, amygdala, orbitofrontal cortex (OFC) and lateral prefrontal cortex (LPFC) seem to be essential in human decision making, where both emotional and cognitive aspects are taken into account. In this paper, we present a computational network model representing the neural information processing of DM, from perception to behavior. We model the population dynamics of the three neural structures (amygdala, OFC and LPFC), as well as their interaction. In our model, the neurodynamic activity of amygdala and OFC represents the neural correlates of secondary emotion, while the activity of certain neural populations in OFC alone represents the outcome expectancy of different options. The cognitive/rational aspect of DM is associated with LPFC. Our model is intended to give insights on the emotional and cognitive processes involved in DM under various internal and external contexts. Different options for actions are represented by the oscillatory activity of cell assemblies, which may change due to experience and learning. Knowledge and experience of the outcome of our decisions and actions can eventually result in changes in our neural structures, attitudes and behaviors. Simulation results may have implications for how we make decisions for our individual actions, as well as for societal choices, where we take examples from transport and its impact on CO2 emissions and climate change. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Interoception drives increased rational decision-making in meditators playing the ultimatum game.
Kirk, Ulrich; Downar, Jonathan; Montague, P Read
2011-01-01
Human decision-making is often conceptualized as a competition between cognitive and emotional processes in the brain. Deviations from rational processes are believed to derive from inclusion of emotional factors in decision-making. Here, we investigate whether experienced Buddhist meditators are better equipped to regulate emotional processes compared with controls during economic decision-making in the Ultimatum Game. We show that meditators accept unfair offers on more than half of the trials, whereas controls only accept unfair offers on one-quarter of the trials. By applying fMRI we show that controls recruit the anterior insula during unfair offers. Such responses are powerful predictors of rejecting offers in social interaction. By contrast, meditators display attenuated activity in high-level emotional representations of the anterior insula and increased activity in the low-level interoceptive representations of the posterior insula. In addition we show that a subset of control participants who play rationally (i.e., accepts >85% unfair offers) recruits the dorsolateral prefrontal cortex presumably reflecting increased cognitive demands, whereas rational meditators by contrast display elevated activity in the somatosensory cortex and posterior superior temporal cortex. In summary, when assessing unfairness in the Ultimatum Game, meditators activate a different network of brain areas compared with controls enabling them to uncouple negative emotional reactions from their behavior. These findings highlight the clinically and socially important possibility that sustained training in mindfulness meditation may impact distinct domains of human decision-making.
5 CFR 9701.222 - Reconsideration of classification decisions.
Code of Federal Regulations, 2012 CFR
2012-01-01
... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...
5 CFR 9701.222 - Reconsideration of classification decisions.
Code of Federal Regulations, 2013 CFR
2013-01-01
... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...
5 CFR 9701.222 - Reconsideration of classification decisions.
Code of Federal Regulations, 2014 CFR
2014-01-01
... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...
5 CFR 9701.222 - Reconsideration of classification decisions.
Code of Federal Regulations, 2011 CFR
2011-01-01
... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...
Using Multiattribute Utility Theory as a Priority-Setting Tool in Human Services Planning.
ERIC Educational Resources Information Center
Camasso, Michael J.; Dick, Janet
1993-01-01
The feasibility of applying multiattribute utility theory to the needs assessment and priority-setting activities of human services planning councils was studied in Essex County (New Jersey). Decision-making and information filtering processes are explored in the context of community planning. (SLD)
Dhukaram, Anandhi Vivekanandan; Baber, Chris
2015-06-01
Patients make various healthcare decisions on a daily basis. Such day-to-day decision making can have significant consequences on their own health, treatment, care, and costs. While decision aids (DAs) provide effective support in enhancing patient's decision making, to date there have been few studies examining patient's decision making process or exploring how the understanding of such decision processes can aid in extracting requirements for the design of DAs. This paper applies Cognitive Work Analysis (CWA) to analyse patient's decision making in order to inform requirements for supporting self-care decision making. This study uses focus groups to elicit information from elderly cardiovascular disease (CVD) patients concerning a range of decision situations they face on a daily basis. Specifically, the focus groups addressed issues related to the decision making of CVD in terms of medication compliance, pain, diet and exercise. The results of these focus groups are used to develop high level views using CWA. CWA framework decomposes the complex decision making problem to inform three approaches to DA design: one design based on high level requirements; one based on a normative model of decision-making for patients; and the third based on a range of heuristics that patients seem to use. CWA helps in extracting and synthesising decision making from different perspectives: decision processes, work organisation, patient competencies and strategies used in decision making. As decision making can be influenced by human behaviour like skills, rules and knowledge, it is argued that patients require support to different types of decision making. This paper also provides insights for designers in using CWA framework for the design of effective DAs to support patients in self-management. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Human perceptual decision making: disentangling task onset and stimulus onset.
Cardoso-Leite, Pedro; Waszak, Florian; Lepsien, Jöran
2014-07-01
The left dorsolateral prefrontal cortex (ldlPFC) has been highlighted as a key actor in human perceptual decision-making (PDM): It is theorized to support decision-formation independently of stimulus type or motor response. PDM studies however generally confound stimulus onset and task onset: when the to-be-recognized stimulus is presented, subjects know that a stimulus is shown and can set up processing resources-even when they do not know which stimulus is shown. We hypothesized that the ldlPFC might be involved in task preparation rather than decision-formation. To test this, we asked participants to report whether sequences of noisy images contained a face or a house within an experimental design that decorrelates stimulus and task onset. Decision-related processes should yield a sustained response during the task, whereas preparation-related areas should yield transient responses at its beginning. The results show that the brain activation pattern at task onset is strikingly similar to that observed in previous PDM studies. In particular, they contradict the idea that ldlPFC forms an abstract decision and suggest instead that its activation reflects preparation for the upcoming task. We further investigated the role of the fusiform face areas and parahippocampal place areas which are thought to be face and house detectors, respectively, that feed their signals to higher level decision areas. The response patterns within these areas suggest that this interpretation is unlikely and that the decisions about the presence of a face or a house in a noisy image might instead already be computed within these areas without requiring higher-order areas. Copyright © 2013 Wiley Periodicals, Inc.
Berendt, Bettina; Preibusch, Sören
2017-06-01
"Big Data" and data-mined inferences are affecting more and more of our lives, and concerns about their possible discriminatory effects are growing. Methods for discrimination-aware data mining and fairness-aware data mining aim at keeping decision processes supported by information technology free from unjust grounds. However, these formal approaches alone are not sufficient to solve the problem. In the present article, we describe reasons why discrimination with data can and typically does arise through the combined effects of human and machine-based reasoning, and argue that this requires a deeper understanding of the human side of decision-making with data mining. We describe results from a large-scale human-subjects experiment that investigated such decision-making, analyzing the reasoning that participants reported during their task to assess whether a loan request should or would be granted. We derive data protection by design strategies for making decision-making discrimination-aware in an accountable way, grounding these requirements in the accountability principle of the European Union General Data Protection Regulation, and outline how their implementations can integrate algorithmic, behavioral, and user interface factors.
Predicting explorative motor learning using decision-making and motor noise.
Chen, Xiuli; Mohr, Kieran; Galea, Joseph M
2017-04-01
A fundamental problem faced by humans is learning to select motor actions based on noisy sensory information and incomplete knowledge of the world. Recently, a number of authors have asked whether this type of motor learning problem might be very similar to a range of higher-level decision-making problems. If so, participant behaviour on a high-level decision-making task could be predictive of their performance during a motor learning task. To investigate this question, we studied performance during an explorative motor learning task and a decision-making task which had a similar underlying structure with the exception that it was not subject to motor (execution) noise. We also collected an independent measurement of each participant's level of motor noise. Our analysis showed that explorative motor learning and decision-making could be modelled as the (approximately) optimal solution to a Partially Observable Markov Decision Process bounded by noisy neural information processing. The model was able to predict participant performance in motor learning by using parameters estimated from the decision-making task and the separate motor noise measurement. This suggests that explorative motor learning can be formalised as a sequential decision-making process that is adjusted for motor noise, and raises interesting questions regarding the neural origin of explorative motor learning.
Predicting explorative motor learning using decision-making and motor noise
Galea, Joseph M.
2017-01-01
A fundamental problem faced by humans is learning to select motor actions based on noisy sensory information and incomplete knowledge of the world. Recently, a number of authors have asked whether this type of motor learning problem might be very similar to a range of higher-level decision-making problems. If so, participant behaviour on a high-level decision-making task could be predictive of their performance during a motor learning task. To investigate this question, we studied performance during an explorative motor learning task and a decision-making task which had a similar underlying structure with the exception that it was not subject to motor (execution) noise. We also collected an independent measurement of each participant’s level of motor noise. Our analysis showed that explorative motor learning and decision-making could be modelled as the (approximately) optimal solution to a Partially Observable Markov Decision Process bounded by noisy neural information processing. The model was able to predict participant performance in motor learning by using parameters estimated from the decision-making task and the separate motor noise measurement. This suggests that explorative motor learning can be formalised as a sequential decision-making process that is adjusted for motor noise, and raises interesting questions regarding the neural origin of explorative motor learning. PMID:28437451
van den Bos, Ruud; Davies, William; Dellu-Hagedorn, Francoise; Goudriaan, Anna E; Granon, Sylvie; Homberg, Judith; Rivalan, Marion; Swendsen, Joel; Adriani, Walter
2013-12-01
Decision-making plays a pivotal role in daily life as impairments in processes underlying decision-making often lead to an inability to make profitable long-term decisions. As a case in point, pathological gamblers continue gambling despite the fact that this disrupts their personal, professional or financial life. The prevalence of pathological gambling will likely increase in the coming years due to expanding possibilities of on-line gambling through the Internet and increasing liberal attitudes towards gambling. It therefore represents a growing concern for society. Both human and animal studies rapidly advance our knowledge on brain-behaviour processes relevant for understanding normal and pathological gambling behaviour. Here, we review in humans and animals three features of pathological gambling which hitherto have received relatively little attention: (1) sex differences in (the development of) pathological gambling, (2) adolescence as a (putative) sensitive period for (developing) pathological gambling and (3) avenues for improving ecological validity of research tools. Based on these issues we also discuss how research in humans and animals may be brought in line to maximize translational research opportunities. Copyright © 2013 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Hollmann, Maurice; Mönch, Tobias; Müller, Charles; Bernarding, Johannes
2009-02-01
A major field in cognitive neuroscience investigates neuronal correlates of human decision-making processes [1, 2]. Is it possible to predict a decision before it is actually revealed by the volunteer? In the presented manuscript we use a standard paradigm from economic behavioral research that proved emotional influences on human decision making: the Ultimatum Game (UG). In the UG, two players have the opportunity to split a sum of money. One player is deemed the proposer and the other, the responder. The proposer makes an offer as to how this money should be split between the two. The second player can either accept or reject this offer. If it is accepted, the money is split as proposed. If rejected, then neither player receives anything. In the presented study a real-time fMRI system was used to derive the brain activation of the responder. Using a Relevance-Vector-Machine classifier it was possible to predict if the responder will accept or reject an offer. The classification result was presented to the operator 1-2 seconds before the volunteer pressed a button to convey his decision. The classification accuracy reached about 70% averaged over six subjects.
Decision Support System for Determining Scholarship Selection using an Analytical Hierarchy Process
NASA Astrophysics Data System (ADS)
Puspitasari, T. D.; Sari, E. O.; Destarianto, P.; Riskiawan, H. Y.
2018-01-01
Decision Support System is a computer program application that analyzes data and presents it so that users can make decision more easily. Determining Scholarship Selection study case in Senior High School in east Java wasn’t easy. It needed application to solve the problem, to improve the accuracy of targets for prospective beneficiaries of poor students and to speed up the screening process. This research will build system uses the method of Analytical Hierarchy Process (AHP) is a method that solves a complex and unstructured problem into its group, organizes the groups into a hierarchical order, inputs numerical values instead of human perception in comparing relative and ultimately with a synthesis determined elements that have the highest priority. The accuracy system for this research is 90%.
Cells, circuits, and choices: social influences on perceptual decision making.
Mojzisch, Andreas; Krug, Kristine
2008-12-01
Making decisions is an integral part of everyday life. Social psychologists have demonstrated in many studies that humans' decisions are frequently and strongly influenced by the opinions of others--even in simple perceptual decisions, where, for example, participants have to judge what an image looks like. However, because the effect of other people's opinions on decision making has remained largely unaddressed by the neuroimaging and neurophysiology literature, we are only beginning to understand how social influence is integrated into the decision-making process. We put forward the thesis that by probing the neurophysiology of social influence with perceptual decision-making tasks similar to those used in the seminal work of Asch (1952, 1956), this gap could be remedied. Perceptual paradigms are already widely used to probe neuronal mechanisms of decision making in nonhuman primates. There is also increasing evidence about how nonhuman primates' behavior is influenced by observing conspecifics. The high spatial and temporal resolution of neurophysiological recordings in awake monkeys could provide insight into where and how social influence modulates decision making, and thus should enable us to develop detailed functional models of the neural mechanisms that support the integration of social influence into the decision-making process.
The role of the insula in intuitive expert bug detection in computer code: an fMRI study.
Castelhano, Joao; Duarte, Isabel C; Ferreira, Carlos; Duraes, Joao; Madeira, Henrique; Castelo-Branco, Miguel
2018-05-09
Software programming is a complex and relatively recent human activity, involving the integration of mathematical, recursive thinking and language processing. The neural correlates of this recent human activity are still poorly understood. Error monitoring during this type of task, requiring the integration of language, logical symbol manipulation and other mathematical skills, is particularly challenging. We therefore aimed to investigate the neural correlates of decision-making during source code understanding and mental manipulation in professional participants with high expertise. The present fMRI study directly addressed error monitoring during source code comprehension, expert bug detection and decision-making. We used C code, which triggers the same sort of processing irrespective of the native language of the programmer. We discovered a distinct role for the insula in bug monitoring and detection and a novel connectivity pattern that goes beyond the expected activation pattern evoked by source code understanding in semantic language and mathematical processing regions. Importantly, insula activity levels were critically related to the quality of error detection, involving intuition, as signalled by reported initial bug suspicion, prior to final decision and bug detection. Activity in this salience network (SN) region evoked by bug suspicion was predictive of bug detection precision, suggesting that it encodes the quality of the behavioral evidence. Connectivity analysis provided evidence for top-down circuit "reutilization" stemming from anterior cingulate cortex (BA32), a core region in the SN that evolved for complex error monitoring such as required for this type of recent human activity. Cingulate (BA32) and anterolateral (BA10) frontal regions causally modulated decision processes in the insula, which in turn was related to activity of math processing regions in early parietal cortex. In other words, earlier brain regions used during evolution for other functions seem to be reutilized in a top-down manner for a new complex function, in an analogous manner as described for other cultural creations such as reading and literacy.
Wilson, Robyn S.; Hardisty, David J.; Epanchin-Niell, Rebecca S.; Runge, Michael C.; Cottingham, Kathryn L.; Urban, Dean L.; Maguire, Lynn A.; Hastings, Alan; Mumby, Peter J.; Peters, Debra P.C.
2016-01-01
Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long-term inertia and short-term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management-decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers’ actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time-scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long-term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short-sighted behavior to make it less appealing. Additional application of these tools and long-term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed.
[Ethical and philosophical dimensions of decision-making in public health].
Grémy, F
2008-01-01
Decisions in public health, or in individual health care, are taken by people (individuals or collective) for other people (individuals or collective). Human values, that is to say what is connected to Ethics, should be to the fore, de jure. Too often, under the pretext that they refer to subjectivity, they appear only after very many technical considerations. The latter, in a scientist society, are supposed to deserve a claim to objectivity, this being of course illusory. The author, placing himself in the line of Levinas, Ricoeur, and also of Kant, for whom the "What must I do?" is the most fundamental question any human being has to face, develops four reasons which plead for the pre-eminence of ethics as the foundation of decisions in a policy for public health. 1) He reminds us the intangible values, which are on one side uniqueness and universality of mankind, and on the other side the singularity of the human person. 2) He insists on the ethical wreck which threatens the whole health- and healthcare systems. 3) He sets out some results of modern neurophysiological research (AR Damasio's work), joining an intuition of Aristoteles: the decision making process implies two phases: deliberation the aim of which is to list the different possible actions to undertake, then the choice between those actions. Damasio shows that the lack of emotions inhibits the choice, especially when decision implies human values. 4) Finally, he insists, after E. Morin, on the practical and theoretical difficulties in taking a "good" decision, and on what Morin calls "ecology of action". The results of a decision may completely escape from the decision-makers aims, very often for unexpected social and psychological reasons.
Wilson, Robyn S; Hardisty, David J; Epanchin-Niell, Rebecca S; Runge, Michael C; Cottingham, Kathryn L; Urban, Dean L; Maguire, Lynn A; Hastings, Alan; Mumby, Peter J; Peters, Debra P C
2016-02-01
Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long-term inertia and short-term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management-decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers' actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time-scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long-term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short-sighted behavior to make it less appealing. Additional application of these tools and long-term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed. © 2015 Society for Conservation Biology.
Alterations in choice behavior by manipulations of world model
Green, C. S.; Benson, C.; Kersten, D.; Schrater, P.
2010-01-01
How to compute initially unknown reward values makes up one of the key problems in reinforcement learning theory, with two basic approaches being used. Model-free algorithms rely on the accumulation of substantial amounts of experience to compute the value of actions, whereas in model-based learning, the agent seeks to learn the generative process for outcomes from which the value of actions can be predicted. Here we show that (i) “probability matching”—a consistent example of suboptimal choice behavior seen in humans—occurs in an optimal Bayesian model-based learner using a max decision rule that is initialized with ecologically plausible, but incorrect beliefs about the generative process for outcomes and (ii) human behavior can be strongly and predictably altered by the presence of cues suggestive of various generative processes, despite statistically identical outcome generation. These results suggest human decision making is rational and model based and not consistent with model-free learning. PMID:20805507
Dual processing model of medical decision-making.
Djulbegovic, Benjamin; Hozo, Iztok; Beckstead, Jason; Tsalatsanis, Athanasios; Pauker, Stephen G
2012-09-03
Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. We show that physician's beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker's threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. We have developed the first dual processing model of medical decision-making that has potential to enrich the current medical decision-making field, which is still to the large extent dominated by expected utility theory. The model also provides a platform for reconciling two groups of competing dual processing theories (parallel competitive with default-interventionalist theories).
Lucky Rhythms in Orbitofrontal Cortex Bias Gambling Decisions in Humans
Sacré, Pierre; Kerr, Matthew S. D.; Kahn, Kevin; Gonzalez-Martinez, Jorge; Bulacio, Juan; Park, Hyun-Joo; Johnson, Matthew A.; Thompson, Susan; Jones, Jaes; Chib, Vikram S.; Gale, John T.; Sarma, Sridevi V.
2016-01-01
It is well established that emotions influence our decisions, yet the neural basis of this biasing effect is not well understood. Here we directly recorded local field potentials from the OrbitoFrontal Cortex (OFC) in five human subjects performing a financial decision-making task. We observed a striking increase in gamma-band (36–50 Hz) oscillatory activity that reflected subjects’ decisions to make riskier choices. Additionally, these gamma rhythms were linked back to mismatched expectations or “luck” occurring in past trials. Specifically, when a subject expected to win but lost, the trial was defined as “unlucky” and when the subject expected to lose but won, the trial was defined as “lucky”. Finally, a fading memory model of luck correlated to an objective measure of emotion, heart rate variability. Our findings suggest OFC may play a pivotal role in processing a subject’s internal (emotional) state during financial decision-making, a particularly interesting result in light of the more recent “cognitive map” theory of OFC function. PMID:27830753
Striatal activation reflects urgency in perceptual decision making.
van Maanen, Leendert; Fontanesi, Laura; Hawkins, Guy E; Forstmann, Birte U
2016-10-01
Deciding between multiple courses of action often entails an increasing need to do something as time passes - a sense of urgency. This notion of urgency is not incorporated in standard theories of speeded decision making that assume information is accumulated until a critical fixed threshold is reached. Yet, it is hypothesized in novel theoretical models of decision making. In two experiments, we investigated the behavioral and neural evidence for an "urgency signal" in human perceptual decision making. Experiment 1 found that as the duration of the decision making process increased, participants made a choice based on less evidence for the selected option. Experiment 2 replicated this finding, and additionally found that variability in this effect across participants covaried with activation in the striatum. We conclude that individual differences in susceptibility to urgency are reflected by striatal activation. By dynamically updating a response threshold, the striatum is involved in signaling urgency in humans. Copyright © 2016 Elsevier Inc. All rights reserved.
2015-10-01
capability to meet the task to the standard under the condition, nothing more or less, else the funding is wasted . Also, that funding for the...bin to segregate gaps qualitatively before the gap value model determined preference among gaps within the bins. Computation of a gap’s...for communication, interpretation, or processing by humans or by automatic means (as it pertains to modeling and simulation). Delphi Method -- a
Stamarski, Cailin S; Son Hing, Leanne S
2015-01-01
Gender inequality in organizations is a complex phenomenon that can be seen in organizational structures, processes, and practices. For women, some of the most harmful gender inequalities are enacted within human resources (HRs) practices. This is because HR practices (i.e., policies, decision-making, and their enactment) affect the hiring, training, pay, and promotion of women. We propose a model of gender discrimination in HR that emphasizes the reciprocal nature of gender inequalities within organizations. We suggest that gender discrimination in HR-related decision-making and in the enactment of HR practices stems from gender inequalities in broader organizational structures, processes, and practices. This includes leadership, structure, strategy, culture, organizational climate, as well as HR policies. In addition, organizational decision makers' levels of sexism can affect their likelihood of making gender biased HR-related decisions and/or behaving in a sexist manner while enacting HR practices. Importantly, institutional discrimination in organizational structures, processes, and practices play a pre-eminent role because not only do they affect HR practices, they also provide a socializing context for organizational decision makers' levels of hostile and benevolent sexism. Although we portray gender inequality as a self-reinforcing system that can perpetuate discrimination, important levers for reducing discrimination are identified.
Stamarski, Cailin S.; Son Hing, Leanne S.
2015-01-01
Gender inequality in organizations is a complex phenomenon that can be seen in organizational structures, processes, and practices. For women, some of the most harmful gender inequalities are enacted within human resources (HRs) practices. This is because HR practices (i.e., policies, decision-making, and their enactment) affect the hiring, training, pay, and promotion of women. We propose a model of gender discrimination in HR that emphasizes the reciprocal nature of gender inequalities within organizations. We suggest that gender discrimination in HR-related decision-making and in the enactment of HR practices stems from gender inequalities in broader organizational structures, processes, and practices. This includes leadership, structure, strategy, culture, organizational climate, as well as HR policies. In addition, organizational decision makers’ levels of sexism can affect their likelihood of making gender biased HR-related decisions and/or behaving in a sexist manner while enacting HR practices. Importantly, institutional discrimination in organizational structures, processes, and practices play a pre-eminent role because not only do they affect HR practices, they also provide a socializing context for organizational decision makers’ levels of hostile and benevolent sexism. Although we portray gender inequality as a self-reinforcing system that can perpetuate discrimination, important levers for reducing discrimination are identified. PMID:26441775
The value of foresight: how prospection affects decision-making.
Pezzulo, Giovanni; Rigoli, Francesco
2011-01-01
Traditional theories of decision-making assume that utilities are based on the intrinsic value of outcomes; in turn, these values depend on associations between expected outcomes and the current motivational state of the decision-maker. This view disregards the fact that humans (and possibly other animals) have prospection abilities, which permit anticipating future mental processes and motivational and emotional states. For instance, we can evaluate future outcomes in light of the motivational state we expect to have when the outcome is collected, not (only) when we make a decision. Consequently, we can plan for the future and choose to store food to be consumed when we expect to be hungry, not immediately. Furthermore, similarly to any expected outcome, we can assign a value to our anticipated mental processes and emotions. It has been reported that (in some circumstances) human subjects prefer to receive an unavoidable punishment immediately, probably because they are anticipating the dread associated with the time spent waiting for the punishment. This article offers a formal framework to guide neuroeconomic research on how prospection affects decision-making. The model has two characteristics. First, it uses model-based Bayesian inference to describe anticipation of cognitive and motivational processes. Second, the utility-maximization process considers these anticipations in two ways: to evaluate outcomes (e.g., the pleasure of eating a pie is evaluated differently at the beginning of a dinner, when one is hungry, and at the end of the dinner, when one is satiated), and as outcomes having a value themselves (e.g., the case of dread as a cost of waiting for punishment). By explicitly accounting for the relationship between prospection and value, our model provides a framework to reconcile the utility-maximization approach with psychological phenomena such as planning for the future and dread.
The Value of Foresight: How Prospection Affects Decision-Making
Pezzulo, Giovanni; Rigoli, Francesco
2011-01-01
Traditional theories of decision-making assume that utilities are based on the intrinsic value of outcomes; in turn, these values depend on associations between expected outcomes and the current motivational state of the decision-maker. This view disregards the fact that humans (and possibly other animals) have prospection abilities, which permit anticipating future mental processes and motivational and emotional states. For instance, we can evaluate future outcomes in light of the motivational state we expect to have when the outcome is collected, not (only) when we make a decision. Consequently, we can plan for the future and choose to store food to be consumed when we expect to be hungry, not immediately. Furthermore, similarly to any expected outcome, we can assign a value to our anticipated mental processes and emotions. It has been reported that (in some circumstances) human subjects prefer to receive an unavoidable punishment immediately, probably because they are anticipating the dread associated with the time spent waiting for the punishment. This article offers a formal framework to guide neuroeconomic research on how prospection affects decision-making. The model has two characteristics. First, it uses model-based Bayesian inference to describe anticipation of cognitive and motivational processes. Second, the utility-maximization process considers these anticipations in two ways: to evaluate outcomes (e.g., the pleasure of eating a pie is evaluated differently at the beginning of a dinner, when one is hungry, and at the end of the dinner, when one is satiated), and as outcomes having a value themselves (e.g., the case of dread as a cost of waiting for punishment). By explicitly accounting for the relationship between prospection and value, our model provides a framework to reconcile the utility-maximization approach with psychological phenomena such as planning for the future and dread. PMID:21747755
NASA Astrophysics Data System (ADS)
Hyun, J. Y.; Yang, Y. C. E.; Tidwell, V. C.; Macknick, J.
2017-12-01
Modeling human behaviors and decisions in water resources management is a challenging issue due to its complexity and uncertain characteristics that affected by both internal (such as stakeholder's beliefs on any external information) and external factors (such as future policies and weather/climate forecast). Stakeholders' decision regarding how much water they need is usually not entirely rational in the real-world cases, so it is not quite suitable to model their decisions with a centralized (top-down) approach that assume everyone in a watershed follow the same order or pursue the same objective. Agent-based modeling (ABM) uses a decentralized approach (bottom-up) that allow each stakeholder to make his/her own decision based on his/her own objective and the belief of information acquired. In this study, we develop an ABM which incorporates the psychological human decision process by the theory of risk perception. The theory of risk perception quantifies human behaviors and decisions uncertainties using two sequential methodologies: the Bayesian Inference and the Cost-Loss Problem. The developed ABM is coupled with a regulation-based water system model: Riverware (RW) to evaluate different human decision uncertainties in water resources management. The San Juan River Basin in New Mexico (Figure 1) is chosen as a case study area, while we define 19 major irrigation districts as water use agents and their primary decision is to decide the irrigated area on an annual basis. This decision will be affected by three external factors: 1) upstream precipitation forecast (potential amount of water availability), 2) violation of the downstream minimum flow (required to support ecosystems), and 3) enforcement of a shortage sharing plan (a policy that is currently undertaken in the region for drought years). Three beliefs (as internal factors) that correspond to these three external factors will also be considered in the modeling framework. The objective of this study is to use the two-way coupling between ABM and RW to mimic how stakeholders' uncertain decisions that have been made through the theory of risk perception will affect local and basin-wide water uses.
Young, Liane; Koenigs, Michael
2007-01-01
Human moral decision-making has long been a topic of philosophical debate, and, more recently, a topic for empirical investigation. Central to this investigation is the extent to which emotional processes underlie our decisions about moral right and wrong. Neuroscience offers a unique perspective on this question by addressing whether brain regions associated with emotional processing are involved in moral cognition. We conduct a narrative review of neuroscientific studies focused on the role of emotion in morality. Specifically, we describe evidence implicating the ventromedial prefrontal cortex (VMPC), a brain region known to be important for emotional processing. Functional imaging studies demonstrate VMPC activation during tasks probing moral cognition. Studies of clinical populations, including patients with VMPC damage, reveal an association between impairments in emotional processing and impairments in moral judgement and behaviour. Considered together, these studies indicate that not only are emotions engaged during moral cognition, but that emotions, particularly those mediated by VMPC, are in fact critical for human morality.
NASA Technical Reports Server (NTRS)
Kyle, R. G.
1972-01-01
Information transfer between the operator and computer-generated display systems is an area where the human factors engineer discovers little useful design data relating human performance to system effectiveness. This study utilized a computer-driven, cathode-ray-tube graphic display to quantify human response speed in a sequential information processing task. The performance criteria was response time to sixteen cell elements of a square matrix display. A stimulus signal instruction specified selected cell locations by both row and column identification. An equal probable number code, from one to four, was assigned at random to the sixteen cells of the matrix and correspondingly required one of four, matched keyed-response alternatives. The display format corresponded to a sequence of diagnostic system maintenance events, that enable the operator to verify prime system status, engage backup redundancy for failed subsystem components, and exercise alternate decision-making judgements. The experimental task bypassed the skilled decision-making element and computer processing time, in order to determine a lower bound on the basic response speed for given stimulus/response hardware arrangement.
Toward an operational model of decision making, emotional regulation, and mental health impact.
Collura, Thomas Francis; Zalaquett, Ronald P; Bonnstetter, Carlos Joyce; Chatters, Seria J
2014-01-01
Current brain research increasingly reveals the underlying mechanisms and processes of human behavior, cognition, and emotion. In addition to being of interest to a wide range of scientists, educators, and professionals, as well as laypeople, brain-based models are of particular value in a clinical setting. Psychiatrists, psychologists, counselors, and other mental health professionals are in need of operational models that integrate recent findings in the physical, cognitive, and emotional domains, and offer a common language for interdisciplinary understanding and communication. Based on individual traits, predispositions, and responses to stimuli, we can begin to identify emotional and behavioral pathways and mental processing patterns. The purpose of this article is to present a brain-path activation model to understand individual differences in decision making and psychopathology. The first section discusses the role of frontal lobe electroencephalography (EEG) asymmetry, summarizes state- and trait-based models of decision making, and provides a more complex analysis that supplements the traditional simple left-right brain model. Key components of the new model are the introduction of right hemisphere parallel and left hemisphere serial scanning in rendering decisions, and the proposition of pathways that incorporate both past experiences as well as future implications into the decision process. Main attributes of each decision-making mechanism are provided. The second section applies the model within the realm of clinical mental health as a tool to understand specific human behavior and pathology. Applications include general and chronic anxiety, depression, paranoia, risk taking, and the pathways employed when well-functioning operational integration is observed. Finally, specific applications such as meditation and mindfulness are offered to facilitate positive functioning.
Development of a First-of-a-Kind Deterministic Decision-Making Tool for Supervisory Control System
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cetiner, Sacit M; Kisner, Roger A; Muhlheim, Michael David
2015-07-01
Decision-making is the process of identifying and choosing alternatives where each alternative offers a different approach or path to move from a given state or condition to a desired state or condition. The generation of consistent decisions requires that a structured, coherent process be defined, immediately leading to a decision-making framework. The overall objective of the generalized framework is for it to be adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or nomore » human intervention. The overriding goal of automation is to replace or supplement human decision makers with reconfigurable decision- making modules that can perform a given set of tasks reliably. Risk-informed decision making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The implementation of the probabilistic portion of the decision-making engine of the proposed supervisory control system was detailed in previous milestone reports. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic multi-attribute decision-making framework uses variable sensor data (e.g., outlet temperature) and calculates where it is within the challenge state, its trajectory, and margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. Metrics to be evaluated include stability, cost, time to complete (action), power level, etc. The integration of deterministic calculations using multi-physics analyses (i.e., neutronics, thermal, and thermal-hydraulics) and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermal-hydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies.« less
Chorvat, Terrence; McCabe, Kevin
2004-01-01
Much has been written about how law as an institution has developed to solve many problems that human societies face. Inherent in all of these explanations are models of how humans make decisions. This article discusses what current neuroscience research tells us about the mechanisms of human decision making of particular relevance to law. This research indicates that humans are both more capable of solving many problems than standard economic models predict, but also limited in ways those models ignore. This article discusses how law is both shaped by our cognitive processes and also shapes them. The article considers some of the implications of this research for improving our understanding of how our current legal regimes operate and how the law can be structured to take advantage of our neural mechanisms to improve social welfare. PMID:15590613
NASA Astrophysics Data System (ADS)
See, Swee Lan; Tan, Mitchell; Looi, Qin En
This paper presents findings from a descriptive research on social gaming. A video-enhanced diary method was used to understand the user experience in social gaming. From this experiment, we found that natural human behavior and gamer’s decision making process can be elicited and speculated during human computer interaction. These are new information that we should consider as they can help us build better human computer interfaces and human robotic interfaces in future.
NASA Astrophysics Data System (ADS)
Holmes, Philip; Eckhoff, Philip; Wong-Lin, K. F.; Bogacz, Rafal; Zacksenhouse, Miriam; Cohen, Jonathan D.
2010-03-01
We describe how drift-diffusion (DD) processes - systems familiar in physics - can be used to model evidence accumulation and decision-making in two-alternative, forced choice tasks. We sketch the derivation of these stochastic differential equations from biophysically-detailed models of spiking neurons. DD processes are also continuum limits of the sequential probability ratio test and are therefore optimal in the sense that they deliver decisions of specified accuracy in the shortest possible time. This leaves open the critical balance of accuracy and speed. Using the DD model, we derive a speed-accuracy tradeoff that optimizes reward rate for a simple perceptual decision task, compare human performance with this benchmark, and discuss possible reasons for prevalent sub-optimality, focussing on the question of uncertain estimates of key parameters. We present an alternative theory of robust decisions that allows for uncertainty, and show that its predictions provide better fits to experimental data than a more prevalent account that emphasises a commitment to accuracy. The article illustrates how mathematical models can illuminate the neural basis of cognitive processes.
Deciding about fast and slow decisions.
Croskerry, Pat; Petrie, David A; Reilly, James B; Tait, Gordon
2014-02-01
Two reports in this issue address the important topic of clinical decision making. Dual process theory has emerged as the dominant model for understanding the complex processes that underlie human decision making. This theory distinguishes between the reflexive, autonomous processes that characterize intuitive decision making and the deliberate reasoning of an analytical approach. In this commentary, the authors address the polarization of viewpoints that has developed around the relative merits of the two systems. Although intuitive processes are typically fast and analytical processes slow, speed alone does not distinguish them. In any event, the majority of decisions in clinical medicine are not dependent on very short response times. What does appear relevant to diagnostic ease and accuracy is the degree to which the symptoms of the disease being diagnosed are characteristic ones. There are also concerns around some methodological issues related to research design in this area of enquiry. Reductionist approaches that attempt to isolate dependent variables may create such artificial experimental conditions that both external and ecological validity are sacrificed. Clinical decision making is a complex process with many independent (and interdependent) variables that need to be separated out in a discrete fashion and then reflected on in real time to preserve the fidelity of clinical practice. With these caveats in mind, the authors believe that research in this area should promote a better understanding of clinical practice and teaching by focusing less on the deficiencies of intuitive and analytical systems and more on their adaptive strengths.
Using an ecological ethics framework to make decisions about the relocation of wildlife
McCoy, E.D.; Berry, K.
2008-01-01
Relocation is an increasingly prominent conservation tool for a variety of wildlife, but the technique also is controversial, even among conservation practitioners. An organized framework for addressing the moral dilemmas often accompanying conservation actions such as relocation has been lacking. Ecological ethics may provide such a framework and appears to be an important step forward in aiding ecological researchers and biodiversity managers to make difficult moral choices. A specific application of this framework can make the reasoning process more transparent and give more emphasis to the strong sentiments about non-human organisms held by many potential users. Providing an example of the application of the framework may also increase the appeal of the reasoning process to ecological researchers and biodiversity managers. Relocation as a conservation action can be accompanied by a variety of moral dilemmas that reflect the interconnection of values, ethical positions, and conservation decisions. A model that is designed to address moral dilemmas arising from relocation of humans provides/demonstrates/illustrates a possible way to apply the ecological ethics framework and to involve practicing conservationists in the overall decision-making process. ?? 2008 Springer Science+Business Media B.V.
Miller, Keith W; Wolf, Marty J; Grodzinsky, Frances
2017-04-01
In this paper we address the question of when a researcher is justified in describing his or her artificial agent as demonstrating ethical decision-making. The paper is motivated by the amount of research being done that attempts to imbue artificial agents with expertise in ethical decision-making. It seems clear that computing systems make decisions, in that they make choices between different options; and there is scholarship in philosophy that addresses the distinction between ethical decision-making and general decision-making. Essentially, the qualitative difference between ethical decisions and general decisions is that ethical decisions must be part of the process of developing ethical expertise within an agent. We use this distinction in examining publicity surrounding a particular experiment in which a simulated robot attempted to safeguard simulated humans from falling into a hole. We conclude that any suggestions that this simulated robot was making ethical decisions were misleading.
Human reliability assessment: tools for law enforcement
NASA Astrophysics Data System (ADS)
Ryan, Thomas G.; Overlin, Trudy K.
1997-01-01
This paper suggests ways in which human reliability analysis (HRA) can assist the United State Justice System, and more specifically law enforcement, in enhancing the reliability of the process from evidence gathering through adjudication. HRA is an analytic process identifying, describing, quantifying, and interpreting the state of human performance, and developing and recommending enhancements based on the results of individual HRA. It also draws on lessons learned from compilations of several HRA. Given the high legal standards the Justice System is bound to, human errors that might appear to be trivial in other venues can make the difference between a successful and unsuccessful prosecution. HRA has made a major contribution to the efficiency, favorable cost-benefit ratio, and overall success of many enterprises where humans interface with sophisticated technologies, such as the military, ground transportation, chemical and oil production, nuclear power generation, commercial aviation and space flight. Each of these enterprises presents similar challenges to the humans responsible for executing action and action sequences, especially where problem solving and decision making are concerned. Nowhere are humans confronted, to a greater degree, with problem solving and decision making than are the diverse individuals and teams responsible for arrest and adjudication of criminal proceedings. This paper concludes that because of the parallels between the aforementioned technologies and the adjudication process, especially crime scene evidence gathering, there is reason to believe that the HRA technology, developed and enhanced in other applications, can be transferred to the Justice System with minimal cost and with significant payoff.
Emotion-based decision-making in healthy subjects: short-term effects of reducing dopamine levels.
Sevy, Serge; Hassoun, Youssef; Bechara, Antoine; Yechiam, Eldad; Napolitano, Barbara; Burdick, Katherine; Delman, Howard; Malhotra, Anil
2006-10-01
Converging evidences from animal and human studies suggest that addiction is associated with dopaminergic dysfunction in brain reward circuits. So far, it is unclear what aspects of addictive behaviors are related to a dopaminergic dysfunction. We hypothesize that a decrease in dopaminergic activity impairs emotion-based decision-making. To demonstrate this hypothesis, we investigated the effects of a decrease in dopaminergic activity on the performance of an emotion-based decision-making task, the Iowa gambling task (IGT), in 11 healthy human subjects. We used a double-blind, placebo-controlled, within-subject design to examine the effect of a mixture containing the branched-chain amino acids (BCAA) valine, isoleucine and leucine on prolactin, IGT performance, perceptual competency and visual aspects of visuospatial working memory, visual attention and working memory, and verbal memory. The expectancy-valence model was used to determine the relative contributions of distinct IGT components (attention to past outcomes, relative weight of wins and losses, and choice strategies) in the decision-making process. Compared to placebo, the BCAA mixture increased prolactin levels and impaired IGT performance. BCAA administration interfered with a particular component process of decision-making related to attention to more recent events as compared to more distant events. There were no differences between placebo and BCAA conditions for other aspects of cognition. Our results suggest a direct link between a reduced dopaminergic activity and poor emotion-based decision-making characterized by shortsightedness, and thus difficulties resisting short-term reward, despite long-term negative consequences. These findings have implications for behavioral and pharmacological interventions targeting impaired emotion-based decision-making in addictive disorders.
5 CFR 9901.223 - Appeal to DoD for review of classification decisions.
Code of Federal Regulations, 2010 CFR
2010-01-01
... RESOURCES MANAGEMENT AND LABOR RELATIONS SYSTEMS (DEPARTMENT OF DEFENSE-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF DEFENSE NATIONAL SECURITY PERSONNEL SYSTEM (NSPS) Classification Classification Process § 9901... process. (1) Employee appeals to DoD must be submitted through the employee's servicing Human Resources...
Leong, T-Y
2012-01-01
This paper summarizes the recent trends and highlights the challenges and opportunities in decision support and knowledge management for patient-centered, personalized, and personal health care. The discussions are based on a broad survey of related references, focusing on the most recent publications. Major advances are examined in the areas of i) shared decision making paradigms, ii) continuity of care infrastructures and architectures, iii) human factors and system design approaches, iv) knowledge management innovations, and v) practical deployment and change considerations. Many important initiatives, projects, and plans with promising results have been identified. The common themes focus on supporting the individual patients who are playing an increasing central role in their own care decision processes. New collaborative decision making paradigms and information infrastructures are required to ensure effective continuity of care. Human factors and usability are crucial for the successful development and deployment of the relevant systems, tools, and aids. Advances in personalized medicine can be achieved through integrating genomic, phenotypic and other biological, individual, and population level information, and gaining useful insights from building and analyzing biological and other models at multiple levels of abstraction. Therefore, new Information and Communication Technologies and evaluation approaches are needed to effectively manage the scale and complexity of biomedical and health information, and adapt to the changing nature of clinical decision support. Recent research in decision support and knowledge management combines heterogeneous information and personal data to provide cost-effective, calibrated, personalized support in shared decision making at the point of care. Current and emerging efforts concentrate on developing or extending conventional paradigms, techniques, systems, and architectures for the new predictive, preemptive, and participatory health care model for patient-centered, personalized medicine. There is also an increasing emphasis on managing complexity with changing care models, processes, and settings.
Wright, Adam; Sittig, Dean F; Ash, Joan S; Erickson, Jessica L; Hickman, Trang T; Paterno, Marilyn; Gebhardt, Eric; McMullen, Carmit; Tsurikova, Ruslana; Dixon, Brian E; Fraser, Greg; Simonaitis, Linas; Sonnenberg, Frank A; Middleton, Blackford
2015-11-01
To identify challenges, lessons learned and best practices for service-oriented clinical decision support, based on the results of the Clinical Decision Support Consortium, a multi-site study which developed, implemented and evaluated clinical decision support services in a diverse range of electronic health records. Ethnographic investigation using the rapid assessment process, a procedure for agile qualitative data collection and analysis, including clinical observation, system demonstrations and analysis and 91 interviews. We identified challenges and lessons learned in eight dimensions: (1) hardware and software computing infrastructure, (2) clinical content, (3) human-computer interface, (4) people, (5) workflow and communication, (6) internal organizational policies, procedures, environment and culture, (7) external rules, regulations, and pressures and (8) system measurement and monitoring. Key challenges included performance issues (particularly related to data retrieval), differences in terminologies used across sites, workflow variability and the need for a legal framework. Based on the challenges and lessons learned, we identified eight best practices for developers and implementers of service-oriented clinical decision support: (1) optimize performance, or make asynchronous calls, (2) be liberal in what you accept (particularly for terminology), (3) foster clinical transparency, (4) develop a legal framework, (5) support a flexible front-end, (6) dedicate human resources, (7) support peer-to-peer communication, (8) improve standards. The Clinical Decision Support Consortium successfully developed a clinical decision support service and implemented it in four different electronic health records and four diverse clinical sites; however, the process was arduous. The lessons identified by the Consortium may be useful for other developers and implementers of clinical decision support services. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Achievement Motivation and the Adolescent Musician: A Synthesis of the Literature
ERIC Educational Resources Information Center
Schatt, Matthew D.
2011-01-01
Motivation plays a role in nearly all human decision-making processes. Regardless of the situation, little may be achieved without the appropriate harnessing of motivation. The same is true in the music classroom. Research appears to indicate that motivation plays a crucial role in human development and achievement. The achievement motivation…
ERIC Educational Resources Information Center
Bayram, Servet
2005-01-01
The concept of Electronic Performance Support Systems (EPSS) is containing multimedia or computer based instruction components that improves human performance by providing process simplification, performance information and decision support system. EPSS has become a hot topic for organizational development, human resources, performance technology,…
Overview of Aro Program on Network Science for Human Decision Making
NASA Astrophysics Data System (ADS)
West, Bruce J.
This program brings together researchers from disparate disciplines to work on a complex research problem that defies confinement within any single discipline. Consequently, not only are new and rewarding solutions sought and obtained for a problem of importance to society and the Army, that is, the human dimension of complex networks, but, in addition, collaborations are established that would not otherwise have formed given the traditional disciplinary compartmentalization of research. This program develops the basic research foundation of a science of networks supporting the linkage between the physical and human (cognitive and social) domains as they relate to human decision making. The strategy is to extend the recent methods of non-equilibrium statistical physics to non-stationary, renewal stochastic processes that appear to be characteristic of the interactions among nodes in complex networks. We also pursue understanding of the phenomenon of synchronization, whose mathematical formulation has recently provided insight into how complex networks reach accommodation and cooperation. The theoretical analyses of complex networks, although mathematically rigorous, often elude analytic solutions and require computer simulation and computation to analyze the underlying dynamic process.
Integrated Cognitive Architectures For Robust Decision Making
2010-09-20
groups differed significantly from the other three [W(5) > 5, p > 0.13, uncorrected]. Performance by Condition It is useful to look at the average...the research that pursues integrated theories of human cognition, two approaches have become particularly influencial : ACT-R and Leabra. ACT-R...a wide range of tasks involving attention, learning, memory, problem solving, decision making, and language processing. Under the pressure of
ERIC Educational Resources Information Center
Clemens, Rachael Annette
2017-01-01
This qualitative and interpretive inquiry explores the information behavior of birthmothers surrounding the processes of decision-making, coping, and living with the act of child relinquishment to adoption. An interpretative phenomenological analysis methodology is used to reveal the phenomenon as experienced by eight birthmothers, women who…
Keeping Signals Straight: How Cells Process Information and Make Decisions
Laub, Michael T.
2016-01-01
As we become increasingly dependent on electronic information-processing systems at home and work, it’s easy to lose sight of the fact that our very survival depends on highly complex biological information-processing systems. Each of the trillions of cells that form the human body has the ability to detect and respond to a wide range of stimuli and inputs, using an extraordinary set of signaling proteins to process this information and make decisions accordingly. Indeed, cells in all organisms rely on these signaling proteins to survive and proliferate in unpredictable and sometimes rapidly changing environments. But how exactly do these proteins relay information within cells, and how do they keep a multitude of incoming signals straight? Here, I describe recent efforts to understand the fidelity of information flow inside cells. This work is providing fundamental insight into how cells function. Additionally, it may lead to the design of novel antibiotics that disrupt the signaling of pathogenic bacteria or it could help to guide the treatment of cancer, which often involves information-processing gone awry inside human cells. PMID:27427909
Gonzalez Bernaldo de Quiros, Fernan; Dawidowski, Adriana R; Figar, Silvana
2017-02-01
In this study, we aimed: 1) to conceptualize the theoretical challenges facing health information systems (HIS) to represent patients' decisions about health and medical treatments in everyday life; 2) to suggest approaches for modeling these processes. The conceptualization of the theoretical and methodological challenges was discussed in 2015 during a series of interdisciplinary meetings attended by health informatics staff, epidemiologists and health professionals working in quality management and primary and secondary prevention of chronic diseases of the Hospital Italiano de Buenos Aires, together with sociologists, anthropologists and e-health stakeholders. HIS are facing the need and challenge to represent social human processes based on constructivist and complexity theories, which are the current frameworks of human sciences for understanding human learning and socio-cultural changes. Computer systems based on these theories can model processes of social construction of concrete and subjective entities and the interrelationships between them. These theories could be implemented, among other ways, through the mapping of health assets, analysis of social impact through community trials and modeling of complexity with system simulation tools. This analysis suggested the need to complement the traditional linear causal explanations of disease onset (and treatments) that are the bases for models of analysis of HIS with constructivist and complexity frameworks. Both may enlighten the complex interrelationships among patients, health services and the health system. The aim of this strategy is to clarify people's decision making processes to improve the efficiency, quality and equity of the health services and the health system.
Emergent collective decision-making: Control, model and behavior
NASA Astrophysics Data System (ADS)
Shen, Tian
In this dissertation we study emergent collective decision-making in social groups with time-varying interactions and heterogeneously informed individuals. First we analyze a nonlinear dynamical systems model motivated by animal collective motion with heterogeneously informed subpopulations, to examine the role of uninformed individuals. We find through formal analysis that adding uninformed individuals in a group increases the likelihood of a collective decision. Secondly, we propose a model for human shared decision-making with continuous-time feedback and where individuals have little information about the true preferences of other group members. We study model equilibria using bifurcation analysis to understand how the model predicts decisions based on the critical threshold parameters that represent an individual's tradeoff between social and environmental influences. Thirdly, we analyze continuous-time data of pairs of human subjects performing an experimental shared tracking task using our second proposed model in order to understand transient behavior and the decision-making process. We fit the model to data and show that it reproduces a wide range of human behaviors surprisingly well, suggesting that the model may have captured the mechanisms of observed behaviors. Finally, we study human behavior from a game-theoretic perspective by modeling the aforementioned tracking task as a repeated game with incomplete information. We show that the majority of the players are able to converge to playing Nash equilibrium strategies. We then suggest with simulations that the mean field evolution of strategies in the population resemble replicator dynamics, indicating that the individual strategies may be myopic. Decisions form the basis of control and problems involving deciding collectively between alternatives are ubiquitous in nature and in engineering. Understanding how multi-agent systems make decisions among alternatives also provides insight for designing decentralized control laws for engineering applications from mobile sensor networks for environmental monitoring to collective construction robots. With this dissertation we hope to provide additional methodology and mathematical models for understanding the behavior and control of collective decision-making in multi-agent systems.
Multi-criteria evaluation methods in the production scheduling
NASA Astrophysics Data System (ADS)
Kalinowski, K.; Krenczyk, D.; Paprocka, I.; Kempa, W.; Grabowik, C.
2016-08-01
The paper presents a discussion on the practical application of different methods of multi-criteria evaluation in the process of scheduling in manufacturing systems. Among the methods two main groups are specified: methods based on the distance function (using metacriterion) and methods that create a Pareto set of possible solutions. The basic criteria used for scheduling were also described. The overall procedure of evaluation process in production scheduling was presented. It takes into account the actions in the whole scheduling process and human decision maker (HDM) participation. The specified HDM decisions are related to creating and editing a set of evaluation criteria, selection of multi-criteria evaluation method, interaction in the searching process, using informal criteria and making final changes in the schedule for implementation. According to need, process scheduling may be completely or partially automated. Full automatization is possible in case of metacriterion based objective function and if Pareto set is selected - the final decision has to be done by HDM.
The Neural Basis of Social Influence in a Dictator Decision.
Wei, Zhenyu; Zhao, Zhiying; Zheng, Yong
2017-01-01
Humans tend to reduce inequitable distributions. Previous neuroimaging studies have shown that inequitable decisions are related to brain regions that associated with negative emotion and signaling conflict. In the highly complex human social environment, our opinions and behaviors can be affected by social information. In current study, we used a modified dictator game to investigate the effect of social influence on making an equitable decision. We found that the choices of participants in present task was influenced by the choices of peers. However, participants' decisions were influenced by equitable rather than inequitable group choices. fMRI results showed that brain regions that related to norm violation and social conflict were related to the inequitable social influence. The neural responses in the dorsomedial prefrontal cortex, rostral cingulate zone, and insula predicted subsequent conforming behavior in individuals. Additionally, psychophysiological interaction analysis revealed that the interconnectivity between the dorsal striatum and insula was elevated in advantageous inequity influence versus no-social influence conditions. We found decreased functional connectivity between the medial prefrontal cortex and insula, supplementary motor area, posterior cingulate gyrus and dorsal anterior cingulate cortex in the disadvantageous inequity influence versus no-social influence conditions. This suggests that a disadvantageous inequity influence may decrease the functional connectivity among brain regions that are related to reward processes. Thus, the neural mechanisms underlying social influence in an equitable decision may be similar to those implicated in social norms and reward processing.
Translational Models of Gambling-Related Decision-Making.
Winstanley, Catharine A; Clark, Luke
Gambling is a harmless, recreational pastime that is ubiquitous across cultures. However, for some, gambling becomes a maladaptive and compulsive, and this syndrome is conceptualized as a behavioural addiction. Laboratory models that capture the key cognitive processes involved in gambling behaviour, and that can be translated across species, have the potential to make an important contribution to both decision neuroscience and the study of addictive disorders. The Iowa gambling task has been widely used to assess human decision-making under uncertainty, and this paradigm can be successfully modelled in rodents. Similar neurobiological processes underpin choice behaviour in humans and rats, and thus, a preference for the disadvantageous "high-risk, high-reward" options may reflect meaningful vulnerability for mental health problems. However, the choice behaviour operationalized by these tasks does not necessarily approximate the vulnerability to gambling disorder (GD) per se. We consider a number of psychological challenges that apply to modelling gambling in a translational way, and evaluate the success of the existing models. Heterogeneity in the structure of gambling games, as well as in the motivations of individuals with GD, is highlighted. The potential issues with extrapolating too directly from established animal models of drug dependency are discussed, as are the inherent difficulties in validating animal models of GD in the absence of any approved treatments for GD. Further advances in modelling the cognitive biases endemic in human decision-making, which appear to be exacerbated in GD, may be a promising line of research.
Balleine, Bernard W; O'Doherty, John P
2010-01-01
Recent behavioral studies in both humans and rodents have found evidence that performance in decision-making tasks depends on two different learning processes; one encoding the relationship between actions and their consequences and a second involving the formation of stimulus–response associations. These learning processes are thought to govern goal-directed and habitual actions, respectively, and have been found to depend on homologous corticostriatal networks in these species. Thus, recent research using comparable behavioral tasks in both humans and rats has implicated homologous regions of cortex (medial prefrontal cortex/medial orbital cortex in humans and prelimbic cortex in rats) and of dorsal striatum (anterior caudate in humans and dorsomedial striatum in rats) in goal-directed action and in the control of habitual actions (posterior lateral putamen in humans and dorsolateral striatum in rats). These learning processes have been argued to be antagonistic or competing because their control over performance appears to be all or none. Nevertheless, evidence has started to accumulate suggesting that they may at times compete and at others cooperate in the selection and subsequent evaluation of actions necessary for normal choice performance. It appears likely that cooperation or competition between these sources of action control depends not only on local interactions in dorsal striatum but also on the cortico-basal ganglia network within which the striatum is embedded and that mediates the integration of learning with basic motivational and emotional processes. The neural basis of the integration of learning and motivation in choice and decision-making is still controversial and we review some recent hypotheses relating to this issue. PMID:19776734
Effects of imperfect automation on decision making in a simulated command and control task.
Rovira, Ericka; McGarry, Kathleen; Parasuraman, Raja
2007-02-01
Effects of four types of automation support and two levels of automation reliability were examined. The objective was to examine the differential impact of information and decision automation and to investigate the costs of automation unreliability. Research has shown that imperfect automation can lead to differential effects of stages and levels of automation on human performance. Eighteen participants performed a "sensor to shooter" targeting simulation of command and control. Dependent variables included accuracy and response time of target engagement decisions, secondary task performance, and subjective ratings of mental work-load, trust, and self-confidence. Compared with manual performance, reliable automation significantly reduced decision times. Unreliable automation led to greater cost in decision-making accuracy under the higher automation reliability condition for three different forms of decision automation relative to information automation. At low automation reliability, however, there was a cost in performance for both information and decision automation. The results are consistent with a model of human-automation interaction that requires evaluation of the different stages of information processing to which automation support can be applied. If fully reliable decision automation cannot be guaranteed, designers should provide users with information automation support or other tools that allow for inspection and analysis of raw data.
Informing clinical policy decision-making practices in ambulance services.
Muecke, Sandy; Curac, Nada; Binks, Darryn
2013-12-01
This study aims to identify the processes and frameworks that support an evidence-based approach to clinical policy decision-making practices in ambulance services. This literature review focused on: (i) the setting (pre-hospital); and (ii) the process of evidence translation, for studies published after the year 2000. Searches of Medline, CINAHL and Google were undertaken. Reference lists of eligible publications were searched for relevant articles. A total of 954 articles were identified. Of these, 20 full text articles were assessed for eligibility and seven full text articles met the inclusion criteria. Three provided detailed descriptions of the evidence-based practice processes used to inform ambulance service protocol or guideline development or review. There is little published literature that describes the processes involved, and frameworks required, to inform clinical policy decision making within ambulance services. This review found that processes were iterative and involved collaborations across many internal and external stakeholders. In several jurisdictions, these were coordinated by a dedicated team. Success appears dependent on committed leadership and purposive human and structural resources. Although time consuming, structured processes have been developed in some jurisdictions to assist decision-making processes. Further insight is likely to be obtained from literature published by those from other disciplines. © 2013 The Authors. International Journal of Evidence-Based Healthcare © 2013 The Joanna Briggs Institute.
Intergroup Conflict and Rational Decision Making
Martínez-Tur, Vicente; Peñarroja, Vicente; Serrano, Miguel A.; Hidalgo, Vanesa; Moliner, Carolina; Salvador, Alicia; Alacreu-Crespo, Adrián; Gracia, Esther; Molina, Agustín
2014-01-01
The literature has been relatively silent about post-conflict processes. However, understanding the way humans deal with post-conflict situations is a challenge in our societies. With this in mind, we focus the present study on the rationality of cooperative decision making after an intergroup conflict, i.e., the extent to which groups take advantage of post-conflict situations to obtain benefits from collaborating with the other group involved in the conflict. Based on dual-process theories of thinking and affect heuristic, we propose that intergroup conflict hinders the rationality of cooperative decision making. We also hypothesize that this rationality improves when groups are involved in an in-group deliberative discussion. Results of a laboratory experiment support the idea that intergroup conflict –associated with indicators of the activation of negative feelings (negative affect state and heart rate)– has a negative effect on the aforementioned rationality over time and on both group and individual decision making. Although intergroup conflict leads to sub-optimal decision making, rationality improves when groups and individuals subjected to intergroup conflict make decisions after an in-group deliberative discussion. Additionally, the increased rationality of the group decision making after the deliberative discussion is transferred to subsequent individual decision making. PMID:25461384
Intergroup conflict and rational decision making.
Martínez-Tur, Vicente; Peñarroja, Vicente; Serrano, Miguel A; Hidalgo, Vanesa; Moliner, Carolina; Salvador, Alicia; Alacreu-Crespo, Adrián; Gracia, Esther; Molina, Agustín
2014-01-01
The literature has been relatively silent about post-conflict processes. However, understanding the way humans deal with post-conflict situations is a challenge in our societies. With this in mind, we focus the present study on the rationality of cooperative decision making after an intergroup conflict, i.e., the extent to which groups take advantage of post-conflict situations to obtain benefits from collaborating with the other group involved in the conflict. Based on dual-process theories of thinking and affect heuristic, we propose that intergroup conflict hinders the rationality of cooperative decision making. We also hypothesize that this rationality improves when groups are involved in an in-group deliberative discussion. Results of a laboratory experiment support the idea that intergroup conflict -associated with indicators of the activation of negative feelings (negative affect state and heart rate)- has a negative effect on the aforementioned rationality over time and on both group and individual decision making. Although intergroup conflict leads to sub-optimal decision making, rationality improves when groups and individuals subjected to intergroup conflict make decisions after an in-group deliberative discussion. Additionally, the increased rationality of the group decision making after the deliberative discussion is transferred to subsequent individual decision making.
Marusich, Laura R; Bakdash, Jonathan Z; Onal, Emrah; Yu, Michael S; Schaffer, James; O'Donovan, John; Höllerer, Tobias; Buchler, Norbou; Gonzalez, Cleotilde
2016-03-01
We investigated how increases in task-relevant information affect human decision-making performance, situation awareness (SA), and trust in a simulated command-and-control (C2) environment. Increased information is often associated with an improvement of SA and decision-making performance in networked organizations. However, previous research suggests that increasing information without considering the task relevance and the presentation can impair performance. We used a simulated C2 task across two experiments. Experiment 1 varied the information volume provided to individual participants and measured the speed and accuracy of decision making for task performance. Experiment 2 varied information volume and information reliability provided to two participants acting in different roles and assessed decision-making performance, SA, and trust between the paired participants. In both experiments, increased task-relevant information volume did not improve task performance. In Experiment 2, increased task-relevant information volume reduced self-reported SA and trust, and incorrect source reliability information led to poorer task performance and SA. These results indicate that increasing the volume of information, even when it is accurate and task relevant, is not necessarily beneficial to decision-making performance. Moreover, it may even be detrimental to SA and trust among team members. Given the high volume of available and shared information and the safety-critical and time-sensitive nature of many decisions, these results have implications for training and system design in C2 domains. To avoid decrements to SA, interpersonal trust, and decision-making performance, information presentation within C2 systems must reflect human cognitive processing limits and capabilities. © 2016, Human Factors and Ergonomics Society.
NASA Astrophysics Data System (ADS)
Panulla, Brian J.; More, Loretta D.; Shumaker, Wade R.; Jones, Michael D.; Hooper, Robert; Vernon, Jeffrey M.; Aungst, Stanley G.
2009-05-01
Rapid improvements in communications infrastructure and sophistication of commercial hand-held devices provide a major new source of information for assessing extreme situations such as environmental crises. In particular, ad hoc collections of humans can act as "soft sensors" to augment data collected by traditional sensors in a net-centric environment (in effect, "crowd-sourcing" observational data). A need exists to understand how to task such soft sensors, characterize their performance and fuse the data with traditional data sources. In order to quantitatively study such situations, as well as study distributed decision-making, we have developed an Extreme Events Laboratory (EEL) at The Pennsylvania State University. This facility provides a network-centric, collaborative situation assessment and decision-making capability by supporting experiments involving human observers, distributed decision making and cognition, and crisis management. The EEL spans the information chain from energy detection via sensors, human observations, signal and image processing, pattern recognition, statistical estimation, multi-sensor data fusion, visualization and analytics, and modeling and simulation. The EEL command center combines COTS and custom collaboration tools in innovative ways, providing capabilities such as geo-spatial visualization and dynamic mash-ups of multiple data sources. This paper describes the EEL and several on-going human-in-the-loop experiments aimed at understanding the new collective observation and analysis landscape.
Using Statistical Process Control to Make Data-Based Clinical Decisions.
ERIC Educational Resources Information Center
Pfadt, Al; Wheeler, Donald J.
1995-01-01
Statistical process control (SPC), which employs simple statistical tools and problem-solving techniques such as histograms, control charts, flow charts, and Pareto charts to implement continual product improvement procedures, can be incorporated into human service organizations. Examples illustrate use of SPC procedures to analyze behavioral data…
The Process of Solving Complex Problems
ERIC Educational Resources Information Center
Fischer, Andreas; Greiff, Samuel; Funke, Joachim
2012-01-01
This article is about Complex Problem Solving (CPS), its history in a variety of research domains (e.g., human problem solving, expertise, decision making, and intelligence), a formal definition and a process theory of CPS applicable to the interdisciplinary field. CPS is portrayed as (a) knowledge acquisition and (b) knowledge application…
Robotic Billiards: Understanding Humans in Order to Counter Them.
Nierhoff, Thomas; Leibrandt, Konrad; Lorenz, Tamara; Hirche, Sandra
2016-08-01
Ongoing technological advances in the areas of computation, sensing, and mechatronics enable robotic-based systems to interact with humans in the real world. To succeed against a human in a competitive scenario, a robot must anticipate the human behavior and include it in its own planning framework. Then it can predict the next human move and counter it accordingly, thus not only achieving overall better performance but also systematically exploiting the opponent's weak spots. Pool is used as a representative scenario to derive a model-based planning and control framework where not only the physics of the environment but also a model of the opponent is considered. By representing the game of pool as a Markov decision process and incorporating a model of the human decision-making based on studies, an optimized policy is derived. This enables the robot to include the opponent's typical game style into its tactical considerations when planning a stroke. The results are validated in simulations and real-life experiments with an anthropomorphic robot playing pool against a human.
Voting Intention and Choices: Are Voters Always Rational and Deliberative?
Lee, I-Ching; Chen, Eva E.; Tsai, Chia-Hung; Yen, Nai-Shing; Chen, Arbee L. P.; Lin, Wei-Chieh
2016-01-01
Human rationality–the ability to behave in order to maximize the achievement of their presumed goals (i.e., their optimal choices)–is the foundation for democracy. Research evidence has suggested that voters may not make decisions after exhaustively processing relevant information; instead, our decision-making capacity may be restricted by our own biases and the environment. In this paper, we investigate the extent to which humans in a democratic society can be rational when making decisions in a serious, complex situation–voting in a local political election. We believe examining human rationality in a political election is important, because a well-functioning democracy rests largely upon the rational choices of individual voters. Previous research has shown that explicit political attitudes predict voting intention and choices (i.e., actual votes) in democratic societies, indicating that people are able to reason comprehensively when making voting decisions. Other work, though, has demonstrated that the attitudes of which we may not be aware, such as our implicit (e.g., subconscious) preferences, can predict voting choices, which may question the well-functioning democracy. In this study, we systematically examined predictors on voting intention and choices in the 2014 mayoral election in Taipei, Taiwan. Results indicate that explicit political party preferences had the largest impact on voting intention and choices. Moreover, implicit political party preferences interacted with explicit political party preferences in accounting for voting intention, and in turn predicted voting choices. Ethnic identity and perceived voting intention of significant others were found to predict voting choices, but not voting intention. In sum, to the comfort of democracy, voters appeared to engage mainly explicit, controlled processes in making their decisions; but findings on ethnic identity and perceived voting intention of significant others may suggest otherwise. PMID:26886266
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Hong; Wang, Shaobu; Fan, Rui
This report summaries the work performed under the LDRD project on the preliminary study on knowledge automation, where specific focus has been made on the investigation of the impact of uncertainties of human decision making onto the optimization of the process operation. At first the statistics on signals from the Brain-Computing Interface (BCI) is analyzed so as to obtain the uncertainties characterization of human operators during the decision making phase using the electroencephalogram (EEG) signals. This is then followed by the discussions of an architecture that reveals the equivalence between optimization and closed loop feedback control design, where it hasmore » been shown that all the optimization problems can be transferred into the control design problem for closed loop systems. This has led to a “closed loop” framework, where the structure of the decision making is shown to be subjected to both process disturbances and controller’s uncertainties. The latter can well represent the uncertainties or randomness occurred during human decision making phase. As a result, a stochastic optimization problem has been formulated and a novel solution has been proposed using probability density function (PDF) shaping for both the cost function and the constraints using stochastic distribution control concept. A sufficient condition has been derived that guarantees the convergence of the optimal solution and discussions have been made for both the total probabilistic solution and chanced constrained optimization which have been well-studied in optimal power flows (OPF) area. A simple case study has been carried out for the economic dispatch of powers for a grid system when there are distributed energy resources (DERs) in the system, and encouraging results have been obtained showing that a significant savings on the generation cost can be expected.« less
Voting Intention and Choices: Are Voters Always Rational and Deliberative?
Lee, I-Ching; Chen, Eva E; Tsai, Chia-Hung; Yen, Nai-Shing; Chen, Arbee L P; Lin, Wei-Chieh
2016-01-01
Human rationality--the ability to behave in order to maximize the achievement of their presumed goals (i.e., their optimal choices)--is the foundation for democracy. Research evidence has suggested that voters may not make decisions after exhaustively processing relevant information; instead, our decision-making capacity may be restricted by our own biases and the environment. In this paper, we investigate the extent to which humans in a democratic society can be rational when making decisions in a serious, complex situation-voting in a local political election. We believe examining human rationality in a political election is important, because a well-functioning democracy rests largely upon the rational choices of individual voters. Previous research has shown that explicit political attitudes predict voting intention and choices (i.e., actual votes) in democratic societies, indicating that people are able to reason comprehensively when making voting decisions. Other work, though, has demonstrated that the attitudes of which we may not be aware, such as our implicit (e.g., subconscious) preferences, can predict voting choices, which may question the well-functioning democracy. In this study, we systematically examined predictors on voting intention and choices in the 2014 mayoral election in Taipei, Taiwan. Results indicate that explicit political party preferences had the largest impact on voting intention and choices. Moreover, implicit political party preferences interacted with explicit political party preferences in accounting for voting intention, and in turn predicted voting choices. Ethnic identity and perceived voting intention of significant others were found to predict voting choices, but not voting intention. In sum, to the comfort of democracy, voters appeared to engage mainly explicit, controlled processes in making their decisions; but findings on ethnic identity and perceived voting intention of significant others may suggest otherwise.
Veksler, Vladislav D; Buchler, Norbou; Hoffman, Blaine E; Cassenti, Daniel N; Sample, Char; Sugrim, Shridat
2018-01-01
Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision likelihood distributions, (b) human factors of cyber tools to address human system integration challenges, estimation of defender cognitive states, and opportunities for automation, (c) dynamic simulations involving attacker, defender, and user models to enhance studies of cyber epidemiology and cyber hygiene, and (d) training effectiveness research and training scenarios to address human cyber-security performance, maturation of cyber-security skill sets, and effective decision-making. Models may be initially constructed at the group-level based on mean tendencies of each subject's subgroup, based on known statistics such as specific skill proficiencies, demographic characteristics, and cultural factors. For more precise and accurate predictions, cognitive models may be fine-tuned to each individual attacker, defender, or user profile, and updated over time (based on recorded behavior) via techniques such as model tracing and dynamic parameter fitting.
Probabilistic models in human sensorimotor control
Wolpert, Daniel M.
2009-01-01
Sensory and motor uncertainty form a fundamental constraint on human sensorimotor control. Bayesian decision theory (BDT) has emerged as a unifying framework to understand how the central nervous system performs optimal estimation and control in the face of such uncertainty. BDT has two components: Bayesian statistics and decision theory. Here we review Bayesian statistics and show how it applies to estimating the state of the world and our own body. Recent results suggest that when learning novel tasks we are able to learn the statistical properties of both the world and our own sensory apparatus so as to perform estimation using Bayesian statistics. We review studies which suggest that humans can combine multiple sources of information to form maximum likelihood estimates, can incorporate prior beliefs about possible states of the world so as to generate maximum a posteriori estimates and can use Kalman filter-based processes to estimate time-varying states. Finally, we review Bayesian decision theory in motor control and how the central nervous system processes errors to determine loss functions and optimal actions. We review results that suggest we plan movements based on statistics of our actions that result from signal-dependent noise on our motor outputs. Taken together these studies provide a statistical framework for how the motor system performs in the presence of uncertainty. PMID:17628731
Replicable effects of primes on human behavior.
Payne, B Keith; Brown-Iannuzzi, Jazmin L; Loersch, Chris
2016-10-01
[Correction Notice: An Erratum for this article was reported online in Journal of Experimental Psychology: General on Oct 31 2016 (see record 2016-52334-001). ] The effect of primes (i.e., incidental cues) on human behavior has become controversial. Early studies reported counterintuitive findings, suggesting that primes can shape a wide range of human behaviors. Recently, several studies failed to replicate some earlier priming results, raising doubts about the reliability of those effects. We present a within-subjects procedure for priming behavior, in which participants decide whether to bet or pass on each trial of a gambling game. We report 6 replications (N = 988) showing that primes consistently affected gambling decisions when the decision was uncertain. Decisions were influenced by primes presented visibly, with a warning to ignore the primes (Experiments 1 through 3) and with subliminally presented masked primes (Experiment 4). Using a process dissociation procedure, we found evidence that primes influenced responses through both automatic and controlled processes (Experiments 5 and 6). Results provide evidence that primes can reliably affect behavior, under at least some conditions, without intention. The findings suggest that the psychological question of whether behavior priming effects are real should be separated from methodological issues affecting how easily particular experimental designs will replicate. PsycINFO Database Record (c) 2016 APA, all rights reserved
Decontamination and management of human remains following incidents of hazardous chemical release.
Hauschild, Veronique D; Watson, Annetta; Bock, Robert
2012-01-01
To provide specific guidance and resources for systematic and orderly decontamination of human remains resulting from a chemical terrorist attack or accidental chemical release. A detailed review and health-based decision criteria protocol is summarized. Protocol basis and logic are derived from analyses of compound-specific toxicological data and chemical/physical characteristics. Guidance is suitable for civilian or military settings where human remains potentially contaminated with hazardous chemicals may be present, such as sites of transportation accidents, terrorist operations, or medical examiner processing points. Guidance is developed from data-characterizing controlled experiments with laboratory animals, fabrics, and materiel. Logic and specific procedures for decontamination and management of remains, protection of mortuary affairs personnel, and decision criteria to determine when remains are sufficiently decontaminated are presented. Established procedures as well as existing materiel and available equipment for decontamination and verification provide reasonable means to mitigate chemical hazards from chemically exposed remains. Unique scenarios such as those involving supralethal concentrations of certain liquid chemical warfare agents may prove difficult to decontaminate but can be resolved in a timely manner by application of the characterized systematic approaches. Decision criteria and protocols to "clear" decontaminated remains for transport and processing are also provided. Once appropriate decontamination and verification have been accomplished, normal procedures for management of remains and release can be followed.
Neural Basis of Strategic Decision Making
Lee, Daeyeol; Seo, Hyojung
2015-01-01
Human choice behaviors during social interactions often deviate from the predictions of game theory. This might arise partly from the limitations in cognitive abilities necessary for recursive reasoning about the behaviors of others. In addition, during iterative social interactions, choices might change dynamically, as knowledge about the intentions of others and estimates for choice outcomes are incrementally updated via reinforcement learning. Some of the brain circuits utilized during social decision making might be general-purpose and contribute to isomorphic individual and social decision making. By contrast, regions in the medial prefrontal cortex and temporal parietal junction might be recruited for cognitive processes unique to social decision making. PMID:26688301
Development of a robust space power system decision model
NASA Astrophysics Data System (ADS)
Chew, Gilbert; Pelaccio, Dennis G.; Jacobs, Mark; Stancati, Michael; Cataldo, Robert
2001-02-01
NASA continues to evaluate power systems to support human exploration of the Moon and Mars. The system(s) would address all power needs of surface bases and on-board power for space transfer vehicles. Prior studies have examined both solar and nuclear-based alternatives with respect to individual issues such as sizing or cost. What has not been addressed is a comprehensive look at the risks and benefits of the options that could serve as the analytical framework to support a system choice that best serves the needs of the exploration program. This paper describes the SAIC developed Space Power System Decision Model, which uses a formal Two-step Analytical Hierarchy Process (TAHP) methodology that is used in the decision-making process to clearly distinguish candidate power systems in terms of benefits, safety, and risk. TAHP is a decision making process based on the Analytical Hierarchy Process, which employs a hierarchic approach of structuring decision factors by weights, and relatively ranks system design options on a consistent basis. This decision process also includes a level of data gathering and organization that produces a consistent, well-documented assessment, from which the capability of each power system option to meet top-level goals can be prioritized. The model defined on this effort focuses on the comparative assessment candidate power system options for Mars surface application(s). This paper describes the principles of this approach, the assessment criteria and weighting procedures, and the tools to capture and assess the expert knowledge associated with space power system evaluation. .
Conventional Reduced Risk Pesticide Program
Find out about the Conventional Reduced Risk Pesticide Program, which expedites the review and regulatory decision-making process of conventional pesticides that pose less risk to human health and the environment than existing conventional alternatives.
Operator Performance Measures for Assessing Voice Communication Effectiveness
1989-07-01
performance and work- load assessment techniques have been based.I Broadbent (1958) described a limited capacity filter model of human information...INFORMATION PROCESSING 20 3.1.1. Auditory Attention 20 3.1.2. Auditory Memory 24 3.2. MODELS OF INFORMATION PROCESSING 24 3.2.1. Capacity Theories 25...Learning 0 Attention * Language Specialization • Decision Making• Problem Solving Auditory Information Processing Models of Processing Ooemtor
Using Human Factors Methods to Design a New Interface for an Electronic Medical Record
Saleem, Jason J.; Patterson, Emily S.; Militello, Laura; Asch, Steven M.; Doebbeling, Bradley N.; Render, Marta L.
2007-01-01
The Veterans Health Administration (VHA) is a leader in development and use of electronic patient records and clinical decision support. The VHA is currently reengineering a somewhat dated platform for its Computerized Patient Record System (CPRS). This process affords a unique opportunity to implement major changes to the current design and function of the system. We report on two human factors studies designed to provide input and guidance during this reengineering process. One study involved a card sort to better understand how providers tend to cognitively organize clinical data, and how that understanding can help guide interface design. The other involved a simulation to assess the impact of redesign modifications on computerized clinical reminders, a form of clinical decision support in the CPRS, on the learnability of the system for first-time users. PMID:18693914
Managing Research in a Risk World
NASA Technical Reports Server (NTRS)
Anton, W.; Havenhill, M.
2014-01-01
The Office of Chief Medical Officer (OCHMO) owns all human health and performance risks managed by the Human System Risk Board (HSRB). While the HSRB manages the risks, the Human Research Program (HRP) manages the research portion of the overall risk mitigation strategy for these risks. The HSRB manages risks according to a process that identifies and analyzes risks, plans risk mitigation and tracks and reviews the implementation of these strategies according to its decisions pertaining to the OCHMO risk posture. HRP manages risk research work using an architecture that describes evidence-based risks, gaps in our knowledge about characterizing or mitigating the risk, and the tasks needed to produce deliverables to fill the gaps and reduce the risk. A planning schedule reflecting expected research milestones is developed, and as deliverables and new evidence are generated, research progress is tracked via the Path to Risk Reduction (PRR) that reflects a risk's research plan for a design reference mission. HRP's risk research process closely interfaces with the HSRB risk management process. As research progresses, new deliverables and evidence are used by the HSRB in conjunction with other operational and non-research evidence to inform decisions pertaining to the likelihood and consequence of the risk and risk posture. Those decisions in turn guide forward work for research as it contributes to overall risk mitigation strategies. As HRP tracks its research work, it aligns its priorities by assessing the effectiveness of its contributions and maintaining specific core competencies that would be invaluable for future work for exploration missions.
Higher-level fusion for military operations based on abductive inference: proof of principle
NASA Astrophysics Data System (ADS)
Pantaleev, Aleksandar V.; Josephson, John
2006-04-01
The ability of contemporary military commanders to estimate and understand complicated situations already suffers from information overload, and the situation can only grow worse. We describe a prototype application that uses abductive inferencing to fuse information from multiple sensors to evaluate the evidence for higher-level hypotheses that are close to the levels of abstraction needed for decision making (approximately JDL levels 2 and 3). Abductive inference (abduction, inference to the best explanation) is a pattern of reasoning that occurs naturally in diverse settings such as medical diagnosis, criminal investigations, scientific theory formation, and military intelligence analysis. Because abduction is part of common-sense reasoning, implementations of it can produce reasoning traces that are very human understandable. Automated abductive inferencing can be deployed to augment human reasoning, taking advantage of computation to process large amounts of information, and to bypass limits to human attention and short-term memory. We illustrate the workings of the prototype system by describing an example of its use for small-unit military operations in an urban setting. Knowledge was encoded as it might be captured prior to engagement from a standard military decision making process (MDMP) and analysis of commander's priority intelligence requirements (PIR). The system is able to reasonably estimate the evidence for higher-level hypotheses based on information from multiple sensors. Its inference processes can be examined closely to verify correctness. Decision makers can override conclusions at any level and changes will propagate appropriately.
Fuzzy inference game approach to uncertainty in business decisions and market competitions.
Oderanti, Festus Oluseyi
2013-01-01
The increasing challenges and complexity of business environments are making business decisions and operations more difficult for entrepreneurs to predict the outcomes of these processes. Therefore, we developed a decision support scheme that could be used and adapted to various business decision processes. These involve decisions that are made under uncertain situations such as business competition in the market or wage negotiation within a firm. The scheme uses game strategies and fuzzy inference concepts to effectively grasp the variables in these uncertain situations. The games are played between human and fuzzy players. The accuracy of the fuzzy rule base and the game strategies help to mitigate the adverse effects that a business may suffer from these uncertain factors. We also introduced learning which enables the fuzzy player to adapt over time. We tested this scheme in different scenarios and discover that it could be an invaluable tool in the hand of entrepreneurs that are operating under uncertain and competitive business environments.
Capturing the temporal evolution of choice across prefrontal cortex
Hunt, Laurence T; Behrens, Timothy EJ; Hosokawa, Takayuki; Wallis, Jonathan D; Kennerley, Steven W
2015-01-01
Activity in prefrontal cortex (PFC) has been richly described using economic models of choice. Yet such descriptions fail to capture the dynamics of decision formation. Describing dynamic neural processes has proven challenging due to the problem of indexing the internal state of PFC and its trial-by-trial variation. Using primate neurophysiology and human magnetoencephalography, we here recover a single-trial index of PFC internal states from multiple simultaneously recorded PFC subregions. This index can explain the origins of neural representations of economic variables in PFC. It describes the relationship between neural dynamics and behaviour in both human and monkey PFC, directly bridging between human neuroimaging data and underlying neuronal activity. Moreover, it reveals a functionally dissociable interaction between orbitofrontal cortex, anterior cingulate cortex and dorsolateral PFC in guiding cost-benefit decisions. We cast our observations in terms of a recurrent neural network model of choice, providing formal links to mechanistic dynamical accounts of decision-making. DOI: http://dx.doi.org/10.7554/eLife.11945.001 PMID:26653139
Collaborative mining and interpretation of large-scale data for biomedical research insights.
Tsiliki, Georgia; Karacapilidis, Nikos; Christodoulou, Spyros; Tzagarakis, Manolis
2014-01-01
Biomedical research becomes increasingly interdisciplinary and collaborative in nature. Researchers need to efficiently and effectively collaborate and make decisions by meaningfully assembling, mining and analyzing available large-scale volumes of complex multi-faceted data residing in different sources. In line with related research directives revealing that, in spite of the recent advances in data mining and computational analysis, humans can easily detect patterns which computer algorithms may have difficulty in finding, this paper reports on the practical use of an innovative web-based collaboration support platform in a biomedical research context. Arguing that dealing with data-intensive and cognitively complex settings is not a technical problem alone, the proposed platform adopts a hybrid approach that builds on the synergy between machine and human intelligence to facilitate the underlying sense-making and decision making processes. User experience shows that the platform enables more informed and quicker decisions, by displaying the aggregated information according to their needs, while also exploiting the associated human intelligence.
Collaborative Mining and Interpretation of Large-Scale Data for Biomedical Research Insights
Tsiliki, Georgia; Karacapilidis, Nikos; Christodoulou, Spyros; Tzagarakis, Manolis
2014-01-01
Biomedical research becomes increasingly interdisciplinary and collaborative in nature. Researchers need to efficiently and effectively collaborate and make decisions by meaningfully assembling, mining and analyzing available large-scale volumes of complex multi-faceted data residing in different sources. In line with related research directives revealing that, in spite of the recent advances in data mining and computational analysis, humans can easily detect patterns which computer algorithms may have difficulty in finding, this paper reports on the practical use of an innovative web-based collaboration support platform in a biomedical research context. Arguing that dealing with data-intensive and cognitively complex settings is not a technical problem alone, the proposed platform adopts a hybrid approach that builds on the synergy between machine and human intelligence to facilitate the underlying sense-making and decision making processes. User experience shows that the platform enables more informed and quicker decisions, by displaying the aggregated information according to their needs, while also exploiting the associated human intelligence. PMID:25268270
Impaired social decision making in patients with major depressive disorder.
Wang, Yun; Zhou, Yuan; Li, Shu; Wang, Peng; Wu, Guo-Wei; Liu, Zhe-Ning
2014-01-23
Abnormal decision-making processes have been observed in patients with major depressive disorder (MDD). However, it is unresolved whether MDD patients show abnormalities in decision making in a social interaction context, in which decisions have actual influences on both the self-interests of the decision makers per se and those of their partners. Using a well-studied ultimatum game (UG), which is frequently used to investigate social interaction behavior, we examined whether MDD can be associated with abnormalities in social decision-making behavior by comparing the acceptance rates of MDD patients (N = 14) with those of normal controls (N = 19). The acceptance rates of the patients were lower than those of the normal controls. Additionally, unfair proposals were accepted at similar rates from computer partners and human partners in the MDD patients, unlike the acceptance rates in the normal controls, who were able to discriminatively treat unfair proposals from computer partners and human partners. Depressed patients show abnormal decision-making behavior in a social interaction context. Several possible explanations, such as increased sensitivity to fairness, negative emotional state and disturbed affective cognition, have been proposed to account for the abnormal social decision-making behavior in patients with MDD. This aberrant social decision-making behavior may provide a new perspective in the search to find biomarkers for the diagnosis and prognosis of MDD.
Neural mechanisms of human perceptual choice under focused and divided attention.
Wyart, Valentin; Myers, Nicholas E; Summerfield, Christopher
2015-02-25
Perceptual decisions occur after the evaluation and integration of momentary sensory inputs, and dividing attention between spatially disparate sources of information impairs decision performance. However, it remains unknown whether dividing attention degrades the precision of sensory signals, precludes their conversion into decision signals, or dampens the integration of decision information toward an appropriate response. Here we recorded human electroencephalographic (EEG) activity while participants categorized one of two simultaneous and independent streams of visual gratings according to their average tilt. By analyzing trial-by-trial correlations between EEG activity and the information offered by each sample, we obtained converging behavioral and neural evidence that dividing attention between left and right visual fields does not dampen the encoding of sensory or decision information. Under divided attention, momentary decision information from both visual streams was encoded in slow parietal signals without interference but was lost downstream during their integration as reflected in motor mu- and beta-band (10-30 Hz) signals, resulting in a "leaky" accumulation process that conferred greater behavioral influence to more recent samples. By contrast, sensory inputs that were explicitly cued as irrelevant were not converted into decision signals. These findings reveal that a late cognitive bottleneck on information integration limits decision performance under divided attention, and places new capacity constraints on decision-theoretic models of information integration under cognitive load. Copyright © 2015 the authors 0270-6474/15/353485-14$15.00/0.
Neural mechanisms of human perceptual choice under focused and divided attention
Wyart, Valentin; Myers, Nicholas E.; Summerfield, Christopher
2015-01-01
Perceptual decisions occur after evaluation and integration of momentary sensory inputs, and dividing attention between spatially disparate sources of information impairs decision performance. However, it remains unknown whether dividing attention degrades the precision of sensory signals, precludes their conversion into decision signals, or dampens the integration of decision information towards an appropriate response. Here we recorded human electroencephalographic (EEG) activity whilst participants categorised one of two simultaneous and independent streams of visual gratings according to their average tilt. By analyzing trial-by-trial correlations between EEG activity and the information offered by each sample, we obtained converging behavioural and neural evidence that dividing attention between left and right visual fields does not dampen the encoding of sensory or decision information. Under divided attention, momentary decision information from both visual streams was encoded in slow parietal signals without interference but was lost downstream during their integration as reflected in motor mu- and beta-band (10–30 Hz) signals, resulting in a ‘leaky’ accumulation process which conferred greater behavioural influence to more recent samples. By contrast, sensory inputs that were explicitly cued as irrelevant were not converted into decision signals. These findings reveal that a late cognitive bottleneck on information integration limits decision performance under divided attention, and place new capacity constraints on decision-theoretic models of information integration under cognitive load. PMID:25716848
Social modulation of decision-making: a cross-species review
van den Bos, Ruud; Jolles, Jolle W.; Homberg, Judith R.
2013-01-01
Taking decisions plays a pivotal role in daily life and comprises a complex process of assessing and weighing short-term and long-term costs and benefits of competing actions. Decision-making has been shown to be affected by factors such as sex, age, genotype, and personality. Importantly, also the social environment affects decisions, both via social interactions (e.g., social learning, cooperation and competition) and social stress effects. Although everyone is aware of this social modulating role on daily life decisions, this has thus far only scarcely been investigated in human and animal studies. Furthermore, neuroscientific studies rarely discuss social influence on decision-making from a functional perspective such as done in behavioral ecology studies. Therefore, the first aim of this article is to review the available data of the influence of the social context on decision-making both from a causal and functional perspective, drawing on animal and human studies. Also, there is currently still a gap between decision-making in real life where influences of the social environment are extensive, and decision-making as measured in the laboratory, which is often done without any (deliberate) social influences. However, methods are being developed to bridge this gap. Therefore, the second aim of this review is to discuss these methods and ways in which this gap can be increasingly narrowed. We end this review by formulating future research questions. PMID:23805092
Martin, J.; Runge, M.C.; Nichols, J.D.; Lubow, B.C.; Kendall, W.L.
2009-01-01
Thresholds and their relevance to conservation have become a major topic of discussion in the ecological literature. Unfortunately, in many cases the lack of a clear conceptual framework for thinking about thresholds may have led to confusion in attempts to apply the concept of thresholds to conservation decisions. Here, we advocate a framework for thinking about thresholds in terms of a structured decision making process. The purpose of this framework is to promote a logical and transparent process for making informed decisions for conservation. Specification of such a framework leads naturally to consideration of definitions and roles of different kinds of thresholds in the process. We distinguish among three categories of thresholds. Ecological thresholds are values of system state variables at which small changes bring about substantial changes in system dynamics. Utility thresholds are components of management objectives (determined by human values) and are values of state or performance variables at which small changes yield substantial changes in the value of the management outcome. Decision thresholds are values of system state variables at which small changes prompt changes in management actions in order to reach specified management objectives. The approach that we present focuses directly on the objectives of management, with an aim to providing decisions that are optimal with respect to those objectives. This approach clearly distinguishes the components of the decision process that are inherently subjective (management objectives, potential management actions) from those that are more objective (system models, estimates of system state). Optimization based on these components then leads to decision matrices specifying optimal actions to be taken at various values of system state variables. Values of state variables separating different actions in such matrices are viewed as decision thresholds. Utility thresholds are included in the objectives component, and ecological thresholds may be embedded in models projecting consequences of management actions. Decision thresholds are determined by the above-listed components of a structured decision process. These components may themselves vary over time, inducing variation in the decision thresholds inherited from them. These dynamic decision thresholds can then be determined using adaptive management. We provide numerical examples (that are based on patch occupancy models) of structured decision processes that include all three kinds of thresholds. ?? 2009 by the Ecological Society of America.
Dual processing model of medical decision-making
2012-01-01
Background Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. Methods We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. Results We show that physician’s beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker’s threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. Conclusions We have developed the first dual processing model of medical decision-making that has potential to enrich the current medical decision-making field, which is still to the large extent dominated by expected utility theory. The model also provides a platform for reconciling two groups of competing dual processing theories (parallel competitive with default-interventionalist theories). PMID:22943520
Physical Education as a Prerequisite for the Possibility of Human Virtue
ERIC Educational Resources Information Center
Surprenant, Chris W.
2014-01-01
This article examines the role of physical education in the process of moral education, and argues that physical education is a necessary prerequisite for the possibility of human virtue. This discussion is divided into four parts. First, I examine the nature of morality and moral decision-making. Drawing on the moral theories presented by Plato,…
Human Sexuality. A Resource Guide for Parents and Teachers on Teaching...High School Level.
ERIC Educational Resources Information Center
Utah State Office of Education, Salt Lake City.
This guide provides information and resources that will facilitate parents' ability to help adolescents understand human sexuality within the context of home and family values and ideals. It provides teachers with resources to facilitate the decision making process. Contents are organized within a framework of objectives and guidelines for both…
Predicting Adaptive Performance in Multicultural Teams: A Causal Model
2008-02-01
with the requirements of the situation. Such evaluations are referred to as stress appraisals ( Lazarus & Folkman , 1984). Stress appraisals are...and Human Decision Processes, 85, 1-31. [15] Lazarus , R.S., & Folkman , S. (1984). Stress, appraisal, and coping. New York: Springer-Verlag...Amos user’s guide. Chicago: Small Waters. [3] Bar-Tal, Y . (1994). The effect on mundane decision-making of the need and ability to achieve cognitive
ERIC Educational Resources Information Center
Lachman, Seymour P., Ed.
The conference was convened to provide a forum for educators, human rights representatives, and government officials to discuss decision-making processes of local education authorities. The focus of the conference was on the increasing influence on educational policy formation of federal and state court decisions, regulatory agencies, professional…
Climate Change and Socio-Hydrological Dynamics: Adaptations and Feedbacks
NASA Astrophysics Data System (ADS)
Woyessa, Yali E.; Welderufael, Worku A.
2012-10-01
A functioning ecological system results in ecosystem goods and services which are of direct value to human beings. Ecosystem services are the conditions and processes which sustain and fulfil human life, and maintain biodiversity and the production of ecosystem goods. However, human actions affect ecological systems and the services they provide through various activities, such as land use, water use, pollution and climate change. Climate change is perhaps one of the most important sustainable development challenges that threatens to undo many of the development efforts being made to reach the targets set for the Millennium Development Goals. Understanding the provision of ecosystem services and how they change under different scenarios of climate and biophysical conditions could assist in bringing the issue of ecosystem services into decision making process. Similarly, the impacts of land use change on ecosystems and biodiversity have received considerable attention from ecologists and hydrologists alike. Land use change in a catchment can impact on water supply by altering hydrological processes, such as infiltration, groundwater recharge, base flow and direct runoff. In the past a variety of models were used for predicting landuse changes. Recently, the focus has shifted away from using mathematically oriented models to agent-based modeling (ABM) approach to simulate land use scenarios. The agent-based perspective, with regard to land-use cover change, is centered on the general nature and rules of land-use decision making by individuals. A conceptual framework is developed to investigate the possibility of incorporating the human dimension of land use decision and climate change model into a hydrological model in order to assess the impact of future land use scenario and climate change on the ecological system in general and water resources in particular.
Using a Model of Analysts' Judgments to Augment an Item Calibration Process
ERIC Educational Resources Information Center
Hauser, Carl; Thum, Yeow Meng; He, Wei; Ma, Lingling
2015-01-01
When conducting item reviews, analysts evaluate an array of statistical and graphical information to assess the fit of a field test (FT) item to an item response theory model. The process can be tedious, particularly when the number of human reviews (HR) to be completed is large. Furthermore, such a process leads to decisions that are susceptible…
NASA Technical Reports Server (NTRS)
Hale, Mark A.; Craig, James I.; Mistree, Farrokh; Schrage, Daniel P.
1995-01-01
Integrated Product and Process Development (IPPD) embodies the simultaneous application of both system and quality engineering methods throughout an iterative design process. The use of IPPD results in the time-conscious, cost-saving development of engineering systems. Georgia Tech has proposed the development of an Integrated Design Engineering Simulator that will merge Integrated Product and Process Development with interdisciplinary analysis techniques and state-of-the-art computational technologies. To implement IPPD, a Decision-Based Design perspective is encapsulated in an approach that focuses on the role of the human designer in product development. The approach has two parts and is outlined in this paper. First, an architecture, called DREAMS, is being developed that facilitates design from a decision-based perspective. Second, a supporting computing infrastructure, called IMAGE, is being designed. The current status of development is given and future directions are outlined.
Visual Perceptual Learning and Models.
Dosher, Barbara; Lu, Zhong-Lin
2017-09-15
Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision. Models, especially computational models, play a key role in behavioral and physiological investigations of the mechanisms of perceptual learning and for understanding, predicting, and optimizing human perceptual processes, learning, and performance. Performance improvements resulting from reweighting or readout of sensory inputs to decision provide a strong theoretical framework for interpreting perceptual learning and transfer that may prove useful in optimizing learning in real-world applications.
[Limits of intensive care--decision making on the way between life and death].
Uehlinger-Walter, J
1994-05-03
Survival and death are closely related in intensive-care medicine. Both have to be accepted and accounted for when decisions have to be made and activity is required. Only then a sound and truthful process of decision-making is guaranteed. Both, the experienced as well as the novice, need guidelines in this process. The basis of these guidelines lies in quite different aspects of life: juridical, philosophic-ethical and religious. The first part of this paper focuses on the specific setting of neonatal intensive care. Three issues must be considered: The patient is not the direct partner in conversation; illness and its consequences have an impact on the social network of the whole family; mothers quite often suffer from severe guilt feelings, which have to be understood and addressed. The second part describes the essential elements of support on the journey' between life and death. They can be summarized under seven headings: urgent acquisition of all necessary data; the need for medical intervention before optimal level of relevant information is available; the importance of allowing for human time factors; the process of arriving at certain decisions; the dealing with unexpected changes in the course and development of the disease; the cessation of therapy; the parental support in bereavement. The overall emphasis of medical intervention should be to view the patient as human being, not as a treatable subject amongst a setting of numerous medical intervention techniques.
Healthcare justice and human rights in perinatal medicine.
Chervenak, Frank A; McCullough, Laurence B
2016-06-01
This article describes an approach to ethics of perinatal medicine in which "women and children first" plays a central role, based on the concept of healthcare justice. Healthcare justice requires that all patients receive clinical management based on their clinical needs, which are defined by deliberative (evidence-based, rigorous, transparent, and accountable) clinical judgment. All patients in perinatal medicine includes pregnant, fetal, and neonatal patients. Healthcare justice also protects the informed consent process, which is intended to empower the exercise of patient autonomy in the decision-making process about patient care. In the context of healthcare justice, the informed consent process should not be influenced by ethically irrelevant factors. Healthcare justice should be understood as a basis for the human rights to healthcare and to participate in decisions about one's healthcare. Healthcare justice in perinatal medicine creates an essential role for the perinatologist to be an effective advocate for pregnant, fetal, and neonatal patients, i.e., for "women and children first." Copyright © 2016 Elsevier Inc. All rights reserved.
A model of pathways to artificial superintelligence catastrophe for risk and decision analysis
NASA Astrophysics Data System (ADS)
Barrett, Anthony M.; Baum, Seth D.
2017-03-01
An artificial superintelligence (ASI) is an artificial intelligence that is significantly more intelligent than humans in all respects. Whilst ASI does not currently exist, some scholars propose that it could be created sometime in the future, and furthermore that its creation could cause a severe global catastrophe, possibly even resulting in human extinction. Given the high stakes, it is important to analyze ASI risk and factor the risk into decisions related to ASI research and development. This paper presents a graphical model of major pathways to ASI catastrophe, focusing on ASI created via recursive self-improvement. The model uses the established risk and decision analysis modelling paradigms of fault trees and influence diagrams in order to depict combinations of events and conditions that could lead to AI catastrophe, as well as intervention options that could decrease risks. The events and conditions include select aspects of the ASI itself as well as the human process of ASI research, development and management. Model structure is derived from published literature on ASI risk. The model offers a foundation for rigorous quantitative evaluation and decision-making on the long-term risk of ASI catastrophe.
Semantic Clinical Guideline Documents
Eriksson, Henrik; Tu, Samson W.; Musen, Mark
2005-01-01
Decision-support systems based on clinical practice guidelines can support physicians and other health-care personnel in the process of following best practice consistently. A knowledge-based approach to represent guidelines makes it possible to encode computer-interpretable guidelines in a formal manner, perform consistency checks, and use the guidelines directly in decision-support systems. Decision-support authors and guideline users require guidelines in human-readable formats in addition to computer-interpretable ones (e.g., for guideline review and quality assurance). We propose a new document-oriented information architecture that combines knowledge-representation models with electronic and paper documents. The approach integrates decision-support modes with standard document formats to create a combined clinical-guideline model that supports on-line viewing, printing, and decision support. PMID:16779037
Emotion-based decision-making in healthy subjects: short-term effects of reducing dopamine levels
Sevy, Serge; Hassoun, Youssef; Bechara, Antoine; Yechiam, Eldad; Napolitano, Barbara; Burdick, Katherine; Delman, Howard; Malhotra, Anil
2007-01-01
Introduction Converging evidences from animal and human studies suggest that addiction is associated with dopaminergic dysfunction in brain reward circuits. So far, it is unclear what aspects of addictive behaviors are related to a dopaminergic dysfunction. Discussion We hypothesize that a decrease in dopaminergic activity impairs emotion-based decision-making. To demonstrate this hypothesis, we investigated the effects of a decrease in dopaminergic activity on the performance of an emotion-based decision-making task, the Iowa gambling task (IGT), in 11 healthy human subjects. Materials and methods We used a double-blind, placebo-controlled, within-subject design to examine the effect of a mixture containing the branched-chain amino acids (BCAA) valine, isoleucine and leucine on prolactin, IGT performance, perceptual competency and visual aspects of visuospatial working memory, visual attention and working memory, and verbal memory. The expectancy-valence model was used to determine the relative contributions of distinct IGT components (attention to past outcomes, relative weight of wins and losses, and choice strategies) in the decision-making process. Observations and results Compared to placebo, the BCAA mixture increased prolactin levels and impaired IGT performance. BCAA administration interfered with a particular component process of decision-making related to attention to more recent events as compared to more distant events. There were no differences between placebo and BCAA conditions for other aspects of cognition. Our results suggest a direct link between a reduced dopaminergic activity and poor emotion-based decision-making characterized by shortsightedness, and thus difficulties resisting short-term reward, despite long-term negative consequences. These findings have implications for behavioral and pharmacological interventions targeting impaired emotion-based decision-making in addictive disorders. PMID:16915385
Harvey, Olivia
2005-01-01
Over 12 months prior to the recent United Nations decision to defer a decision about what type of international treaty should be developed in the global stem-cell research and human cloning debate, the Federal Parliament of Australia passed two separate pieces of legislation relating to both these concerns. After a five-year long process of community consultation, media spectacle and parliamentary debate, reproductive cloning has been banned in Australia and only embryos considered to be excess to assisted reproductive technologies in existence on the 5th of April 2002 are currently valid research material. This paper argues that underpinning both pieces of legislation is a profound belief in the disruptive potential of all types of human cloning for the very nature and integrity of human species being. A belief, moreover, that is based on a presumption that it is apparently possible to conceptualise what being human even means for all Australians.
Fuzzy MCDM Technique for Planning the Environment Watershed
NASA Astrophysics Data System (ADS)
Chen, Yi-Chun; Lien, Hui-Pang; Tzeng, Gwo-Hshiung; Yang, Lung-Shih; Yen, Leon
In the real word, the decision making problems are very vague and uncertain in a number of ways. The most criteria have interdependent and interactive features so they cannot be evaluated by conventional measures method. Such as the feasibility, thus, to approximate the human subjective evaluation process, it would be more suitable to apply a fuzzy method in environment-watershed plan topic. This paper describes the design of a fuzzy decision support system in multi-criteria analysis approach for selecting the best plan alternatives or strategies in environmentwatershed. The Fuzzy Analytic Hierarchy Process (FAHP) method is used to determine the preference weightings of criteria for decision makers by subjective perception. A questionnaire was used to find out from three related groups comprising fifteen experts. Subjectivity and vagueness analysis is dealt with the criteria and alternatives for selection process and simulation results by using fuzzy numbers with linguistic terms. Incorporated the decision makers’ attitude towards preference, overall performance value of each alternative can be obtained based on the concept of Fuzzy Multiple Criteria Decision Making (FMCDM). This research also gives an example of evaluating consisting of five alternatives, solicited from a environmentwatershed plan works in Taiwan, is illustrated to demonstrate the effectiveness and usefulness of the proposed approach.
Hales, Claire A; Robinson, Emma S J; Houghton, Conor J
2016-01-01
Human decision making is modified by emotional state. Rodents exhibit similar biases during interpretation of ambiguous cues that can be altered by affective state manipulations. In this study, the impact of negative affective state on judgement bias in rats was measured using an ambiguous-cue interpretation task. Acute treatment with an anxiogenic drug (FG7142), and chronic restraint stress and social isolation both induced a bias towards more negative interpretation of the ambiguous cue. The diffusion model was fit to behavioural data to allow further analysis of the underlying decision making processes. To uncover the way in which parameters vary together in relation to affective state manipulations, independent component analysis was conducted on rate of information accumulation and distances to decision threshold parameters for control data. Results from this analysis were applied to parameters from negative affective state manipulations. These projected components were compared to control components to reveal the changes in decision making processes that are due to affective state manipulations. Negative affective bias in rodents induced by either FG7142 or chronic stress is due to a combination of more negative interpretation of the ambiguous cue, reduced anticipation of the high reward and increased anticipation of the low reward.
Smaldino, Paul E; Richerson, Peter J
2012-01-01
Most research on decision making has focused on how human or animal decision makers choose between two or more options, posed in advance by the researchers. The mechanisms by which options are generated for most decisions, however, are not well understood. Models of sequential search have examined the trade-off between continued exploration and choosing one's current best option, but still cannot explain the processes by which new options are generated. We argue that understanding the origins of options is a crucial but untapped area for decision making research. We explore a number of factors which influence the generation of options, which fall broadly into two categories: psycho-biological and socio-cultural. The former category includes factors such as perceptual biases and associative memory networks. The latter category relies on the incredible human capacity for culture and social learning, which doubtless shape not only our choices but the options available for choice. Our intention is to start a discussion that brings us closer toward understanding the origins of options.
The chronometry of risk processing in the human cortex
Symmonds, Mkael; Moran, Rosalyn J.; Wright, Nicholas D.; Bossaerts, Peter; Barnes, Gareth; Dolan, Raymond J.
2013-01-01
The neuroscience of human decision-making has focused on localizing brain activity correlating with decision variables and choice, most commonly using functional MRI (fMRI). Poor temporal resolution means these studies are agnostic in relation to how decisions unfold in time. Consequently, here we address the temporal evolution of neural activity related to encoding of risk using magnetoencephalography (MEG), and show modulations of electromagnetic power in posterior parietal and dorsomedial prefrontal cortex (DMPFC) which scale with both variance and skewness in a lottery, detectable within 500 ms following stimulus presentation. Electromagnetic responses in somatosensory cortex following this risk encoding predict subsequent choices. Furthermore, within anterior insula we observed early and late effects of subject-specific risk preferences, suggestive of a role in both risk assessment and risk anticipation during choice. The observation that cortical activity tracks specific and independent components of risk from early time-points in a decision-making task supports the hypothesis that specialized brain circuitry underpins risk perception. PMID:23970849
Smaldino, Paul E.; Richerson, Peter J.
2012-01-01
Most research on decision making has focused on how human or animal decision makers choose between two or more options, posed in advance by the researchers. The mechanisms by which options are generated for most decisions, however, are not well understood. Models of sequential search have examined the trade-off between continued exploration and choosing one’s current best option, but still cannot explain the processes by which new options are generated. We argue that understanding the origins of options is a crucial but untapped area for decision making research. We explore a number of factors which influence the generation of options, which fall broadly into two categories: psycho-biological and socio-cultural. The former category includes factors such as perceptual biases and associative memory networks. The latter category relies on the incredible human capacity for culture and social learning, which doubtless shape not only our choices but the options available for choice. Our intention is to start a discussion that brings us closer toward understanding the origins of options. PMID:22514515
Localized microstimulation of primate pregenual cingulate cortex induces negative decision-making.
Amemori, Ken-ichi; Graybiel, Ann M
2012-05-01
The pregenual anterior cingulate cortex (pACC) has been implicated in human anxiety disorders and depression, but the circuit-level mechanisms underlying these disorders are unclear. In healthy individuals, the pACC is involved in cost-benefit evaluation. We developed a macaque version of an approach-avoidance decision task used to evaluate anxiety and depression in humans and, with multi-electrode recording and cortical microstimulation, we probed pACC function as monkeys performed this task. We found that the macaque pACC has an opponent process-like organization of neurons representing motivationally positive and negative subjective value. Spatial distribution of these two neuronal populations overlapped in the pACC, except in one subzone, where neurons with negative coding were more numerous. Notably, microstimulation in this subzone, but not elsewhere in the pACC, increased negative decision-making, and this negative biasing was blocked by anti-anxiety drug treatment. This cortical zone could be critical for regulating negative emotional valence and anxiety in decision-making.
Kishida, Kenneth T.; Saez, Ignacio; Lohrenz, Terry; Witcher, Mark R.; Laxton, Adrian W.; Tatter, Stephen B.; White, Jason P.; Ellis, Thomas L.; Phillips, Paul E. M.; Montague, P. Read
2016-01-01
In the mammalian brain, dopamine is a critical neuromodulator whose actions underlie learning, decision-making, and behavioral control. Degeneration of dopamine neurons causes Parkinson’s disease, whereas dysregulation of dopamine signaling is believed to contribute to psychiatric conditions such as schizophrenia, addiction, and depression. Experiments in animal models suggest the hypothesis that dopamine release in human striatum encodes reward prediction errors (RPEs) (the difference between actual and expected outcomes) during ongoing decision-making. Blood oxygen level-dependent (BOLD) imaging experiments in humans support the idea that RPEs are tracked in the striatum; however, BOLD measurements cannot be used to infer the action of any one specific neurotransmitter. We monitored dopamine levels with subsecond temporal resolution in humans (n = 17) with Parkinson’s disease while they executed a sequential decision-making task. Participants placed bets and experienced monetary gains or losses. Dopamine fluctuations in the striatum fail to encode RPEs, as anticipated by a large body of work in model organisms. Instead, subsecond dopamine fluctuations encode an integration of RPEs with counterfactual prediction errors, the latter defined by how much better or worse the experienced outcome could have been. How dopamine fluctuations combine the actual and counterfactual is unknown. One possibility is that this process is the normal behavior of reward processing dopamine neurons, which previously had not been tested by experiments in animal models. Alternatively, this superposition of error terms may result from an additional yet-to-be-identified subclass of dopamine neurons. PMID:26598677
Kishida, Kenneth T; Saez, Ignacio; Lohrenz, Terry; Witcher, Mark R; Laxton, Adrian W; Tatter, Stephen B; White, Jason P; Ellis, Thomas L; Phillips, Paul E M; Montague, P Read
2016-01-05
In the mammalian brain, dopamine is a critical neuromodulator whose actions underlie learning, decision-making, and behavioral control. Degeneration of dopamine neurons causes Parkinson's disease, whereas dysregulation of dopamine signaling is believed to contribute to psychiatric conditions such as schizophrenia, addiction, and depression. Experiments in animal models suggest the hypothesis that dopamine release in human striatum encodes reward prediction errors (RPEs) (the difference between actual and expected outcomes) during ongoing decision-making. Blood oxygen level-dependent (BOLD) imaging experiments in humans support the idea that RPEs are tracked in the striatum; however, BOLD measurements cannot be used to infer the action of any one specific neurotransmitter. We monitored dopamine levels with subsecond temporal resolution in humans (n = 17) with Parkinson's disease while they executed a sequential decision-making task. Participants placed bets and experienced monetary gains or losses. Dopamine fluctuations in the striatum fail to encode RPEs, as anticipated by a large body of work in model organisms. Instead, subsecond dopamine fluctuations encode an integration of RPEs with counterfactual prediction errors, the latter defined by how much better or worse the experienced outcome could have been. How dopamine fluctuations combine the actual and counterfactual is unknown. One possibility is that this process is the normal behavior of reward processing dopamine neurons, which previously had not been tested by experiments in animal models. Alternatively, this superposition of error terms may result from an additional yet-to-be-identified subclass of dopamine neurons.
Decision-Making in the Ventral Premotor Cortex Harbinger of Action
Pardo-Vazquez, Jose L.; Padron, Isabel; Fernandez-Rey, Jose; Acuña, Carlos
2011-01-01
Although the premotor (PM) cortex was once viewed as the substrate of pure motor functions, soon it was realized that it was involved in higher brain functions. By this it is meant that the PM cortex functions would better be explained as motor set, preparation for limb movement, or sensory guidance of movement rather than solely by a fixed link to motor performance. These findings, together with a better knowledge of the PM cortex histology and hodology in human and non-human primates prompted quantitative studies of this area combining behavioral tasks with electrophysiological recordings. In addition, the exploration of the PM cortex neurons with qualitative methods also suggested its participation in higher functions. Behavioral choices frequently depend on temporal cues, which together with knowledge of previous outcomes and expectancies are combined to decide and choose a behavioral action. In decision-making the knowledge about the consequences of decisions, either correct or incorrect, is fundamental because they can be used to adapt future behavior. The neuronal correlates of a decision process have been described in several cortical areas of primates. Among them, there is evidence that the monkey ventral premotor (PMv) cortex, an anatomical and physiological well-differentiated area of the PM cortex, supports both perceptual decisions and performance monitoring. Here we review the evidence that the steps in a decision-making process are encoded in the firing rate of the PMv neurons. This provides compelling evidence suggesting that the PMv is involved in the use of recent and long-term sensory memory to decide, execute, and evaluate the outcomes of the subjects’ choices. PMID:21991249
NASA Astrophysics Data System (ADS)
Babbar-Sebens, M.; Minsker, B. S.
2006-12-01
In the water resources management field, decision making encompasses many kinds of engineering, social, and economic constraints and objectives. Representing all of these problem dependant criteria through models (analytical or numerical) and various formulations (e.g., objectives, constraints, etc.) within an optimization- simulation system can be a very non-trivial issue. Most models and formulations utilized for discerning desirable traits in a solution can only approximate the decision maker's (DM) true preference criteria, and they often fail to consider important qualitative and incomputable phenomena related to the management problem. In our research, we have proposed novel decision support frameworks that allow DMs to actively participate in the optimization process. The DMs explicitly indicate their true preferences based on their subjective criteria and the results of various simulation models and formulations. The feedback from the DMs is then used to guide the search process towards solutions that are "all-rounders" from the perspective of the DM. The two main research questions explored in this work are: a) Does interaction between the optimization algorithm and a DM assist the system in searching for groundwater monitoring designs that are robust from the DM's perspective?, and b) How can an interactive search process be made more effective when human factors, such as human fatigue and cognitive learning processes, affect the performance of the algorithm? The application of these frameworks on a real-world groundwater long-term monitoring (LTM) case study in Michigan highlighted the following salient advantages: a) in contrast to the non-interactive optimization methodology, the proposed interactive frameworks were able to identify low cost monitoring designs whose interpolation maps respected the expected spatial distribution of the contaminants, b) for many same-cost designs, the interactive methodologies were able to propose multiple alternatives that met the DM's preference criteria, therefore allowing the expert to select among several strong candidate designs depending on her/his LTM budget, c) two of the methodologies - Case-Based Micro Interactive Genetic Algorithm (CBMIGA) and Interactive Genetic Algorithm with Mixed Initiative Interaction (IGAMII) - were also able to assist in controlling human fatigue and adapt to the DM's learning process.
The Role of Human Expertise in Enhancing Data Mining
ERIC Educational Resources Information Center
Kaddouri, Abdelaaziz
2011-01-01
Current data mining (DM) technology is not domain-specific and therefore rarely generates reliable, business actionable knowledge that can be used to improve the effectiveness of the decision-making process in the banking industry. DM is mainly an autonomous, data-driven process with little focus on domain expertise, constraints, or requirements…
Expediting the Institutional Review Board Process for Exercise Protocols
ERIC Educational Resources Information Center
Macfarlane, Pamela A.; Looney, Marilyn A.
2011-01-01
All researchers who use human participants in their study must obtain permission from their appropriate Institutional Review Board (IRB). Once the IRB application enters the review process, a decision is made regarding the type of review it should receive: Level I administrative (exempt), Level II subcommittee (expedited), or Level III full board…
Do we care about the powerless third? An ERP study of the three-person ultimatum game
Alexopoulos, Johanna; Pfabigan, Daniela M.; Lamm, Claus; Bauer, Herbert; Fischmeister, Florian Ph. S.
2012-01-01
Recent years have provided increasing insights into the factors affecting economic decision-making. Little is known about how these factors influence decisions that also bear consequences for other people. We examined whether decisions that also affected a third, passive player modulate the behavioral and neural responses to monetary offers in a modified version of the three-person ultimatum game. We aimed to elucidate to what extent social preferences affect early neuronal processing when subjects were evaluating offers that were fair or unfair to themselves, to the third player, or to both. As an event-related potential (ERP) index for early evaluation processes in economic decision-making, we recorded the medial frontal negativity (MFN) component in response to such offers. Unfair offers were rejected more often than equitable ones, in particular when negatively affecting the subject. While the MFN amplitude was higher following unfair as compared to fair offers to the subject, MFN amplitude was not modulated by the shares assigned to the third, passive player. Furthermore, rejection rates and MFN amplitudes following fair offers were positively correlated, as subjects showing lower MFN amplitudes following fair offers tended to reject unfair offers more often—but only if those offers negatively affected their own payoff. Altogether, the rejection behavior suggests that humans mainly care about a powerless third when they are confronted with inequality as well. The correlation between rejection rates and the MFN amplitude supports the notion that this ERP component is also modulated by positive events and highlights how our expectations concerning other humans' behavior guide our own decisions. However, social preferences like inequality aversion and concern for the well-being of others are not reflected in this early neuronal response, but seem to result from later, deliberate and higher-order cognitive processes. PMID:22470328
Do we care about the powerless third? An ERP study of the three-person ultimatum game.
Alexopoulos, Johanna; Pfabigan, Daniela M; Lamm, Claus; Bauer, Herbert; Fischmeister, Florian Ph S
2012-01-01
Recent years have provided increasing insights into the factors affecting economic decision-making. Little is known about how these factors influence decisions that also bear consequences for other people. We examined whether decisions that also affected a third, passive player modulate the behavioral and neural responses to monetary offers in a modified version of the three-person ultimatum game. We aimed to elucidate to what extent social preferences affect early neuronal processing when subjects were evaluating offers that were fair or unfair to themselves, to the third player, or to both. As an event-related potential (ERP) index for early evaluation processes in economic decision-making, we recorded the medial frontal negativity (MFN) component in response to such offers. Unfair offers were rejected more often than equitable ones, in particular when negatively affecting the subject. While the MFN amplitude was higher following unfair as compared to fair offers to the subject, MFN amplitude was not modulated by the shares assigned to the third, passive player. Furthermore, rejection rates and MFN amplitudes following fair offers were positively correlated, as subjects showing lower MFN amplitudes following fair offers tended to reject unfair offers more often-but only if those offers negatively affected their own payoff. Altogether, the rejection behavior suggests that humans mainly care about a powerless third when they are confronted with inequality as well. The correlation between rejection rates and the MFN amplitude supports the notion that this ERP component is also modulated by positive events and highlights how our expectations concerning other humans' behavior guide our own decisions. However, social preferences like inequality aversion and concern for the well-being of others are not reflected in this early neuronal response, but seem to result from later, deliberate and higher-order cognitive processes.
Adaptive self-organization of Bali's ancient rice terraces.
Lansing, J Stephen; Thurner, Stefan; Chung, Ning Ning; Coudurier-Curveur, Aurélie; Karakaş, Çağil; Fesenmyer, Kurt A; Chew, Lock Yue
2017-06-20
Spatial patterning often occurs in ecosystems as a result of a self-organizing process caused by feedback between organisms and the physical environment. Here, we show that the spatial patterns observable in centuries-old Balinese rice terraces are also created by feedback between farmers' decisions and the ecology of the paddies, which triggers a transition from local to global-scale control of water shortages and rice pests. We propose an evolutionary game, based on local farmers' decisions that predicts specific power laws in spatial patterning that are also seen in a multispectral image analysis of Balinese rice terraces. The model shows how feedbacks between human decisions and ecosystem processes can evolve toward an optimal state in which total harvests are maximized and the system approaches Pareto optimality. It helps explain how multiscale cooperation from the community to the watershed scale could persist for centuries, and why the disruption of this self-organizing system by the Green Revolution caused chaos in irrigation and devastating losses from pests. The model shows that adaptation in a coupled human-natural system can trigger self-organized criticality (SOC). In previous exogenously driven SOC models, adaptation plays no role, and no optimization occurs. In contrast, adaptive SOC is a self-organizing process where local adaptations drive the system toward local and global optima.
2012-06-01
THIS PAGE INTENTIONALLY LEFT BLANK xv LIST OF ACRONYMS AND ABBREVIATIONS BPM Business Process Model BPMN Business Process Modeling Notation C&A...checking leads to an improvement in the quality and success of enterprise software development. Business Process Modeling Notation ( BPMN ) is an...emerging standard that allows business processes to be captured in a standardized format. BPMN lacks formal semantics which leaves many of its features
Parents' involvement in the human papillomavirus vaccination decision for their sons.
Perez, Samara; Restle, Hannah; Naz, Anila; Tatar, Ovidiu; Shapiro, Gilla K; Rosberger, Zeev
2017-12-01
Parents are critical to ensure sufficient human papillomavirus (HPV) vaccine coverage. No studies to date have examined how mothers and fathers perceive their own, their partners' and their sons' involvement in HPV vaccination decision-making process. An online survey methodology was used to collect data from a national sample of Canadian parents (33% fathers, 67% mothers, M age =44) who had a 9-16years old son (n=3117). Parent's perception of their self-involvement, partner-involvement and son's involvement in the decision to get their son the HPV vaccine were measured on a Likert scale and were classified as 'no involvement', 'moderate involvement' and 'high involvement'. Mothers and fathers both perceive that they themselves and their partners should be highly involved in their son's HPV vaccination decision. Son's involvement was reported as moderate and influenced by age. Significant gender differences were found for self and partner involvement, but the effect sizes were small. Mothers and fathers both perceive that they themselves and their partners should be significantly involved in their son's HPV vaccination decision. A dyad decision-making model involving both parents for HPV vaccine decision-making is suggested with a stronger recommendation for a triad decision-making model involving both parents as well as the child/adolescent. Gender stereotypes of females perceiving themselves as the sole decision-maker or fathers not wanting to be involved in their children's health decision were not supported. Copyright © 2017 Elsevier B.V. All rights reserved.
The Neural Basis of Aversive Pavlovian Guidance during Planning
Faulkner, Paul
2017-01-01
Important real-world decisions are often arduous as they frequently involve sequences of choices, with initial selections affecting future options. Evaluating every possible combination of choices is computationally intractable, particularly for longer multistep decisions. Therefore, humans frequently use heuristics to reduce the complexity of decisions. We recently used a goal-directed planning task to demonstrate the profound behavioral influence and ubiquity of one such shortcut, namely aversive pruning, a reflexive Pavlovian process that involves neglecting parts of the decision space residing beyond salient negative outcomes. However, how the brain implements this important decision heuristic and what underlies individual differences have hitherto remained unanswered. Therefore, we administered an adapted version of the same planning task to healthy male and female volunteers undergoing functional magnetic resonance imaging (fMRI) to determine the neural basis of aversive pruning. Through both computational and standard categorical fMRI analyses, we show that when planning was influenced by aversive pruning, the subgenual cingulate cortex was robustly recruited. This neural signature was distinct from those associated with general planning and valuation, two fundamental cognitive components elicited by our task but which are complementary to aversive pruning. Furthermore, we found that individual variation in levels of aversive pruning was associated with the responses of insula and dorsolateral prefrontal cortices to the receipt of large monetary losses, and also with subclinical levels of anxiety. In summary, our data reveal the neural signatures of an important reflexive Pavlovian process that shapes goal-directed evaluations and thereby determines the outcome of high-level sequential cognitive processes. SIGNIFICANCE STATEMENT Multistep decisions are complex because initial choices constrain future options. Evaluating every path for long decision sequences is often impractical; thus, cognitive shortcuts are often essential. One pervasive and powerful heuristic is aversive pruning, in which potential decision-making avenues are curtailed at immediate negative outcomes. We used neuroimaging to examine how humans implement such pruning. We found it to be associated with activity in the subgenual cingulate cortex, with neural signatures that were distinguishable from those covarying with planning and valuation. Individual variations in aversive pruning levels related to subclinical anxiety levels and insular cortex activation. These findings reveal the neural mechanisms by which basic negative Pavlovian influences guide decision-making during planning, with implications for disrupted decision-making in psychiatric disorders. PMID:28924006
The Neural Basis of Aversive Pavlovian Guidance during Planning.
Lally, Níall; Huys, Quentin J M; Eshel, Neir; Faulkner, Paul; Dayan, Peter; Roiser, Jonathan P
2017-10-18
Important real-world decisions are often arduous as they frequently involve sequences of choices, with initial selections affecting future options. Evaluating every possible combination of choices is computationally intractable, particularly for longer multistep decisions. Therefore, humans frequently use heuristics to reduce the complexity of decisions. We recently used a goal-directed planning task to demonstrate the profound behavioral influence and ubiquity of one such shortcut, namely aversive pruning, a reflexive Pavlovian process that involves neglecting parts of the decision space residing beyond salient negative outcomes. However, how the brain implements this important decision heuristic and what underlies individual differences have hitherto remained unanswered. Therefore, we administered an adapted version of the same planning task to healthy male and female volunteers undergoing functional magnetic resonance imaging (fMRI) to determine the neural basis of aversive pruning. Through both computational and standard categorical fMRI analyses, we show that when planning was influenced by aversive pruning, the subgenual cingulate cortex was robustly recruited. This neural signature was distinct from those associated with general planning and valuation, two fundamental cognitive components elicited by our task but which are complementary to aversive pruning. Furthermore, we found that individual variation in levels of aversive pruning was associated with the responses of insula and dorsolateral prefrontal cortices to the receipt of large monetary losses, and also with subclinical levels of anxiety. In summary, our data reveal the neural signatures of an important reflexive Pavlovian process that shapes goal-directed evaluations and thereby determines the outcome of high-level sequential cognitive processes. SIGNIFICANCE STATEMENT Multistep decisions are complex because initial choices constrain future options. Evaluating every path for long decision sequences is often impractical; thus, cognitive shortcuts are often essential. One pervasive and powerful heuristic is aversive pruning, in which potential decision-making avenues are curtailed at immediate negative outcomes. We used neuroimaging to examine how humans implement such pruning. We found it to be associated with activity in the subgenual cingulate cortex, with neural signatures that were distinguishable from those covarying with planning and valuation. Individual variations in aversive pruning levels related to subclinical anxiety levels and insular cortex activation. These findings reveal the neural mechanisms by which basic negative Pavlovian influences guide decision-making during planning, with implications for disrupted decision-making in psychiatric disorders. Copyright © 2017 the authors 0270-6474/17/3710216-15$15.00/0.
Leimbach, Friederike; Georgiev, Dejan; Litvak, Vladimir; Antoniades, Chrystalina; Limousin, Patricia; Jahanshahi, Marjan; Bogacz, Rafal
2018-06-01
During a decision process, the evidence supporting alternative options is integrated over time, and the choice is made when the accumulated evidence for one of the options reaches a decision threshold. Humans and animals have an ability to control the decision threshold, that is, the amount of evidence that needs to be gathered to commit to a choice, and it has been proposed that the subthalamic nucleus (STN) is important for this control. Recent behavioral and neurophysiological data suggest that, in some circumstances, the decision threshold decreases with time during choice trials, allowing overcoming of indecision during difficult choices. Here we asked whether this within-trial decrease of the decision threshold is mediated by the STN and if it is affected by disrupting information processing in the STN through deep brain stimulation (DBS). We assessed 13 patients with Parkinson disease receiving bilateral STN DBS six or more months after the surgery, 11 age-matched controls, and 12 young healthy controls. All participants completed a series of decision trials, in which the evidence was presented in discrete time points, which allowed more direct estimation of the decision threshold. The participants differed widely in the slope of their decision threshold, ranging from constant threshold within a trial to steeply decreasing. However, the slope of the decision threshold did not depend on whether STN DBS was switched on or off and did not differ between the patients and controls. Furthermore, there was no difference in accuracy and RT between the patients in the on and off stimulation conditions and healthy controls. Previous studies that have reported modulation of the decision threshold by STN DBS or unilateral subthalamotomy in Parkinson disease have involved either fast decision-making under conflict or time pressure or in anticipation of high reward. Our findings suggest that, in the absence of reward, decision conflict, or time pressure for decision-making, the STN does not play a critical role in modulating the within-trial decrease of decision thresholds during the choice process.
Soliciting scientific information and beliefs in predictive modeling and adaptive management
NASA Astrophysics Data System (ADS)
Glynn, P. D.; Voinov, A. A.; Shapiro, C. D.
2015-12-01
Post-normal science requires public engagement and adaptive corrections in addressing issues with high complexity and uncertainty. An adaptive management framework is presented for the improved management of natural resources and environments through a public participation process. The framework solicits the gathering and transformation and/or modeling of scientific information but also explicitly solicits the expression of participant beliefs. Beliefs and information are compared, explicitly discussed for alignments or misalignments, and ultimately melded back together as a "knowledge" basis for making decisions. An effort is made to recognize the human or participant biases that may affect the information base and the potential decisions. In a separate step, an attempt is made to recognize and predict the potential "winners" and "losers" (perceived or real) of any decision or action. These "winners" and "losers" include present human communities with different spatial, demographic or socio-economic characteristics as well as more dispersed or more diffusely characterized regional or global communities. "Winners" and "losers" may also include future human communities as well as communities of other biotic species. As in any adaptive management framework, assessment of predictions, iterative follow-through and adaptation of policies or actions is essential, and commonly very difficult or impossible to achieve. Recognizing beforehand the limits of adaptive management is essential. More generally, knowledge of the behavioral and economic sciences and of ethics and sociology will be key to a successful implementation of this adaptive management framework. Knowledge of biogeophysical processes will also be essential, but by definition of the issues being addressed, will always be incomplete and highly uncertain. The human dimensions of the issues addressed and the participatory processes used carry their own complexities and uncertainties. Some ideas and principles are provided that may help guide and implement the proposed adaptive management framework and its public and stakeholder engagement processes. Examples and characteristics of issues that could be beneficially addressed through the proposed framework will also be presented.
Bornstein, Aaron M.; Daw, Nathaniel D.
2013-01-01
How do we use our memories of the past to guide decisions we've never had to make before? Although extensive work describes how the brain learns to repeat rewarded actions, decisions can also be influenced by associations between stimuli or events not directly involving reward — such as when planning routes using a cognitive map or chess moves using predicted countermoves — and these sorts of associations are critical when deciding among novel options. This process is known as model-based decision making. While the learning of environmental relations that might support model-based decisions is well studied, and separately this sort of information has been inferred to impact decisions, there is little evidence concerning the full cycle by which such associations are acquired and drive choices. Of particular interest is whether decisions are directly supported by the same mnemonic systems characterized for relational learning more generally, or instead rely on other, specialized representations. Here, building on our previous work, which isolated dual representations underlying sequential predictive learning, we directly demonstrate that one such representation, encoded by the hippocampal memory system and adjacent cortical structures, supports goal-directed decisions. Using interleaved learning and decision tasks, we monitor predictive learning directly and also trace its influence on decisions for reward. We quantitatively compare the learning processes underlying multiple behavioral and fMRI observables using computational model fits. Across both tasks, a quantitatively consistent learning process explains reaction times, choices, and both expectation- and surprise-related neural activity. The same hippocampal and ventral stream regions engaged in anticipating stimuli during learning are also engaged in proportion to the difficulty of decisions. These results support a role for predictive associations learned by the hippocampal memory system to be recalled during choice formation. PMID:24339770
Kim, Kkotbong; Yang, Jinhyang
2017-06-01
After being diagnosed with breast cancer, women must make a number of decisions about their treatment and management. When the decision-making process among breast cancer patients is ineffective, it results in harm to their health. Little is known about the decision-making process of breast cancer patients during the entire course of treatment and management. We investigated women with breast cancer to explore the decision-making processes related to treatment and management. Eleven women participated, all of whom were receiving treatment or management in Korea. The average participant age was 43.5years. For data collection and analysis, a grounded theory methodology was used. Through constant comparative analyses, a core category emerged that we referred to as "finding the right individualized healthcare trajectory." The decision-making process occurred in four phases: turmoil, exploration, balance, and control. The turmoil phase included weighing the credibility of information and lowering the anxiety level. The exploration phase included assessing the expertise/promptness of medical treatment and evaluating the effectiveness of follow-up management. The balance phase included performing analyses from multiple angles and rediscovering value as a human being. The control phase included constructing an individualized management system and following prescribed and other management options. It is important to provide patients with accurate information related to the treatment and management of breast cancer so that they can make effective decisions. Healthcare providers should engage with patients on issues related to their disease, understand the burden placed on patients because of issues related to their sex, and ensure that the patient has a sufficient support system. The results of this study can be used to develop phase-specific, patient-centered, and tailored interventions for breast cancer patients. Copyright © 2017 Elsevier Inc. All rights reserved.
A framework to support human factors of automation in railway intelligent infrastructure.
Dadashi, Nastaran; Wilson, John R; Golightly, David; Sharples, Sarah
2014-01-01
Technological and organisational advances have increased the potential for remote access and proactive monitoring of the infrastructure in various domains and sectors - water and sewage, oil and gas and transport. Intelligent Infrastructure (II) is an architecture that potentially enables the generation of timely and relevant information about the state of any type of infrastructure asset, providing a basis for reliable decision-making. This paper reports an exploratory study to understand the concepts and human factors associated with II in the railway, largely drawing from structured interviews with key industry decision-makers and attachment to pilot projects. Outputs from the study include a data-processing framework defining the key human factors at different levels of the data structure within a railway II system and a system-level representation. The framework and other study findings will form a basis for human factors contributions to systems design elements such as information interfaces and role specifications.
Human factors of intelligent computer aided display design
NASA Technical Reports Server (NTRS)
Hunt, R. M.
1985-01-01
Design concepts for a decision support system being studied at NASA Langley as an aid to visual display unit (VDU) designers are described. Ideally, human factors should be taken into account by VDU designers. In reality, although the human factors database on VDUs is small, such systems must be constantly developed. Human factors are therefore a secondary consideration. An expert system will thus serve mainly in an advisory capacity. Functions can include facilitating the design process by shortening the time to generate and alter drawings, enhancing the capability of breaking design requirements down into simpler functions, and providing visual displays equivalent to the final product. The VDU system could also discriminate, and display the difference, between designer decisions and machine inferences. The system could also aid in analyzing the effects of designer choices on future options and in ennunciating when there are data available on a design selections.
DOE Office of Scientific and Technical Information (OSTI.GOV)
NONE
1996-09-01
This Remedial Investigation (RI) Report characterizes the nature and extent of contamination, evaluates the fate and transport of contaminants, and assesses risk to human health and the environment resulting from waste disposal and other US Department of Energy (DOE) operations in Bear Creek Valley (BCV). BCV, which is located within the DOE Oak Ridge Reservation (ORR) encompasses multiple waste units containing hazardous and radioactive wastes arising from operations at the adjacent Oak Ridge Y-12 Plant. The primary waste units discussed in this RI Report are the S-3 Site, Oil Landfarm (OLF), Boneyard/Burnyard (BYBY), Sanitary Landfill 1 (SL 1), and Bearmore » Creek Burial Grounds (BCBG). These waste units, plus the contaminated media resulting from environmental transport of the wastes from these units, are the subject of this RI. This BCV RI Report represents the first major step in the decision-making process for the BCV watershed. The RI results, in concert with the follow-on FS will form the basis for the Proposed Plan and Record of Decision for all BCV sites. This comprehensive decision document process will meet the objectives of the watershed approach for BCV. Appendix F documents potential risks and provides information necessary for making remediation decisions. A quantitative analysis of the inorganic, organic, and radiological site-related contaminants found in various media is used to characterize the potential risks to human health associated with exposure to these contaminants.« less
O'Brien-Pallas, Linda; Hayes, Laureen
2008-12-01
This paper draws upon empirical research and other published sources to discuss nursing workforce issues, the challenges of using health human resource research in policy decisions and the importance of evidence-based policies and practices for nursing care and outcomes. Increasing evidence points to the critical relationship between registered nurse care and improved patient outcomes. The negative impact that insufficient nurse staffing has on patient, nursing and system outcomes has influenced health human resource researchers to further examine nurses' work environments to determine factors that are amenable to policy change. Survey of literature was conducted. Electronic databases were searched using keywords. Sustained health human resource planning efforts by policy makers are difficult given changing governments and political agendas. The health human resource conceptual framework provides researchers and planners with a guide to decision-making that considers current circumstances as well as those factors that need to be accounted for in predicting future requirements. However, effective use of research depends on communication of findings between researchers and policymakers. Health care managers and other decision-makers in health care organisations often lack an understanding of the research process and do not always have easy access to current evidence. Also, managerial decisions are often constrained by organisational requirements such as resource availability and policies and procedures. Unless nursing workplace issues are addressed, the physiological and psychological stress in the work environments of nurses will continue. Effective health human resource policy and planning (at the macro level) and management strategies (at the micro level) would stabilise the nursing workforce and reduce job stress. Furthermore, the efficiency and cost-effectiveness of the health system could be enhanced through improved health outcomes of care providers and health care clients.
Yohn, Samantha E.; López-Cruz, Laura; San Miguel, Noemí; Correa, Mercè
2016-01-01
Abstract Motivation has been defined as the process that allows organisms to regulate their internal and external environment, and control the probability, proximity and availability of stimuli. As such, motivation is a complex process that is critical for survival, which involves multiple behavioural functions mediated by a number of interacting neural circuits. Classical theories of motivation suggest that there are both directional and activational aspects of motivation, and activational aspects (i.e. speed and vigour of both the instigation and persistence of behaviour) are critical for enabling organisms to overcome work-related obstacles or constraints that separate them from significant stimuli. The present review discusses the role of brain dopamine and related circuits in behavioural activation, exertion of effort in instrumental behaviour, and effort-related decision-making, based upon both animal and human studies. Impairments in behavioural activation and effort-related aspects of motivation are associated with psychiatric symptoms such as anergia, fatigue, lassitude and psychomotor retardation, which cross multiple pathologies, including depression, schizophrenia, and Parkinson’s disease. Therefore, this review also attempts to provide an interdisciplinary approach that integrates findings from basic behavioural neuroscience, behavioural economics, clinical neuropsychology, psychiatry, and neurology, to provide a coherent framework for future research and theory in this critical field. Although dopamine systems are a critical part of the brain circuitry regulating behavioural activation, exertion of effort, and effort-related decision-making, mesolimbic dopamine is only one part of a distributed circuitry that includes multiple neurotransmitters and brain areas. Overall, there is a striking similarity between the brain areas involved in behavioural activation and effort-related processes in rodents and in humans. Animal models of effort-related decision-making are highly translatable to humans, and an emerging body of evidence indicates that alterations in effort-based decision-making are evident in several psychiatric and neurological disorders. People with major depression, schizophrenia, and Parkinson’s disease show evidence of decision-making biases towards a lower exertion of effort. Translational studies linking research with animal models, human volunteers, and clinical populations are greatly expanding our knowledge about the neural basis of effort-related motivational dysfunction, and it is hoped that this research will ultimately lead to improved treatment for motivational and psychomotor symptoms in psychiatry and neurology. PMID:27189581
Beyond Bioethics: A Child Rights-Based Approach to Complex Medical Decision-Making.
Wade, Katherine; Melamed, Irene; Goldhagen, Jeffrey
2016-01-01
This analysis adopts a child rights approach-based on the principles, standards, and norms of child rights and the U.N. Convention on the Rights of the Child (CRC)-to explore how decisions could be made with regard to treatment of a severely impaired infant (Baby G). While a child rights approach does not provide neat answers to ethically complex issues, it does provide a framework for decision-making in which the infant is viewed as an independent rights-holder. The state has obligations to develop the capacity of those who make decisions for infants in such situations to meet their obligations to respect, protect, and fulfill their rights as delineated in the CRC. Furthermore, a child rights approach requires procedural clarity and transparency in decision-making processes. As all rights in the CRC are interdependent and indivisible, all must be considered in the process of ethical decision-making, and the reasons for decisions must be delineated by reference to how these rights were considered. It is also important that decisions that are made in this context be monitored and reviewed to ensure consistency. A rights-based framework ensures decision-making is child-centered and that there are transparent criteria and legitimate procedures for making decisions regarding the child's most basic human right: the right to life, survival, and development.
Complacency and bias in human use of automation: an attentional integration.
Parasuraman, Raja; Manzey, Dietrich H
2010-06-01
Our aim was to review empirical studies of complacency and bias in human interaction with automated and decision support systems and provide an integrated theoretical model for their explanation. Automation-related complacency and automation bias have typically been considered separately and independently. Studies on complacency and automation bias were analyzed with respect to the cognitive processes involved. Automation complacency occurs under conditions of multiple-task load, when manual tasks compete with the automated task for the operator's attention. Automation complacency is found in both naive and expert participants and cannot be overcome with simple practice. Automation bias results in making both omission and commission errors when decision aids are imperfect. Automation bias occurs in both naive and expert participants, cannot be prevented by training or instructions, and can affect decision making in individuals as well as in teams. While automation bias has been conceived of as a special case of decision bias, our analysis suggests that it also depends on attentional processes similar to those involved in automation-related complacency. Complacency and automation bias represent different manifestations of overlapping automation-induced phenomena, with attention playing a central role. An integrated model of complacency and automation bias shows that they result from the dynamic interaction of personal, situational, and automation-related characteristics. The integrated model and attentional synthesis provides a heuristic framework for further research on complacency and automation bias and design options for mitigating such effects in automated and decision support systems.
The Neural Basis of Social Influence in a Dictator Decision
Wei, Zhenyu; Zhao, Zhiying; Zheng, Yong
2017-01-01
Humans tend to reduce inequitable distributions. Previous neuroimaging studies have shown that inequitable decisions are related to brain regions that associated with negative emotion and signaling conflict. In the highly complex human social environment, our opinions and behaviors can be affected by social information. In current study, we used a modified dictator game to investigate the effect of social influence on making an equitable decision. We found that the choices of participants in present task was influenced by the choices of peers. However, participants’ decisions were influenced by equitable rather than inequitable group choices. fMRI results showed that brain regions that related to norm violation and social conflict were related to the inequitable social influence. The neural responses in the dorsomedial prefrontal cortex, rostral cingulate zone, and insula predicted subsequent conforming behavior in individuals. Additionally, psychophysiological interaction analysis revealed that the interconnectivity between the dorsal striatum and insula was elevated in advantageous inequity influence versus no-social influence conditions. We found decreased functional connectivity between the medial prefrontal cortex and insula, supplementary motor area, posterior cingulate gyrus and dorsal anterior cingulate cortex in the disadvantageous inequity influence versus no-social influence conditions. This suggests that a disadvantageous inequity influence may decrease the functional connectivity among brain regions that are related to reward processes. Thus, the neural mechanisms underlying social influence in an equitable decision may be similar to those implicated in social norms and reward processing. PMID:29375412
Harm to others outweighs harm to self in moral decision making
Crockett, Molly J.; Kurth-Nelson, Zeb; Siegel, Jenifer Z.; Dayan, Peter; Dolan, Raymond J.
2014-01-01
Concern for the suffering of others is central to moral decision making. How humans evaluate others’ suffering, relative to their own suffering, is unknown. We investigated this question by inviting subjects to trade off profits for themselves against pain experienced either by themselves or an anonymous other person. Subjects made choices between different amounts of money and different numbers of painful electric shocks. We independently varied the recipient of the shocks (self vs. other) and whether the choice involved paying to decrease pain or profiting by increasing pain. We built computational models to quantify the relative values subjects ascribed to pain for themselves and others in this setting. In two studies we show that most people valued others’ pain more than their own pain. This was evident in a willingness to pay more to reduce others’ pain than their own and a requirement for more compensation to increase others’ pain relative to their own. This ‟hyperaltruistic” valuation of others’ pain was linked to slower responding when making decisions that affected others, consistent with an engagement of deliberative processes in moral decision making. Subclinical psychopathic traits correlated negatively with aversion to pain for both self and others, in line with reports of aversive processing deficits in psychopathy. Our results provide evidence for a circumstance in which people care more for others than themselves. Determining the precise boundaries of this surprisingly prosocial disposition has implications for understanding human moral decision making and its disturbance in antisocial behavior. PMID:25404350
Decision making: the neuroethological turn
Pearson, John M.; Watson, Karli K.; Platt, Michael L.
2014-01-01
Neuroeconomics applies models from economics and psychology to inform neurobiological studies of choice. This approach has revealed neural signatures of concepts like value, risk, and ambiguity, which are known to influence decision-making. Such observations have led theorists to hypothesize a single, unified decision process that mediates choice behavior via a common neural currency for outcomes like food, money, or social praise. In parallel, recent neuroethological studies of decision-making have focused on natural behaviors like foraging, mate choice, and social interactions. These decisions strongly impact evolutionary fitness and thus are likely to have played a key role in shaping the neural circuits that mediate decision-making. This approach has revealed a suite of computational motifs that appear to be shared across a wide variety of organisms. We argue that the existence of deep homologies in the neural circuits mediating choice may have profound implications for understanding human decision-making in health and disease. PMID:24908481
Blyer, Kristina; Hulton, Linda
2016-01-01
This systematic review examines shared decision making to promote the appropriate use of antibiotics for college students with respiratory tract infections. CINAL, Cochrane, PubMed, EBSCO, and PsycNET were searched in October 2014 using the following criteria: English language, human subjects, peer-reviewed, shared decision making for respiratory tract infections, adult patients or college students, and antibiotic use for respiratory tract infections. Twelve articles were selected for final review. College students and younger, more educated, adults prefer shared decision making. Shared decision making shows promise for decreasing antibiotic use for respiratory tract infections. Education, understanding, and provider-patient communication are important to the shared decision-making process. Shared decision making shows promise to promote the appropriate use of antibiotics for respiratory tract infections in college students and could be considered for future studies.
Neural Basis of Strategic Decision Making.
Lee, Daeyeol; Seo, Hyojung
2016-01-01
Human choice behaviors during social interactions often deviate from the predictions of game theory. This might arise partly from the limitations in the cognitive abilities necessary for recursive reasoning about the behaviors of others. In addition, during iterative social interactions, choices might change dynamically as knowledge about the intentions of others and estimates for choice outcomes are incrementally updated via reinforcement learning. Some of the brain circuits utilized during social decision making might be general-purpose and contribute to isomorphic individual and social decision making. By contrast, regions in the medial prefrontal cortex (mPFC) and temporal parietal junction (TPJ) might be recruited for cognitive processes unique to social decision making. Copyright © 2015 Elsevier Ltd. All rights reserved.
Errors in Aviation Decision Making: Bad Decisions or Bad Luck?
NASA Technical Reports Server (NTRS)
Orasanu, Judith; Martin, Lynne; Davison, Jeannie; Null, Cynthia H. (Technical Monitor)
1998-01-01
Despite efforts to design systems and procedures to support 'correct' and safe operations in aviation, errors in human judgment still occur and contribute to accidents. In this paper we examine how an NDM (naturalistic decision making) approach might help us to understand the role of decision processes in negative outcomes. Our strategy was to examine a collection of identified decision errors through the lens of an aviation decision process model and to search for common patterns. The second, and more difficult, task was to determine what might account for those patterns. The corpus we analyzed consisted of tactical decision errors identified by the NTSB (National Transportation Safety Board) from a set of accidents in which crew behavior contributed to the accident. A common pattern emerged: about three quarters of the errors represented plan-continuation errors, that is, a decision to continue with the original plan despite cues that suggested changing the course of action. Features in the context that might contribute to these errors were identified: (a) ambiguous dynamic conditions and (b) organizational and socially-induced goal conflicts. We hypothesize that 'errors' are mediated by underestimation of risk and failure to analyze the potential consequences of continuing with the initial plan. Stressors may further contribute to these effects. Suggestions for improving performance in these error-inducing contexts are discussed.
Examining the Impact of Culture and Human Elements on OLAP Tools Usefulness
ERIC Educational Resources Information Center
Sharoupim, Magdy S.
2010-01-01
The purpose of the present study was to examine the impact of culture and human-related elements on the On-line Analytical Processing (OLAP) usability in generating decision-making information. The use of OLAP technology has evolved rapidly and gained momentum, mainly due to the ability of OLAP tools to examine and query large amounts of data sets…
Human Dimensions in Future Battle Command Systems: A Workshop Report
2008-04-01
information processing). These dimensions can best be described anecdotally and metaphorically as: • Battle command is a human-centric...enhance information visualization techniques in the decision tools, including multimodal platforms: video, graphics, symbols, etc. This should be...organization members. Each dimension can metaphorically represent the spatial location of individuals and group thinking in a trajectory of social norms
ERIC Educational Resources Information Center
Ryburn, Murray; Fleming, Annette
1993-01-01
Britain's Human Fertilisation and Embryology Act provides for the assessment of adults for parenthood on both medical and social grounds, justified by concern for the welfare of the child. Compares these assessments with those undertaken in the adoption process and questions the utility of such decisions for the welfare of the children involved.…
NASA Technical Reports Server (NTRS)
Tavana, Madjid
2003-01-01
The primary driver for developing missions to send humans to other planets is to generate significant scientific return. NASA plans human planetary explorations with an acceptable level of risk consistent with other manned operations. Space exploration risks can not be completely eliminated. Therefore, an acceptable level of cost, technical, safety, schedule, and political risks and benefits must be established for exploratory missions. This study uses a three-dimensional multi-criteria decision making model to identify the risks and benefits associated with three alternative mission architecture operations concepts for the human exploration of Mars identified by the Mission Operations Directorate at Johnson Space Center. The three alternatives considered in this study include split, combo lander, and dual scenarios. The model considers the seven phases of the mission including: 1) Earth Vicinity/Departure; 2) Mars Transfer; 3) Mars Arrival; 4) Planetary Surface; 5) Mars Vicinity/Departure; 6) Earth Transfer; and 7) Earth Arrival. Analytic Hierarchy Process (AHP) and subjective probability estimation are used to captures the experts belief concerning the risks and benefits of the three alternative scenarios through a series of sequential, rational, and analytical processes.
Stochastic characterization of small-scale algorithms for human sensory processing
NASA Astrophysics Data System (ADS)
Neri, Peter
2010-12-01
Human sensory processing can be viewed as a functional H mapping a stimulus vector s into a decisional variable r. We currently have no direct access to r; rather, the human makes a decision based on r in order to drive subsequent behavior. It is this (typically binary) decision that we can measure. For example, there may be two external stimuli s[0] and s[1], mapped onto r[0] and r[1] by the sensory apparatus H; the human chooses the stimulus associated with largest r. This kind of decisional transduction poses a major challenge for an accurate characterization of H. In this article, we explore a specific approach based on a behavioral variant of reverse correlation techniques, where the input s contains a target signal corrupted by a controlled noisy perturbation. The presence of the target signal poses an additional challenge because it distorts the otherwise unbiased nature of the noise source. We consider issues arising from both the decisional transducer and the target signal, their impact on system identification, and ways to handle them effectively for system characterizations that extend to second-order functional approximations with associated small-scale cascade models.
Lee as Critical Thinker: The Example of the Gettysburg Campaign
2012-05-04
well as what should have been done if the critical thinking process had been conducted appropriately. Conclusion: Several human and military...of reasoning that make up the cognitive decision making process .6 The critical thinking elements of the model (Clarify Concern, Point of View...Finally, there are three remaining biases, traps, and errors that can negatively affect the critical thinking process . A confirmation trap describes
Predicting decisions in human social interactions using real-time fMRI and pattern classification.
Hollmann, Maurice; Rieger, Jochem W; Baecke, Sebastian; Lützkendorf, Ralf; Müller, Charles; Adolf, Daniela; Bernarding, Johannes
2011-01-01
Negotiation and trade typically require a mutual interaction while simultaneously resting in uncertainty which decision the partner ultimately will make at the end of the process. Assessing already during the negotiation in which direction one's counterpart tends would provide a tremendous advantage. Recently, neuroimaging techniques combined with multivariate pattern classification of the acquired data have made it possible to discriminate subjective states of mind on the basis of their neuronal activation signature. However, to enable an online-assessment of the participant's mind state both approaches need to be extended to a real-time technique. By combining real-time functional magnetic resonance imaging (fMRI) and online pattern classification techniques, we show that it is possible to predict human behavior during social interaction before the interacting partner communicates a specific decision. Average accuracy reached approximately 70% when we predicted online the decisions of volunteers playing the ultimatum game, a well-known paradigm in economic game theory. Our results demonstrate the successful online analysis of complex emotional and cognitive states using real-time fMRI, which will enable a major breakthrough for social fMRI by providing information about mental states of partners already during the mutual interaction. Interestingly, an additional whole brain classification across subjects confirmed the online results: anterior insula, ventral striatum, and lateral orbitofrontal cortex, known to act in emotional self-regulation and reward processing for adjustment of behavior, appeared to be strong determinants of later overt behavior in the ultimatum game. Using whole brain classification we were also able to discriminate between brain processes related to subjective emotional and motivational states and brain processes related to the evaluation of objective financial incentives.
How system designers think: a study of design thinking in human factors engineering.
Papantonopoulos, Sotiris
2004-11-01
The paper presents a descriptive study of design thinking in human factors engineering. The objective of the study is to analyse the role of interpretation in design thinking and the role of design practice in guiding interpretation. The study involved 10 system designers undertaking the allocation of cognitive functions in three production planning and control task scenarios. Allocation decisions were recorded and verbal protocols of the design process were collected to elicit the subjects' thought processes. Verbal protocol analysis showed that subjects carried out the design of cognitive task allocation as a problem of applying a selected automation technology from their initial design deliberations. This design strategy stands in contrast to the predominant view of system design that stipulates that user requirements should be thoroughly analysed prior to making any decisions about technology. Theoretical frameworks from design research and ontological design showed that the system design process may be better understood by recognizing the role of design hypotheses in system design, as well as the diverse interactions between interpretation and practice, means and ends, and design practice and the designer's pre-understanding which shape the design process. Ways to balance the bias exerted on the design process were discussed.
Risk management frameworks for human health and environmental risks.
Jardine, Cindy; Hrudey, Steve; Shortreed, John; Craig, Lorraine; Krewski, Daniel; Furgal, Chris; McColl, Stephen
2003-01-01
A comprehensive analytical review of the risk assessment, risk management, and risk communication approaches currently being undertaken by key national, provincial/state, territorial, and international agencies was conducted. The information acquired for review was used to identify the differences, commonalities, strengths, and weaknesses among the various approaches, and to identify elements that should be included in an effective, current, and comprehensive approach applicable to environmental, human health and occupational health risks. More than 80 agencies, organizations, and advisory councils, encompassing more than 100 risk documents, were examined during the period from February 2000 until November 2002. An overview was made of the most important general frameworks for risk assessment, risk management, and risk communication for human health and ecological risk, and for occupational health risk. In addition, frameworks for specific applications were reviewed and summarized, including those for (1)contaminated sites; (2) northern contaminants; (3) priority substances; (4) standards development; (5) food safety; (6) medical devices; (7) prescription drug use; (8) emergency response; (9) transportation; (10) risk communication. Twelve frameworks were selected for more extensive review on the basis of representation of the areas of human health, ecological, and occupational health risk; relevance to Canadian risk management needs; representation of comprehensive and well-defined approaches; generalizability with their risk areas; representation of "state of the art" in Canada, the United States, and/or internationally; and extent of usage of potential usage within Canada. These 12 frameworks were: 1. Framework for Environmental Health Risk Management (US Presidential/Congressional Commission on Risk Assessment and Risk Management, 1997). 2. Health Risk Determination: The Challenge of Health Protection (Health and Welfare Canada, 1990). 3. Health Canada Decision-Making Framework for Identifying, Assessing and Managing Health Risks (Health Canada, 2000). 4. Canadian Environmental Protection Act: Human Health Risk Assessment of Priority Substances(Health Canada, 1994). 5. CSA-Q8550 Risk Management: Guidelines for Decision-Makers (Canada Standards Association, 1997). 6. Risk Assessment in the Federal Government: Managing the Process (US National Research Council, 1983). 7. Understanding Risk: Informing Decisions in a Democratic Society (US National Research Council, 1996). 8. Environmental Health Risk Assessment (enHealth Council of Australia, 2002). 9. A Framework for Ecological Risk Assessment (CCME, 1996). 10. Ecological Risk Assessments of Priority Substances Under the Canadian Environmental Protection Act (Environment Canada, 1996).11. Guidelines for Ecological Risk Assessment (US EPA, 1998b). 12. Proposed Model for Occupational Health Risk Assessment and Management (Rampal & Sadhra, 1999). Based on the extensive review of these frameworks, seven key elements that should be included in a comprehensive framework for human health, ecological, and occupational risk assessment and management were identified: 1. Problem formulation stage. 2. Stakeholder involvement. 3. Communication. 4. Quantitative risk assessment components. 5. Iteration and evaluation. 6. Informed decision making. 7. Flexibility. On the basis of this overarching approach to risk management, the following "checklist" to ensure a good risk management decision is proposed: - Make sure you're solving the right problem. - Consider the problem and the risk within the full context of the situation, using a broad perspective. - Acknowledge, incorporate, and balance the multiple dimensions of risk. - Ensure the highest degree of reliability for all components of the risk management process. - Involve interested and effected parties from the outset of the process. - Commit to honest and open communication between all parties. - Employ continuous evaluation throughout the process (formative, process, and outcome evaluation), and be prepared to change the decision if new information becomes available. Comprehensive and sound principles are critical to providing structure and integrity to risk management frameworks. Guiding principles are intended to provide an ethical grounding for considering the many factors involved in risk management decision making. Ten principles are proposed to guide risk management decision making. The first four principles were adapted and modified from Hattis (1996) along with the addition of two more principles by Hrudey (2000). These have been supplemented by another four principles to make the 10 presented. The principles are based in fundamental ethical principles and values. These principles are intended to be aspirational rather than prescriptive--their application requires flexibility and practical judgement. Risk management is inherently a process in search of balance among competing interests and concerns. Each risk management decision will be "balancing act" of competing priorities, and trade-offs may sometimes have to be made between seemingly conflicting principles. The 10 decision-making principles, with the corresponding ethical principle in italics are: 1. Do more good than harm (beneficence, nonmalificence).- The ultimate goal of good risk management is to prevent or minimize risk, or to "do good" as much as possible. 2. Fair process of decision making (fairness, natural justice). - Risk management must be just, equitable, impartial, unbiased, dispassionate, and objective as far as possible given the circumstances of each situation. 3. Ensure an equitable distribution of risk (equity). - An equitable process of risk management would ensure fair outcomes and equal treatment of all concerned through an equal distribution of benefits and burdens (includes the concept of distributive justice, i.e., equal opportunities for all individuals). 4. Seek optimal use of limited risk management resources (utility). - Optimal risk management demands using limited resources where they will achieve the most risk reduction of overall benefit. 5. Promise no more risk management that can be delivered (honesty).- Unrealistic expectations of risk management can be avoided with honest and candid public accounting of what we know and don't know, and what we can and can't do using risk assessment and risk management. 6. Impose no more risk that you would tolerate yourself (the Golden Rule). - The Golden Rule is important in risk management because it forces decision makers to abandon complete detachment from their decisions so they may understand the perspectives of those affected. 7. Be cautious in the face of uncertainty ("better safe than sorry"). - Risk management must adopt a cautious approach when faced with a potentially serous risk, even if the evidence is uncertain. 8. Foster informed risk decision making for all stakeholders (autonomy). - Fostering autonomous decision making involves both providing people with the opportunity to participate, and full and honest disclosure of all the information required for informed decisions. 9. Risk management processes must be flexible and evolutionary to be open to new knowledge and understanding (evolution, evaluation, iterative process). - The incorporation of new evidence requires that risk management be a flexible, evolutionary, and iterative process, and that evaluation is employed at the beginning and througthout the process. 10. the complete elimination fo risk is not possible (life is not risk free).- Risk is pervasive in our society, and cannot be totally eliminated despite an oft-expressed public desire for "zero risk". However, the level of risk that may ve tolerable by any individual is dependent on values of beliefs, as well as scientific information. Each agency must continue to employ a process that meets the needs of their specific application of risk management. A single approach cannot satisfy the diverse areas to which risk decisions are being applied. However, with increasing experience in the application of the approaches, we are evolving to a common understanding of the essential elements and principles required for successful risk assessment, risk management, and risk communication. Risk management will continue to be a balancing act of competing priorities and needs. Flexibility and good judgement are ultimately the key to successfully making appropriate risk decisions.
Multi-tasking arbitration and behaviour design for human-interactive robots
NASA Astrophysics Data System (ADS)
Kobayashi, Yuichi; Onishi, Masaki; Hosoe, Shigeyuki; Luo, Zhiwei
2013-05-01
Robots that interact with humans in household environments are required to handle multiple real-time tasks simultaneously, such as carrying objects, collision avoidance and conversation with human. This article presents a design framework for the control and recognition processes to meet these requirements taking into account stochastic human behaviour. The proposed design method first introduces a Petri net for synchronisation of multiple tasks. The Petri net formulation is converted to Markov decision processes and processed in an optimal control framework. Three tasks (safety confirmation, object conveyance and conversation) interact and are expressed by the Petri net. Using the proposed framework, tasks that normally tend to be designed by integrating many if-then rules can be designed in a systematic manner in a state estimation and optimisation framework from the viewpoint of the shortest time optimal control. The proposed arbitration method was verified by simulations and experiments using RI-MAN, which was developed for interactive tasks with humans.
An Exploration of Dual Systems via Time Pressure Manipulation in Decision-making Problems
NASA Astrophysics Data System (ADS)
Guo, Lisa
Every day, decisions need to be made where time is a limiting factor. Regardless of situation, time constraints often place a premium on rapid decision-making. Researchers have been interested in studying this human behavior and understanding its underlying cognitive processes. In previous studies, scientists have believed that the cognitive processes underlying decision-making behavior were consistent with dual-process modes of thinking. Critics of dual-process theory question the vagueness of its definition, and claim that single-process accounts can explain the data just as well. My aim is to elucidate the cognitive processes that underlie decisions which involve some level of risk through the experimental manipulation of time pressure. Using this method, I hope to distinguish between competing hypotheses related to the origin of the effect. I will explore three types of decisions that illustrate these concepts: risky decision-making involving gambles, intertemporal choice, and one-shot public goods games involving social cooperation. In our experiments, participants made decisions about gambles framed as either gains or losses; decided upon intertemporal choices for smaller but sooner rewards or larger but later rewards; and played a one-shot public goods game involving social cooperation and contributing an amount of money to a group. In each case, we experimentally manipulated time pressure, either within subjects or among individuals. Results showed under time pressure, increased framing effects under in both hypothetical and incentivized choices; and greater contributions and cooperation among individuals, lending support to the dual process hypothesis that these effects arise from a fast, intuitive system. However, our intertemporal choice experiment showed that time constraints led to increased selection of the larger but later options, which suggests that the magnitude of the reward may play larger role in choice selection under cognitive load than previously studied. This diverges from the current dual-process interpretation that myopic choices under time pressure favor smaller but sooner rewards, and suggests that more studies are needed in this realm to disentangle the intuitive from the deliberative system through the manipulation of cognitive load.
Introduction to cognitive processes of expert pilots.
Adams, R J; Ericsson, A E
2000-10-01
This report addresses the historical problem that a very high percentage of accidents have been classified as involving "pilot error." Through extensive research since 1977, the Federal Aviation Administration determined that the predominant underlying cause of these types of accidents involved decisional problems or cognitive information processing. To attack these problems, Aeronautical Decision Making (ADM) training materials were developed and tested for ten years. Since the publication of the ADM training manuals in 1987, significant reductions in human performance error (HPE) accidents have been documented both in the U.S. and world wide. However, shortcomings have been observed in the use of these materials for recurrency training and in their relevance to more experienced pilots. The following discussion defines the differences between expert and novice decision makers from a cognitive information processing perspective, correlates the development of expert pilot cognitive processes with training and experience, and reviews accident scenarios which exemplify those processes. This introductory material is a necessary prerequisite to an understanding of how to formulate expert pilot decision making training innovations; and, to continue the record of improved safety through ADM training.
Deciding to Decide: How Decisions Are Made and How Some Forces Affect the Process.
McConnell, Charles R
There is a decision-making pattern that applies in all situations, large or small, although in small decisions, the steps are not especially evident. The steps are gathering information, analyzing information and creating alternatives, selecting and implementing an alternative, and following up on implementation. The amount of effort applied in any decision situation should be consistent with the potential consequences of the decision. Essentially, all decisions are subject to certain limitations or constraints, forces, or circumstances that limit one's range of choices. Follow-up on implementation is the phase of decision making most often neglected, yet it is frequently the phase that determines success or failure. Risk and uncertainty are always present in a decision situation, and the application of human judgment is always necessary. In addition, there are often emotional forces at work that can at times unwittingly steer one away from that which is best or most workable under the circumstances and toward a suboptimal result based largely on the desires of the decision maker.
Music and Video Gaming during Breaks: Influence on Habitual versus Goal-Directed Decision Making.
Liu, Shuyan; Schad, Daniel J; Kuschpel, Maxim S; Rapp, Michael A; Heinz, Andreas
2016-01-01
Different systems for habitual versus goal-directed control are thought to underlie human decision-making. Working memory is known to shape these decision-making systems and their interplay, and is known to support goal-directed decision making even under stress. Here, we investigated if and how decision systems are differentially influenced by breaks filled with diverse everyday life activities known to modulate working memory performance. We used a within-subject design where young adults listened to music and played a video game during breaks interleaved with trials of a sequential two-step Markov decision task, designed to assess habitual as well as goal-directed decision making. Based on a neurocomputational model of task performance, we observed that for individuals with a rather limited working memory capacity video gaming as compared to music reduced reliance on the goal-directed decision-making system, while a rather large working memory capacity prevented such a decline. Our findings suggest differential effects of everyday activities on key decision-making processes.
Music and Video Gaming during Breaks: Influence on Habitual versus Goal-Directed Decision Making
Kuschpel, Maxim S.; Rapp, Michael A.; Heinz, Andreas
2016-01-01
Different systems for habitual versus goal-directed control are thought to underlie human decision-making. Working memory is known to shape these decision-making systems and their interplay, and is known to support goal-directed decision making even under stress. Here, we investigated if and how decision systems are differentially influenced by breaks filled with diverse everyday life activities known to modulate working memory performance. We used a within-subject design where young adults listened to music and played a video game during breaks interleaved with trials of a sequential two-step Markov decision task, designed to assess habitual as well as goal-directed decision making. Based on a neurocomputational model of task performance, we observed that for individuals with a rather limited working memory capacity video gaming as compared to music reduced reliance on the goal-directed decision-making system, while a rather large working memory capacity prevented such a decline. Our findings suggest differential effects of everyday activities on key decision-making processes. PMID:26982326
Communicating Numerical Risk: Human Factors That Aid Understanding in Health Care
Brust-Renck, Priscila G.; Royer, Caisa E.; Reyna, Valerie F.
2014-01-01
In this chapter, we review evidence from the human factors literature that verbal and visual formats can help increase the understanding of numerical risk information in health care. These visual representations of risk are grounded in empirically supported theory. As background, we first review research showing that people often have difficulty understanding numerical risks and benefits in health information. In particular, we discuss how understanding the meanings of numbers results in healthier decisions. Then, we discuss the processes that determine how communication of numerical risks can enhance (or degrade) health judgments and decisions. Specifically, we examine two different approaches to risk communication: a traditional approach and fuzzy-trace theory. Applying research on the complications of understanding and communicating risks, we then highlight how different visual representations are best suited to communicating different risk messages (i.e., their gist). In particular, we review verbal and visual messages that highlight gist representations that can better communicate health information and improve informed decision making. This discussion is informed by human factors theories and methods, which involve the study of how to maximize the interaction between humans and the tools they use. Finally, we present implications and recommendations for future research on human factors in health care. PMID:24999307
Veksler, Vladislav D.; Buchler, Norbou; Hoffman, Blaine E.; Cassenti, Daniel N.; Sample, Char; Sugrim, Shridat
2018-01-01
Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision likelihood distributions, (b) human factors of cyber tools to address human system integration challenges, estimation of defender cognitive states, and opportunities for automation, (c) dynamic simulations involving attacker, defender, and user models to enhance studies of cyber epidemiology and cyber hygiene, and (d) training effectiveness research and training scenarios to address human cyber-security performance, maturation of cyber-security skill sets, and effective decision-making. Models may be initially constructed at the group-level based on mean tendencies of each subject's subgroup, based on known statistics such as specific skill proficiencies, demographic characteristics, and cultural factors. For more precise and accurate predictions, cognitive models may be fine-tuned to each individual attacker, defender, or user profile, and updated over time (based on recorded behavior) via techniques such as model tracing and dynamic parameter fitting. PMID:29867661
Shizgal, Peter
2012-01-01
Almost 80 years ago, Lionel Robbins proposed a highly influential definition of the subject matter of economics: the allocation of scarce means that have alternative ends. Robbins confined his definition to human behavior, and he strove to separate economics from the natural sciences in general and from psychology in particular. Nonetheless, I extend his definition to the behavior of non-human animals, rooting my account in psychological processes and their neural underpinnings. Some historical developments are reviewed that render such a view more plausible today than would have been the case in Robbins' time. To illustrate a neuroeconomic perspective on decision making in non-human animals, I discuss research on the rewarding effect of electrical brain stimulation. Central to this discussion is an empirically based, functional/computational model of how the subjective intensity of the electrical reward is computed and combined with subjective costs so as to determine the allocation of time to the pursuit of reward. Some successes achieved by applying the model are discussed, along with limitations, and evidence is presented regarding the roles played by several different neural populations in processes posited by the model. I present a rationale for marshaling convergent experimental methods to ground psychological and computational processes in the activity of identified neural populations, and I discuss the strengths, weaknesses, and complementarity of the individual approaches. I then sketch some recent developments that hold great promise for advancing our understanding of structure-function relationships in neuroscience in general and in the neuroeconomic study of decision making in particular.
Shizgal, Peter
2011-01-01
Almost 80 years ago, Lionel Robbins proposed a highly influential definition of the subject matter of economics: the allocation of scarce means that have alternative ends. Robbins confined his definition to human behavior, and he strove to separate economics from the natural sciences in general and from psychology in particular. Nonetheless, I extend his definition to the behavior of non-human animals, rooting my account in psychological processes and their neural underpinnings. Some historical developments are reviewed that render such a view more plausible today than would have been the case in Robbins’ time. To illustrate a neuroeconomic perspective on decision making in non-human animals, I discuss research on the rewarding effect of electrical brain stimulation. Central to this discussion is an empirically based, functional/computational model of how the subjective intensity of the electrical reward is computed and combined with subjective costs so as to determine the allocation of time to the pursuit of reward. Some successes achieved by applying the model are discussed, along with limitations, and evidence is presented regarding the roles played by several different neural populations in processes posited by the model. I present a rationale for marshaling convergent experimental methods to ground psychological and computational processes in the activity of identified neural populations, and I discuss the strengths, weaknesses, and complementarity of the individual approaches. I then sketch some recent developments that hold great promise for advancing our understanding of structure–function relationships in neuroscience in general and in the neuroeconomic study of decision making in particular. PMID:22363253
Decision-Making in Agent-Based Models of Migration: State of the Art and Challenges.
Klabunde, Anna; Willekens, Frans
We review agent-based models (ABM) of human migration with respect to their decision-making rules. The most prominent behavioural theories used as decision rules are the random utility theory, as implemented in the discrete choice model, and the theory of planned behaviour. We identify the critical choices that must be made in developing an ABM, namely the modelling of decision processes and social networks. We also discuss two challenges that hamper the widespread use of ABM in the study of migration and, more broadly, demography and the social sciences: (a) the choice and the operationalisation of a behavioural theory (decision-making and social interaction) and (b) the selection of empirical evidence to validate the model. We offer advice on how these challenges might be overcome.
Hierarchical analytical and simulation modelling of human-machine systems with interference
NASA Astrophysics Data System (ADS)
Braginsky, M. Ya; Tarakanov, D. V.; Tsapko, S. G.; Tsapko, I. V.; Baglaeva, E. A.
2017-01-01
The article considers the principles of building the analytical and simulation model of the human operator and the industrial control system hardware and software. E-networks as the extension of Petri nets are used as the mathematical apparatus. This approach allows simulating complex parallel distributed processes in human-machine systems. The structural and hierarchical approach is used as the building method for the mathematical model of the human operator. The upper level of the human operator is represented by the logical dynamic model of decision making based on E-networks. The lower level reflects psychophysiological characteristics of the human-operator.
ERIC Educational Resources Information Center
Hackman, Judith Dozier
Seven potentially useful maxims from the field of human information processing are proposed that may help institutional researchers prepare and present information for higher education decision-makers. The maxims, which are based on research and theory about how people cognitively process information, are as follows: (1) more may not be better;…
Attention - Control in the Frequentistic Processing of Multidimensional Event Streams.
1980-07-01
Human memory. Annual Review of Psychology, 1979, 30, 63-702. Craik , F. I. M., & Lockhart , R. S. Levels of processing : A framework for memory research...1979; Jacoby & Craik , 1979). Thus, the notions of memora- bility (or retrievability) and levels of processing are tied closely in the sense that the...differing levels and degrees of elaborateness (Jacoby & Craik , 1979). Decisions as to which attributes receive elaborated processing and how they are
Dual Rationality and Deliberative Agents
NASA Astrophysics Data System (ADS)
Debenham, John; Sierra, Carles
Human agents deliberate using models based on reason for only a minute proportion of the decisions that they make. In stark contrast, the deliberation of artificial agents is heavily dominated by formal models based on reason such as game theory, decision theory and logic—despite that fact that formal reasoning will not necessarily lead to superior real-world decisions. Further the Nobel Laureate Friedrich Hayek warns us of the ‘fatal conceit’ in controlling deliberative systems using models based on reason as the particular model chosen will then shape the system’s future and either impede, or eventually destroy, the subtle evolutionary processes that are an integral part of human systems and institutions, and are crucial to their evolution and long-term survival. We describe an architecture for artificial agents that is founded on Hayek’s two rationalities and supports the two forms of deliberation used by mankind.
Heuristic thinking makes a chemist smart.
Graulich, Nicole; Hopf, Henning; Schreiner, Peter R
2010-05-01
We focus on the virtually neglected use of heuristic principles in understanding and teaching of organic chemistry. As human thinking is not comparable to computer systems employing factual knowledge and algorithms--people rarely make decisions through careful considerations of every possible event and its probability, risks or usefulness--research in science and teaching must include psychological aspects of the human decision making processes. Intuitive analogical and associative reasoning and the ability to categorize unexpected findings typically demonstrated by experienced chemists should be made accessible to young learners through heuristic concepts. The psychology of cognition defines heuristics as strategies that guide human problem-solving and deciding procedures, for example with patterns, analogies, or prototypes. Since research in the field of artificial intelligence and current studies in the psychology of cognition have provided evidence for the usefulness of heuristics in discovery, the status of heuristics has grown into something useful and teachable. In this tutorial review, we present a heuristic analysis of a familiar fundamental process in organic chemistry--the cyclic six-electron case, and we show that this approach leads to a more conceptual insight in understanding, as well as in teaching and learning.
Hydraulic Characteristics Of Two Bicycle-Safe Grate Inlet Designs
DOT National Transportation Integrated Search
1988-12-01
Expert Systems are computer programs designed to include a simulation of the reasoning and decision-making processes of human experts. This report provides a set of general guidelines for the development and distribution of highway related expert sys...
Primary expectations of secondary metabolites
USDA-ARS?s Scientific Manuscript database
Plant secondary metabolites (e.g., phenolics) are important for human health, in addition to the organoleptic properties they impart to fresh and processed foods. Consumer expectations such as appearance, taste, or texture influence their purchasing decisions. Thorough identification of phenolic com...
Primary expectations of secondary metabolites
USDA-ARS?s Scientific Manuscript database
My program examines the plant secondary metabolites (i.e. phenolics) important for human health, and which impart the organoleptic properties that are quality indicators for fresh and processed foods. Consumer expectations such as appearance, taste, or texture influence their purchasing decisions; a...
5 CFR 9901.222 - Review of classification decisions.
Code of Federal Regulations, 2011 CFR
2011-01-01
....222 Section 9901.222 Administrative Personnel DEPARTMENT OF DEFENSE HUMAN RESOURCES MANAGEMENT AND LABOR RELATIONS SYSTEMS (DEPARTMENT OF DEFENSE-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF DEFENSE NATIONAL SECURITY PERSONNEL SYSTEM (NSPS) Classification Classification Process § 9901.222 Review of...
OPP Guidance for Submission of State and Tribal Water Quality Monitoring Data
This guidance describes the process to submit state and tribal surface and groundwater monitoring data for consideration in exposure characterizations for ecological and and human health risk assessments and in risk management decisions for pesticides.
Visualization of decision processes using a cognitive architecture
NASA Astrophysics Data System (ADS)
Livingston, Mark A.; Murugesan, Arthi; Brock, Derek; Frost, Wende K.; Perzanowski, Dennis
2013-01-01
Cognitive architectures are computational theories of reasoning the human mind engages in as it processes facts and experiences. A cognitive architecture uses declarative and procedural knowledge to represent mental constructs that are involved in decision making. Employing a model of behavioral and perceptual constraints derived from a set of one or more scenarios, the architecture reasons about the most likely consequence(s) of a sequence of events. Reasoning of any complexity and depth involving computational processes, however, is often opaque and challenging to comprehend. Arguably, for decision makers who may need to evaluate or question the results of autonomous reasoning, it would be useful to be able to inspect the steps involved in an interactive, graphical format. When a chain of evidence and constraint-based decision points can be visualized, it becomes easier to explore both how and why a scenario of interest will likely unfold in a particular way. In initial work on a scheme for visualizing cognitively-based decision processes, we focus on generating graphical representations of models run in the Polyscheme cognitive architecture. Our visualization algorithm operates on a modified version of Polyscheme's output, which is accomplished by augmenting models with a simple set of tags. We provide example visualizations and discuss properties of our technique that pose challenges for our representation goals. We conclude with a summary of feedback solicited from domain experts and practitioners in the field of cognitive modeling.
Griffiths, Kristi R.; Morris, Richard W.; Balleine, Bernard W.
2014-01-01
The ability to learn contingencies between actions and outcomes in a dynamic environment is critical for flexible, adaptive behavior. Goal-directed actions adapt to changes in action-outcome contingencies as well as to changes in the reward-value of the outcome. When networks involved in reward processing and contingency learning are maladaptive, this fundamental ability can be lost, with detrimental consequences for decision-making. Impaired decision-making is a core feature in a number of psychiatric disorders, ranging from depression to schizophrenia. The argument can be developed, therefore, that seemingly disparate symptoms across psychiatric disorders can be explained by dysfunction within common decision-making circuitry. From this perspective, gaining a better understanding of the neural processes involved in goal-directed action, will allow a comparison of deficits observed across traditional diagnostic boundaries within a unified theoretical framework. This review describes the key processes and neural circuits involved in goal-directed decision-making using evidence from animal studies and human neuroimaging. Select studies are discussed to outline what we currently know about causal judgments regarding actions and their consequences, action-related reward evaluation, and, most importantly, how these processes are integrated in goal-directed learning and performance. Finally, we look at how adaptive decision-making is impaired across a range of psychiatric disorders and how deepening our understanding of this circuitry may offer insights into phenotypes and more targeted interventions. PMID:24904322
Deep Space Network (DSN), Network Operations Control Center (NOCC) computer-human interfaces
NASA Technical Reports Server (NTRS)
Ellman, Alvin; Carlton, Magdi
1993-01-01
The technical challenges, engineering solutions, and results of the NOCC computer-human interface design are presented. The use-centered design process was as follows: determine the design criteria for user concerns; assess the impact of design decisions on the users; and determine the technical aspects of the implementation (tools, platforms, etc.). The NOCC hardware architecture is illustrated. A graphical model of the DSN that represented the hierarchical structure of the data was constructed. The DSN spacecraft summary display is shown. Navigation from top to bottom is accomplished by clicking the appropriate button for the element about which the user desires more detail. The telemetry summary display and the antenna color decision table are also shown.
Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System
NASA Astrophysics Data System (ADS)
Ben Rabah, N.; Saddem, R.; Ben Hmida, F.; Carre-Menetrier, V.; Tagina, M.
2017-01-01
Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach.
Application of decision science to resilience management in Jamaica Bay
Eaton, Mitchell; Fuller, Angela K.; Johnson, Fred A.; Hare, M. P.; Stedman, Richard C.; Sanderson, E.W.; Solecki, W. D.; Waldman, J.R.; Paris, A. S.
2016-01-01
This book highlights the growing interest in management interventions designed to enhance the resilience of the Jamaica Bay socio-ecological system. Effective management, whether the focus is on managing biological processes or human behavior or (most likely) both, requires decision makers to anticipate how the managed system will respond to interventions (i.e., via predictions or projections). In systems characterized by many interacting components and high uncertainty, making probabilistic predictions is often difficult and requires careful thinking not only about system dynamics, but also about how management objectives are specified and the analytic method used to select the preferred action(s). Developing a clear statement of the problem(s) and articulation of management objectives is often best achieved by including input from managers, scientists and other stakeholders affected by the decision through a process of joint problem framing (Marcot and others 2012; Keeney and others 1990). Using a deliberate, coherent and transparent framework for deciding among management alternatives to best meet these objectives then ensures a greater likelihood for successful intervention. Decision science provides the theoretical and practical basis for developing this framework and applying decision analysis methods for making complex decisions under uncertainty and risk.
Zendehrouh, Sareh
2015-11-01
Recent work on decision-making field offers an account of dual-system theory for decision-making process. This theory holds that this process is conducted by two main controllers: a goal-directed system and a habitual system. In the reinforcement learning (RL) domain, the habitual behaviors are connected with model-free methods, in which appropriate actions are learned through trial-and-error experiences. However, goal-directed behaviors are associated with model-based methods of RL, in which actions are selected using a model of the environment. Studies on cognitive control also suggest that during processes like decision-making, some cortical and subcortical structures work in concert to monitor the consequences of decisions and to adjust control according to current task demands. Here a computational model is presented based on dual system theory and cognitive control perspective of decision-making. The proposed model is used to simulate human performance on a variant of probabilistic learning task. The basic proposal is that the brain implements a dual controller, while an accompanying monitoring system detects some kinds of conflict including a hypothetical cost-conflict one. The simulation results address existing theories about two event-related potentials, namely error related negativity (ERN) and feedback related negativity (FRN), and explore the best account of them. Based on the results, some testable predictions are also presented. Copyright © 2015 Elsevier Ltd. All rights reserved.
(De)centralization of social support in six Western European countries.
Kroneman, Madelon; Cardol, Mieke; Friele, Roland
2012-06-01
Participation of disabled or chronically ill persons into the society may require support in the sense of human or technical aid. In this study we look into the decision making power of governments and the way citizens are involved in these processes. Decision making power can be political, financial and administrative and may be organized at national, regional or local level. This is a cross-sectional descriptive study of the decision making power in Belgium, France, Germany, the Netherlands, Sweden and the United Kingdom in 2010. We focused on acts and regulations for human and technical aids and for making the environment accessible. Several acts and regulations were identified in relation to social support. In the Netherlands and Sweden social support was mainly organized in one act, whereas in the other countries social support was part of several acts or regulations. Citizen's voice appeared to be represented in boards or advisory committees. Descriptions of entitlements varied from explicitly formulated to globally described. The level of decision making power varies between the countries en between the types of decision making power. Citizens' participation is mainly represented through patient associations. Countries with strongly decentralized decision making make use of framework legislation at national level to set general targets or aims. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
The role of behavioral decision theory for cockpit information management
NASA Technical Reports Server (NTRS)
Jonsson, Jon E.
1991-01-01
The focus of this report is the consideration of one form of cognition, judgment and decision making, while examining some information management issues associated with the implementation of new forms of automation. As technology matures and more tasks become suitable to automation, human factors researchers will have to consider the effect that increasing automation will have on operator performance. Current technology allows flight deck designers the opportunity to automate activities involving substantially more cognitive processing.
NASA Astrophysics Data System (ADS)
Pietrzyk, Mariusz W.; Manning, David J.; Dix, Alan; Donovan, Tim
2009-02-01
Aim: The goal of the study is to determine the spatial frequency characteristics at locations in the image of overt and covert observers' decisions and find out if there are any similarities in different observers' groups: the same radiological experience group or the same accuracy scored level. Background: The radiological task is described as a visual searching decision making procedure involving visual perception and cognitive processing. Humans perceive the world through a number of spatial frequency channels, each sensitive to visual information carried by different spatial frequency ranges and orientations. Recent studies have shown that particular physical properties of local and global image-based elements are correlated with the performance and the level of experience of human observers in breast cancer and lung nodule detections. Neurological findings in visual perception were an inspiration for wavelet applications in vision research because the methodology tries to mimic the brain processing algorithms. Methods: The wavelet approach to the set of postero-anterior chest radiographs analysis has been used to characterize perceptual preferences observers with different levels of experience in the radiological task. Psychophysical methodology has been applied to track eye movements over the image, where particular ROIs related to the observers' fixation clusters has been analysed in the spaces frame by Daubechies functions. Results: Significance differences have been found between the spatial frequency characteristics at the location of different decisions.
Functional Assessment of Genetic Variants with Outcomes Adapted to Clinical Decision-Making
Thouvenot, Pierre; Ben Yamin, Barbara; Fourrière, Lou; Lescure, Aurianne; Boudier, Thomas; Del Nery, Elaine; Chauchereau, Anne; Goldgar, David E.; Stoppa-Lyonnet, Dominique; Nicolas, Alain; Millot, Gaël A.
2016-01-01
Understanding the medical effect of an ever-growing number of human variants detected is a long term challenge in genetic counseling. Functional assays, based on in vitro or in vivo evaluations of the variant effects, provide essential information, but they require robust statistical validation, as well as adapted outputs, to be implemented in the clinical decision-making process. Here, we assessed 25 pathogenic and 15 neutral missense variants of the BRCA1 breast/ovarian cancer susceptibility gene in four BRCA1 functional assays. Next, we developed a novel approach that refines the variant ranking in these functional assays. Lastly, we developed a computational system that provides a probabilistic classification of variants, adapted to clinical interpretation. Using this system, the best functional assay exhibits a variant classification accuracy estimated at 93%. Additional theoretical simulations highlight the benefit of this ready-to-use system in the classification of variants after functional assessment, which should facilitate the consideration of functional evidences in the decision-making process after genetic testing. Finally, we demonstrate the versatility of the system with the classification of siRNAs tested for human cell growth inhibition in high throughput screening. PMID:27272900
From blame to punishment: Disrupting prefrontal cortex activity reveals norm enforcement mechanisms
Buckholtz, Joshua W.; Martin, Justin W.; Treadway, Michael T.; Jan, Katherine; Zald, David H.; Jones, Owen; Marois, René
2017-01-01
Summary Humans maintain a level of cooperation among non-kin that is unrivaled in the animal kingdom. This unique feature of human culture is enabled by our ability to generate, transmit, and follow widely held agreements about morally acceptable and permissible behavior (social norms). However, the social welfare provided by cooperation crucially depends on our ability to enforce these norms by sanctioning those who violate them. Determining moral responsibility and assigning a deserved punishment are two cognitive cornerstones of norm enforcement; together, they form the foundation for modern state-administered systems of justice. Although prior work has implicated the dorsolateral prefrontal cortex (DLPFC) in social norm-based judgments, the relative contribution of this brain region to judgments of moral responsibility and punishment decision-making remains poorly understood. Here, we used repetitive transcranial magnetic stimulation (rTMS) and functional magnetic resonance imaging (fMRI) to determine the specific, causal role of DLPFC function in norm-enforcement behavior. rTMS to DLPFC significantly reduced punishment for wrongful acts without affecting blameworthiness ratings for the same acts, suggesting a neural dissociation between punishment decisions and moral responsibility judgments. We confirmed this dissociation using fMRI: DLPFC is preferentially recruited for punishment decision-making compared to blameworthiness evaluation. Finally, we employed conditional process modeling to show that DLPFC supports punishment decision-making by integrating information about culpability and harm. Together, these findings reveal a selective, causal role for lateral prefrontal cortex in punishment decision-making, and suggest a computational source for this selectivity: the ability of the DLPFC to integrate distinct information processing streams that form the basis of our punishment decisions. PMID:26386518
Artemenko, M V
2008-01-01
Two approaches to calculation of the qualitative measures for assessing the functional state level of human body are considered. These approaches are based on image and fuzzy set recognition theories and are used to construct diagnostic decision rules. The first approach uses the data on deviation of detected parameters from those for healthy persons; the second approach analyzes the degree of deviation of detected parameters from the approximants characterizing the correlation differences between the parameters. A method for synthesis of decision rules and the results of blood count-based research for a number of diseases (hemophilia, thrombocytopathy, hypertension, arrhythmia, hepatic cirrhosis, trichophytia) are considered. An effect of a change in the functional link between the cholesterol content in blood and the relative rate of variation of AST and ALT enzymes in blood from direct proportional (healthy state) to inverse proportional (hepatic cirrhosis) is discussed. It is shown that analysis of correlation changes in detected parameters of the human body state during diagnostic process is more effective for application in decision support systems than the state space analysis.
Karakülah, Gökhan; Dicle, Oğuz; Koşaner, Ozgün; Suner, Aslı; Birant, Çağdaş Can; Berber, Tolga; Canbek, Sezin
2014-01-01
The lack of laboratory tests for the diagnosis of most of the congenital anomalies renders the physical examination of the case crucial for the diagnosis of the anomaly; and the cases in the diagnostic phase are mostly being evaluated in the light of the literature knowledge. In this respect, for accurate diagnosis, ,it is of great importance to provide the decision maker with decision support by presenting the literature knowledge about a particular case. Here, we demonstrated a methodology for automated scanning and determining of the phenotypic features from the case reports related to congenital anomalies in the literature with text and natural language processing methods, and we created a framework of an information source for a potential diagnostic decision support system for congenital anomalies.
Shared decision making in Brazil: Concrete efforts to empower the patients' voice.
Mendes de Abreu, Mirhelen; Simao de Mello, Joao Pedro; Ferreira F Ribeiro, Lilah; Andrade Mussi, Luiza; L Borges, Mariana Luiza; Petroli, Maurício; da Costa Tavares, Nycholas; da Cunha Cancela, Rafael; Fausto de Lima, Sabrina
2017-06-01
Patient involvement in healthcare decisions has grown in Brazil at three different levels: 1) the macro level, which includes the patient actively influencing legislation and regulation of medical care as well as political changes in the process of care itself; 2) the meso level, which includes institutions that aim to improve information, empowerment and counseling to patients, and 3) the micro level, which focuses on the actual decision-making process that takes place within patient-physician encounter. In Brazil, the macro and meso levels are stronger than the micro one. In this paper, the practical efforts to engage patients in the center of their own care are presented. In order to do that, an overview on the National Humanization Policy and the Brazilian patient's movement is provided. Copyright © 2017. Published by Elsevier GmbH.
Awasthi, Bhuvanesh
2017-01-01
Abstract In this study, we investigated the effect of transcranial alternating current stimulation (tACS) on voluntary risky decision making and executive control in humans. Stimulation was delivered online at 5 Hz (θ), 10 Hz (α), 20 Hz (β), and 40 Hz (γ) on the left and right frontal area while participants performed a modified risky decision-making task. This task allowed participants to voluntarily select between risky and certain decisions associated with potential gains or losses, while simultaneously measuring the cognitive control component (voluntary switching) of decision making. The purpose of this experimental design was to test whether voluntary risky decision making and executive control can be modulated with tACS in a frequency-specific manner. Our results revealed a robust effect of a 20-Hz stimulation over the left prefrontal area that significantly increased voluntary risky decision making, which may suggest a possible link between risky decision making and reward processing, underlined by β-oscillatory activity. PMID:29379865
Yaple, Zachary; Martinez-Saito, Mario; Feurra, Matteo; Shestakova, Anna; Klucharev, Vasily
2017-01-01
In this study, we investigated the effect of transcranial alternating current stimulation (tACS) on voluntary risky decision making and executive control in humans. Stimulation was delivered online at 5 Hz (θ), 10 Hz (α), 20 Hz (β), and 40 Hz (γ) on the left and right frontal area while participants performed a modified risky decision-making task. This task allowed participants to voluntarily select between risky and certain decisions associated with potential gains or losses, while simultaneously measuring the cognitive control component (voluntary switching) of decision making. The purpose of this experimental design was to test whether voluntary risky decision making and executive control can be modulated with tACS in a frequency-specific manner. Our results revealed a robust effect of a 20-Hz stimulation over the left prefrontal area that significantly increased voluntary risky decision making, which may suggest a possible link between risky decision making and reward processing, underlined by β-oscillatory activity.
Su, Yu-Shiang; Chen, Jheng-Ting; Tang, Yong-Jheng; Yuan, Shu-Yun; McCarrey, Anna C; Goh, Joshua Oon Soo
2018-05-21
Appropriate neural representation of value and application of decision strategies are necessary to make optimal investment choices in real life. Normative human aging alters neural selectivity and control processing in brain regions implicated in value-based decision processing including striatal, medial temporal, and frontal areas. However, the specific neural mechanisms of how these age-related functional brain changes modulate value processing in older adults remain unclear. Here, young and older adults performed a lottery-choice functional magnetic resonance imaging experiment in which probabilities of winning different magnitudes of points constituted expected values of stakes. Increasing probability of winning modulated striatal responses in young adults, but modulated medial temporal and ventromedial prefrontal areas instead in older adults. Older adults additionally engaged higher responses in dorso-medio-lateral prefrontal cortices to more unfavorable stakes. Such extrastriatal involvement mediated age-related increase in risk-taking decisions. Furthermore, lower resting-state functional connectivity between lateral prefrontal and striatal areas also predicted lottery-choice task risk-taking that was mediated by higher functional connectivity between prefrontal and medial temporal areas during the task, with this mediation relationship being stronger in older than younger adults. Overall, we report evidence of a systemic neural mechanistic change in processing of probability in mixed-lottery values with age that increases risk-taking of unfavorable stakes in older adults. Moreover, individual differences in age-related effects on baseline frontostriatal communication may be a central determinant of such subsequent age differences in value-based decision neural processing and resulting behaviors. Copyright © 2018 Elsevier Inc. All rights reserved.
A model of the human in a cognitive prediction task.
NASA Technical Reports Server (NTRS)
Rouse, W. B.
1973-01-01
The human decision maker's behavior when predicting future states of discrete linear dynamic systems driven by zero-mean Gaussian processes is modeled. The task is on a slow enough time scale that physiological constraints are insignificant compared with cognitive limitations. The model is basically a linear regression system identifier with a limited memory and noisy observations. Experimental data are presented and compared to the model.
Give Design a Chance: A Case for a Human Centered Approach to Operational Art
2017-03-30
strategy development and operational art. This demands fuller integration of the Army Design Methodology (ADM) and the Military Decision Making Process...MDMP). This monograph proposes a way of thinking and planning that goes beyond current Army doctrinal methodologies to address the changing...between conceptual and detailed planning. 15. SUBJECT TERMS Design; Army Design Methodology (ADM); Human Centered; Strategy; Operational Art
Ambiguity and Uncertainty in Probabilistic Inference.
1984-06-01
Bulletin, 1967, 68, 29-46. *Rappoport, A., a Wllston, T. S . *individual decision behavior . Annual Review of Psychology, 1972, 23, 131-176. * Savage, L... Behavior and Human Performance, 1973, 10 40-423. Shafer , G. A. A mathematical theory of evidence. Princeton, NJ: Princeton University Press, 1976.- *~-7... S . Comparison of Bayesian and regression approaches to the study of information processing in judgment. Organizational Behavior and Human
NASA Astrophysics Data System (ADS)
Mishra, S. K.; Ding, D.; Rapolu, U.
2012-12-01
Human activity is intricately linked to the quality and quantity of water resources. Although many studies have examined water-human interaction, the complexity of such coupled systems is not well understood largely because of gaps in our knowledge of water-cycle processes which are heavily influenced by socio-economic drivers. On this context, this team has investigated connections among agriculture, policy, climate, land use/land cover, and water quality in Iowa over the past couple of years. To help explore these connections the team is developing a variety of cyber infrastructure tools that facilitate the collection, analysis and visualization of data, and the simulation of system dynamics. In an ongoing effort, the prototype system is applied to Clear Creek watershed, an agricultural dominating catchment in Iowa in the US Midwest, to understand water-human processes relevant to management decisions by farmers regarding agro ecosystems. The primary aim of this research is to understand the connections that exist among the agricultural and biofuel economy, land use/land cover change, and water quality. To help explore these connections an agent-based model (ABM) of land use change has been developed that simulates the decisions made by farmers given alternative assumptions about market forces, farmer characteristics, and water quality regulations. The SWAT model was used to simulate the impact of these decisions on the movement of sediment, nitrogen, and phosphorus across the landscape. The paper also demonstrate how through the use of this system researchers can, for example, search for scenarios that lead to desirable socio-economic outcomes as well as preserve water quantity and quality.
What is adaptive about adaptive decision making? A parallel constraint satisfaction account.
Glöckner, Andreas; Hilbig, Benjamin E; Jekel, Marc
2014-12-01
There is broad consensus that human cognition is adaptive. However, the vital question of how exactly this adaptivity is achieved has remained largely open. Herein, we contrast two frameworks which account for adaptive decision making, namely broad and general single-mechanism accounts vs. multi-strategy accounts. We propose and fully specify a single-mechanism model for decision making based on parallel constraint satisfaction processes (PCS-DM) and contrast it theoretically and empirically against a multi-strategy account. To achieve sufficiently sensitive tests, we rely on a multiple-measure methodology including choice, reaction time, and confidence data as well as eye-tracking. Results show that manipulating the environmental structure produces clear adaptive shifts in choice patterns - as both frameworks would predict. However, results on the process level (reaction time, confidence), in information acquisition (eye-tracking), and from cross-predicting choice consistently corroborate single-mechanisms accounts in general, and the proposed parallel constraint satisfaction model for decision making in particular. Copyright © 2014 Elsevier B.V. All rights reserved.
Disrupting the right prefrontal cortex alters moral judgement.
Tassy, Sébastien; Oullier, Olivier; Duclos, Yann; Coulon, Olivier; Mancini, Julien; Deruelle, Christine; Attarian, Sharam; Felician, Olivier; Wicker, Bruno
2012-03-01
Humans daily face social situations involving conflicts between competing moral decision. Despite a substantial amount of studies published over the past 10 years, the respective role of emotions and reason, their possible interaction, and their behavioural expression during moral evaluation remains an unresolved issue. A dualistic approach to moral evaluation proposes that the right dorsolateral prefrontal cortex (rDLPFc) controls emotional impulses. However, recent findings raise the possibility that the right DLPFc processes emotional information during moral decision making. We used repetitive transcranial magnetic stimulation (rTMS) to transiently disrupt rDLPFc activity before measuring decision making in the context of moral dilemmas. Results reveal an increase of the probability of utilitarian responses during objective evaluation of moral dilemmas in the rTMS group (compared to a SHAM one). This suggests that the right DLPFc function not only participates to a rational cognitive control process, but also integrates emotions generated by contextual information appraisal, which are decisive for response selection in moral judgements. © The Author (2011). Published by Oxford University Press.
Disrupting the right prefrontal cortex alters moral judgement
Tassy, Sébastien; Oullier, Olivier; Duclos, Yann; Coulon, Olivier; Mancini, Julien; Deruelle, Christine; Attarian, Sharam; Felician, Olivier
2012-01-01
Humans daily face social situations involving conflicts between competing moral decision. Despite a substantial amount of studies published over the past 10 years, the respective role of emotions and reason, their possible interaction, and their behavioural expression during moral evaluation remains an unresolved issue. A dualistic approach to moral evaluation proposes that the right dorsolateral prefrontal cortex (rDLPFc) controls emotional impulses. However, recent findings raise the possibility that the right DLPFc processes emotional information during moral decision making. We used repetitive transcranial magnetic stimulation (rTMS) to transiently disrupt rDLPFc activity before measuring decision making in the context of moral dilemmas. Results reveal an increase of the probability of utilitarian responses during objective evaluation of moral dilemmas in the rTMS group (compared to a SHAM one). This suggests that the right DLPFc function not only participates to a rational cognitive control process, but also integrates emotions generated by contextual information appraisal, which are decisive for response selection in moral judgements. PMID:21515641
Diffusion Modelling Reveals the Decision Making Processes Underlying Negative Judgement Bias in Rats
Hales, Claire A.; Robinson, Emma S. J.; Houghton, Conor J.
2016-01-01
Human decision making is modified by emotional state. Rodents exhibit similar biases during interpretation of ambiguous cues that can be altered by affective state manipulations. In this study, the impact of negative affective state on judgement bias in rats was measured using an ambiguous-cue interpretation task. Acute treatment with an anxiogenic drug (FG7142), and chronic restraint stress and social isolation both induced a bias towards more negative interpretation of the ambiguous cue. The diffusion model was fit to behavioural data to allow further analysis of the underlying decision making processes. To uncover the way in which parameters vary together in relation to affective state manipulations, independent component analysis was conducted on rate of information accumulation and distances to decision threshold parameters for control data. Results from this analysis were applied to parameters from negative affective state manipulations. These projected components were compared to control components to reveal the changes in decision making processes that are due to affective state manipulations. Negative affective bias in rodents induced by either FG7142 or chronic stress is due to a combination of more negative interpretation of the ambiguous cue, reduced anticipation of the high reward and increased anticipation of the low reward. PMID:27023442
Reaching a Consensus: Terminology and Concepts Used in Coordination and Decision-Making Research.
Pyritz, Lennart W; King, Andrew J; Sueur, Cédric; Fichtel, Claudia
2011-12-01
Research on coordination and decision-making in humans and nonhuman primates has increased considerably throughout the last decade. However, terminology has been used inconsistently, hampering the broader integration of results from different studies. In this short article, we provide a glossary containing the central terms of coordination and decision-making research. The glossary is based on previous definitions that have been critically revised and annotated by the participants of the symposium "Where next? Coordination and decision-making in primate groups" at the XXIIIth Congress of the International Primatological Society (IPS) in Kyoto, Japan. We discuss a number of conceptual and methodological issues and highlight consequences for their implementation. In summary, we recommend that future studies on coordination and decision-making in animal groups do not use the terms "combined decision" and "democratic/despotic decision-making." This will avoid ambiguity as well as anthropocentric connotations. Further, we demonstrate the importance of 1) taxon-specific definitions of coordination parameters (initiation, leadership, followership, termination), 2) differentiation between coordination research on individual-level process and group-level outcome, 3) analyses of collective action processes including initiation and termination, and 4) operationalization of successful group movements in the field to collect meaningful and comparable data across different species.
van 't Wout, Mascha; Kahn, René S; Sanfey, Alan G; Aleman, André
2005-11-07
Although decision-making is typically seen as a rational process, emotions play a role in tasks that include unfairness. Recently, activation in the right dorsolateral prefrontal cortex during offers experienced as unfair in the Ultimatum Game was suggested to subserve goal maintenance in this task. This is restricted to correlational evidence, however, and it remains unclear whether the dorsolateral prefrontal cortex is crucial for strategic decision-making. The present study used repetitive transcranial magnetic stimulation in order to investigate the causal role of the dorsolateral prefrontal cortex in strategic decision-making in the Ultimatum Game. The results showed that repetitive transcranial magnetic stimulation over the right dorsolateral prefrontal cortex resulted in an altered decision-making strategy compared with sham stimulation. We conclude that the dorsolateral prefrontal cortex is causally implicated in strategic decision-making in healthy human study participants.
Plant phenolics – from field to fork
USDA-ARS?s Scientific Manuscript database
Plant secondary metabolites, such as phenolics, are important to human health and for the organoleptic properties they impart to fresh and processed foods. Consumers judge appearance, taste, and texture when making purchasing decisions. Thorough identification of phenolic compounds is key to discern...
MAJOR MONITORING NETWORKS: A FOUNDATION TO PRESERVE, PROTECT AND RESTORE
MAJOR MONITORING NETWORKS: A FOUNDATION TO PRESERVE, PROTECT, AND RESTORE
Ideally, major human and environmental monitoring networks should provide the scientific information needed for policy and management decision-making processes. It is widely recognized that reliable...
Humane Education: Science, Technology, and Society in the English Classroom.
ERIC Educational Resources Information Center
Emeigh, Tonya Huber
1988-01-01
Presents "Beastly Thoughts," a holistic writing module designed to involve students in decision-making processes about socially relevant issues regarding animals. Provides 48 activities for investigation and lists 33 references for possible book reviews. Includes 38 references. (MVL)
Spatial Assessment of Forest Ecosystem Functions and Services using Human Relating Factors for SDG
NASA Astrophysics Data System (ADS)
Song, C.; Lee, W. K.; Jeon, S. W.; Kim, T.; Lim, C. H.
2015-12-01
Application of ecosystem service concept in environmental related decision making could be numerical and objective standard for policy maker between preserving and developing perspective of environment. However, pursuing maximum benefit from natural capital through ecosystem services caused failure by losing ecosystem functions through its trade-offs. Therefore, difference between ecosystem functions and services were demonstrated and would apply human relating perspectives. Assessment results of ecosystem functions and services can be divided 3 parts. Tree growth per year set as the ecosystem function factor and indicated through so called pure function map. After that, relating functions can be driven such as water conservation, air pollutant purification, climate change regulation, and timber production. Overall process and amount are numerically quantified. These functional results can be transferred to ecosystem services by multiplying economic unit value, so function reflecting service maps can be generated. On the other hand, above services, to implement more reliable human demand, human reflecting service maps are also be developed. As the validation, quantified ecosystem functions are compared with former results through pixel based analysis. Three maps are compared, and through comparing difference between ecosystem function and services and inversed trends in function based and human based service are analysed. In this study, we could find differences in PF, FRS, and HRS in relation to based ecosystem conditions. This study suggests that the differences in PF, FRS, and HRS should be understood in the decision making process for sustainable management of ecosystem services. Although the analysis is based on in sort existing process separation, it is important to consider the possibility of different usage of ecosystem function assessment results and ecosystem service assessment results in SDG policy making. Furthermore, process based functional approach can suggest environmental information which is reflected the other kinds of perspective.
Following Human Footsteps: Proposal of a Decision Theory Based on Human Behavior
NASA Technical Reports Server (NTRS)
Mahmud, Faisal
2011-01-01
Human behavior is a complex nature which depends on circumstances and decisions varying from time to time as well as place to place. The way a decision is made either directly or indirectly related to the availability of the options. These options though appear at random nature, have a solid directional way for decision making. In this paper, a decision theory is proposed which is based on human behavior. The theory is structured with model sets that will show the all possible combinations for making a decision, A virtual and simulated environment is considered to show the results of the proposed decision theory
Distributions of observed death tolls govern sensitivity to human fatalities
Olivola, Christopher Y.; Sagara, Namika
2009-01-01
How we react to humanitarian crises, epidemics, and other tragic events involving the loss of human lives depends largely on the extent to which we are moved by the size of their associated death tolls. Many studies have demonstrated that people generally exhibit a diminishing sensitivity to the number of human fatalities and, equivalently, a preference for risky (vs. sure) alternatives in decisions under risk involving human losses. However, the reason for this tendency remains unknown. Here we show that the distributions of event-related death tolls that people observe govern their evaluations of, and risk preferences concerning, human fatalities. In particular, we show that our diminishing sensitivity to human fatalities follows from the fact that these death tolls are approximately power-law distributed. We further show that, by manipulating the distribution of mortality-related events that people observe, we can alter their risk preferences in decisions involving fatalities. Finally, we show that the tendency to be risk-seeking in mortality-related decisions is lower in countries in which high-mortality events are more frequently observed. Our results support a model of magnitude evaluation based on memory sampling and relative judgment. This model departs from the utility-based approaches typically encountered in psychology and economics in that it does not rely on stable, underlying value representations to explain valuation and choice, or on choice behavior to derive value functions. Instead, preferences concerning human fatalities emerge spontaneously from the distributions of sampled events and the relative nature of the evaluation process. PMID:20018778
NASA Astrophysics Data System (ADS)
Spak, S.; Pooley, M.
2012-12-01
The next generation of coupled human and earth systems models promises immense potential and grand challenges as they transition toward new roles as core tools for defining and living within planetary boundaries. New frontiers in community model development include not only computational, organizational, and geophysical process questions, but also the twin objectives of more meaningfully integrating the human dimension and extending applicability to informing policy decisions on a range of new and interconnected issues. We approach these challenges by posing key policy questions that require more comprehensive coupled human and geophysical models, identify necessary model and organizational processes and outputs, and work backwards to determine design criteria in response to these needs. We find that modular community earth system model design must: * seamlessly scale in space (global to urban) and time (nowcasting to paleo-studies) and fully coupled on all component systems * automatically differentiate to provide complete coupled forward and adjoint models for sensitivity studies, optimization applications, and 4DVAR assimilation across Earth and human observing systems * incorporate diagnostic tools to quantify uncertainty in couplings, and in how human activity affects them * integrate accessible community development and application with JIT-compilation, cloud computing, game-oriented interfaces, and crowd-sourced problem-solving We outline accessible near-term objectives toward these goals, and describe attempts to incorporate these design objectives in recent pilot activities using atmosphere-land-ocean-biosphere-human models (WRF-Chem, IBIS, UrbanSim) at urban and regional scales for policy applications in climate, energy, and air quality.
Perceived Need for a Parental Decision Aid for the HPV Vaccine: Content and Format Preferences
Lechuga, Julia; Swain, Geoffrey; Weinhardt, Lance S.
2014-01-01
The human papillomavirus (HPV) is a precursor of cervical cancer. In 2006, the Federal Drug Administration licensed a vaccine to protect against four types of HPV. Three years postlicensure of the vaccine, HPV vaccination is still fraught with controversy. To date, research suggests that contrary to popular notions, parents are less concerned with controversies on moral issues and more with uncertainty regarding because long-term safety of a drug is resolved after licensure. This study was designed to understand whether mothers from diverse ethnicities perceive a need for a decision support tool. Results suggest that the design of a culturally tailored decision support tool may help guide parents through the decision-making process. PMID:21444922
Perceived need of a parental decision aid for the HPV vaccine: content and format preferences.
Lechuga, Julia; Swain, Geoffrey; Weinhardt, Lance S
2012-03-01
The human papillomavirus (HPV) is a precursor of cervical cancer. In 2006, the Federal Drug Administration licensed a vaccine to protect against four types of HPV. Three years postlicensure of the vaccine, HPV vaccination is still fraught with controversy. To date, research suggests that contrary to popular notions, parents are less concerned with controversies on moral issues and more with uncertainty regarding because long-term safety of a drug is resolved after licensure. This study was designed to understand whether mothers from diverse ethnicities perceive a need for a decision support tool. Results suggest that the design of a culturally tailored decision support tool may help guide parents through the decision-making process.
A computational model of the human visual cortex
NASA Astrophysics Data System (ADS)
Albus, James S.
2008-04-01
The brain is first and foremost a control system that is capable of building an internal representation of the external world, and using this representation to make decisions, set goals and priorities, formulate plans, and control behavior with intent to achieve its goals. The computational model proposed here assumes that this internal representation resides in arrays of cortical columns. More specifically, it models each cortical hypercolumn together with its underlying thalamic nuclei as a Fundamental Computational Unit (FCU) consisting of a frame-like data structure (containing attributes and pointers) plus the computational processes and mechanisms required to maintain it. In sensory-processing areas of the brain, FCUs enable segmentation, grouping, and classification. Pointers stored in FCU frames link pixels and signals to objects and events in situations and episodes that are overlaid with meaning and emotional values. In behavior-generating areas of the brain, FCUs make decisions, set goals and priorities, generate plans, and control behavior. Pointers are used to define rules, grammars, procedures, plans, and behaviors. It is suggested that it may be possible to reverse engineer the human brain at the FCU level of fidelity using nextgeneration massively parallel computer hardware and software. Key Words: computational modeling, human cortex, brain modeling, reverse engineering the brain, image processing, perception, segmentation, knowledge representation
A dataset of human decision-making in teamwork management.
Yu, Han; Shen, Zhiqi; Miao, Chunyan; Leung, Cyril; Chen, Yiqiang; Fauvel, Simon; Lin, Jun; Cui, Lizhen; Pan, Zhengxiang; Yang, Qiang
2017-01-17
Today, most endeavours require teamwork by people with diverse skills and characteristics. In managing teamwork, decisions are often made under uncertainty and resource constraints. The strategies and the effectiveness of the strategies different people adopt to manage teamwork under different situations have not yet been fully explored, partially due to a lack of detailed large-scale data. In this paper, we describe a multi-faceted large-scale dataset to bridge this gap. It is derived from a game simulating complex project management processes. It presents the participants with different conditions in terms of team members' capabilities and task characteristics for them to exhibit their decision-making strategies. The dataset contains detailed data reflecting the decision situations, decision strategies, decision outcomes, and the emotional responses of 1,144 participants from diverse backgrounds. To our knowledge, this is the first dataset simultaneously covering these four facets of decision-making. With repeated measurements, the dataset may help establish baseline variability of decision-making in teamwork management, leading to more realistic decision theoretic models and more effective decision support approaches.
A dataset of human decision-making in teamwork management
Yu, Han; Shen, Zhiqi; Miao, Chunyan; Leung, Cyril; Chen, Yiqiang; Fauvel, Simon; Lin, Jun; Cui, Lizhen; Pan, Zhengxiang; Yang, Qiang
2017-01-01
Today, most endeavours require teamwork by people with diverse skills and characteristics. In managing teamwork, decisions are often made under uncertainty and resource constraints. The strategies and the effectiveness of the strategies different people adopt to manage teamwork under different situations have not yet been fully explored, partially due to a lack of detailed large-scale data. In this paper, we describe a multi-faceted large-scale dataset to bridge this gap. It is derived from a game simulating complex project management processes. It presents the participants with different conditions in terms of team members’ capabilities and task characteristics for them to exhibit their decision-making strategies. The dataset contains detailed data reflecting the decision situations, decision strategies, decision outcomes, and the emotional responses of 1,144 participants from diverse backgrounds. To our knowledge, this is the first dataset simultaneously covering these four facets of decision-making. With repeated measurements, the dataset may help establish baseline variability of decision-making in teamwork management, leading to more realistic decision theoretic models and more effective decision support approaches. PMID:28094787
A dataset of human decision-making in teamwork management
NASA Astrophysics Data System (ADS)
Yu, Han; Shen, Zhiqi; Miao, Chunyan; Leung, Cyril; Chen, Yiqiang; Fauvel, Simon; Lin, Jun; Cui, Lizhen; Pan, Zhengxiang; Yang, Qiang
2017-01-01
Today, most endeavours require teamwork by people with diverse skills and characteristics. In managing teamwork, decisions are often made under uncertainty and resource constraints. The strategies and the effectiveness of the strategies different people adopt to manage teamwork under different situations have not yet been fully explored, partially due to a lack of detailed large-scale data. In this paper, we describe a multi-faceted large-scale dataset to bridge this gap. It is derived from a game simulating complex project management processes. It presents the participants with different conditions in terms of team members' capabilities and task characteristics for them to exhibit their decision-making strategies. The dataset contains detailed data reflecting the decision situations, decision strategies, decision outcomes, and the emotional responses of 1,144 participants from diverse backgrounds. To our knowledge, this is the first dataset simultaneously covering these four facets of decision-making. With repeated measurements, the dataset may help establish baseline variability of decision-making in teamwork management, leading to more realistic decision theoretic models and more effective decision support approaches.
Expert judgment and uncertainty regarding the protection of imperiled species.
Heeren, Alexander; Karns, Gabriel; Bruskotter, Jeremy; Toman, Eric; Wilson, Robyn; Szarek, Harmony
2017-06-01
Decisions concerning the appropriate listing status of species under the U.S. Endangered Species Act (ESA) can be controversial even among conservationists. These decisions may determine whether a species persists in the near term and have long-lasting social and political ramifications. Given the ESA's mandate that such decisions be based on the best available science, it is important to examine what factors contribute to experts' judgments concerning the listing of species. We examined how a variety of factors (such as risk perception, value orientations, and norms) influenced experts' judgments concerning the appropriate listing status of the grizzly bear (Ursus arctos horribilis) population in the Greater Yellowstone Ecosystem. Experts were invited to complete an online survey examining their perceptions of the threats grizzly bears face and their listing recommendation. Although experts' assessments of the threats to this species were strongly correlated with their recommendations for listing status, this relationship did not exist when other cognitive factors were included in the model. Specifically, values related to human use of wildlife and norms (i.e., a respondent's expectation of peers' assessments) were most influential in listing status recommendations. These results suggest that experts' decisions about listing, like all human decisions, are subject to the use of heuristics (i.e., decision shortcuts). An understanding of how heuristics and related biases affect decisions under uncertainty can help inform decision making about threatened and endangered species and may be useful in designing effective processes for protection of imperiled species. © 2016 Society for Conservation Biology.
NASA Astrophysics Data System (ADS)
Lin, Zi-Jing; Li, Lin; Cazzell, Marry; Liu, Hanli
2013-03-01
Functional near-infrared spectroscopy (fNIRS) is a non-invasive imaging technique which measures the hemodynamic changes that reflect the brain activity. Diffuse optical tomography (DOT), a variant of fNIRS with multi-channel NIRS measurements, has demonstrated capability of three dimensional (3D) reconstructions of hemodynamic changes due to the brain activity. Conventional method of DOT image analysis to define the brain activation is based upon the paired t-test between two different states, such as resting-state versus task-state. However, it has limitation because the selection of activation and post-activation period is relatively subjective. General linear model (GLM) based analysis can overcome this limitation. In this study, we combine the 3D DOT image reconstruction with GLM-based analysis (i.e., voxel-wise GLM analysis) to investigate the brain activity that is associated with the risk-decision making process. Risk decision-making is an important cognitive process and thus is an essential topic in the field of neuroscience. The balloon analogue risk task (BART) is a valid experimental model and has been commonly used in behavioral measures to assess human risk taking action and tendency while facing risks. We have utilized the BART paradigm with a blocked design to investigate brain activations in the prefrontal and frontal cortical areas during decision-making. Voxel-wise GLM analysis was performed on 18human participants (10 males and 8females).In this work, we wish to demonstrate the feasibility of using voxel-wise GLM analysis to image and study cognitive functions in response to risk decision making by DOT. Results have shown significant changes in the dorsal lateral prefrontal cortex (DLPFC) during the active choice mode and a different hemodynamic pattern between genders, which are in good agreements with published literatures in functional magnetic resonance imaging (fMRI) and fNIRS studies.
Normalized value coding explains dynamic adaptation in the human valuation process.
Khaw, Mel W; Glimcher, Paul W; Louie, Kenway
2017-11-28
The notion of subjective value is central to choice theories in ecology, economics, and psychology, serving as an integrated decision variable by which options are compared. Subjective value is often assumed to be an absolute quantity, determined in a static manner by the properties of an individual option. Recent neurobiological studies, however, have shown that neural value coding dynamically adapts to the statistics of the recent reward environment, introducing an intrinsic temporal context dependence into the neural representation of value. Whether valuation exhibits this kind of dynamic adaptation at the behavioral level is unknown. Here, we show that the valuation process in human subjects adapts to the history of previous values, with current valuations varying inversely with the average value of recently observed items. The dynamics of this adaptive valuation are captured by divisive normalization, linking these temporal context effects to spatial context effects in decision making as well as spatial and temporal context effects in perception. These findings suggest that adaptation is a universal feature of neural information processing and offer a unifying explanation for contextual phenomena in fields ranging from visual psychophysics to economic choice.
Parasuraman, Raja; Jiang, Yang
2012-01-01
We describe the use of behavioral, neuroimaging, and genetic methods to examine individual differences in cognition and affect, guided by three criteria: (1) relevance to human performance in work and everyday settings; (2) interactions between working memory, decision-making, and affective processing; and (3) examination of individual differences. The results of behavioral, functional MRI (fMRI), event-related potential (ERP), and molecular genetic studies show that analyses at the group level often mask important findings associated with sub-groups of individuals. Dopaminergic/noradrenergic genes influencing prefrontal cortex activity contribute to inter-individual variation in working memory and decision behavior, including performance in complex simulations of military decision-making. The interactive influences of individual differences in anxiety, sensation seeking, and boredom susceptibility on evaluative decision-making can be systematically described using ERP and fMRI methods. We conclude that a multi-modal neuroergonomic approach to examining brain function (using both neuroimaging and molecular genetics) can be usefully applied to understanding individual differences in cognition and affect and has implications for human performance at work. PMID:21569853
Human factors research problems in electronic voice warning system design
NASA Technical Reports Server (NTRS)
Simpson, C. A.; Williams, D. H.
1975-01-01
The speech messages issued by voice warning systems must be carefully designed in accordance with general principles of human decision making processes, human speech comprehension, and the conditions in which the warnings can occur. The operator's effectiveness must not be degraded by messages that are either inappropriate or difficult to comprehend. Important experimental variables include message content, linguistic redundancy, signal/noise ratio, interference with concurrent tasks, and listener expectations generated by the pragmatic or real world context in which the messages are presented.
Cocker, Paul J; Hosking, Jay G; Benoit, James; Winstanley, Catharine A
2012-07-01
Amotivational states and insufficient recruitment of mental effort have been observed in a variety of clinical populations, including depression, traumatic brain injury, post-traumatic stress disorder, and attention deficit hyperactivity disorder. Previous rodent models of effort-based decision making have utilized physical costs whereas human studies of effort are primarily cognitive in nature, and it is unclear whether the two types of effortful decision making are underpinned by the same neurobiological processes. We therefore designed a novel rat cognitive effort task (rCET) based on the 5-choice serial reaction time task, a well-validated measure of attention and impulsivity. Within each trial of the rCET, rats are given the choice between an easy or hard visuospatial discrimination, and successful hard trials are rewarded with double the number of sugar pellets. Similar to previous human studies, stable individual variation in choice behavior was observed, with 'workers' choosing hard trials significantly more than their 'slacker' counterparts. Whereas workers 'slacked off' in response to administration of amphetamine and caffeine, slackers 'worked harder' under amphetamine, but not caffeine. Conversely, these stimulants increased motor impulsivity in all animals. Ethanol did not affect animals' choice but invigorated behavior. In sum, we have shown for the first time that rats are differentially sensitive to cognitive effort when making decisions, independent of other processes such as impulsivity, and these baseline differences can influence the cognitive response to psychostimulants. Such findings could inform our understanding of impairments in effort-based decision making and contribute to treatment development.
Cocker, Paul J; Hosking, Jay G; Benoit, James; Winstanley, Catharine A
2012-01-01
Amotivational states and insufficient recruitment of mental effort have been observed in a variety of clinical populations, including depression, traumatic brain injury, post-traumatic stress disorder, and attention deficit hyperactivity disorder. Previous rodent models of effort-based decision making have utilized physical costs whereas human studies of effort are primarily cognitive in nature, and it is unclear whether the two types of effortful decision making are underpinned by the same neurobiological processes. We therefore designed a novel rat cognitive effort task (rCET) based on the 5-choice serial reaction time task, a well-validated measure of attention and impulsivity. Within each trial of the rCET, rats are given the choice between an easy or hard visuospatial discrimination, and successful hard trials are rewarded with double the number of sugar pellets. Similar to previous human studies, stable individual variation in choice behavior was observed, with ‘workers' choosing hard trials significantly more than their ‘slacker' counterparts. Whereas workers ‘slacked off' in response to administration of amphetamine and caffeine, slackers ‘worked harder' under amphetamine, but not caffeine. Conversely, these stimulants increased motor impulsivity in all animals. Ethanol did not affect animals' choice but invigorated behavior. In sum, we have shown for the first time that rats are differentially sensitive to cognitive effort when making decisions, independent of other processes such as impulsivity, and these baseline differences can influence the cognitive response to psychostimulants. Such findings could inform our understanding of impairments in effort-based decision making and contribute to treatment development. PMID:22453140
ERIC Educational Resources Information Center
Arnold, Gordon B.
A study of the college curriculum decision-making process examined the generation of options or alternatives considered as part of a general education curriculum revision in the late 1980s at a major church-affiliated university. This process was examined in the framework of the rational-choice model of human behavior. Data were gathered from a…
ERIC Educational Resources Information Center
Borowsky, Ron; Besner, Derek
2006-01-01
D. C. Plaut and J. R. Booth presented a parallel distributed processing model that purports to simulate human lexical decision performance. This model (and D. C. Plaut, 1995) offers a single mechanism account of the pattern of factor effects on reaction time (RT) between semantic priming, word frequency, and stimulus quality without requiring a…
Proceedings of the international conference on cybernetics and societ
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1985-01-01
This book presents the papers given at a conference on artificial intelligence, expert systems and knowledge bases. Topics considered at the conference included automating expert system development, modeling expert systems, causal maps, data covariances, robot vision, image processing, multiprocessors, parallel processing, VLSI structures, man-machine systems, human factors engineering, cognitive decision analysis, natural language, computerized control systems, and cybernetics.
Expectations Do Not Alter Early Sensory Processing during Perceptual Decision-Making.
Rungratsameetaweemana, Nuttida; Itthipuripat, Sirawaj; Salazar, Annalisa; Serences, John T
2018-06-13
Two factors play important roles in shaping perception: the allocation of selective attention to behaviorally relevant sensory features, and prior expectations about regularities in the environment. Signal detection theory proposes distinct roles of attention and expectation on decision-making such that attention modulates early sensory processing, whereas expectation influences the selection and execution of motor responses. Challenging this classic framework, recent studies suggest that expectations about sensory regularities enhance the encoding and accumulation of sensory evidence during decision-making. However, it is possible, that these findings reflect well documented attentional modulations in visual cortex. Here, we tested this framework in a group of male and female human participants by examining how expectations about stimulus features (orientation and color) and expectations about motor responses impacted electroencephalography (EEG) markers of early sensory processing and the accumulation of sensory evidence during decision-making (the early visual negative potential and the centro-parietal positive potential, respectively). We first demonstrate that these markers are sensitive to changes in the amount of sensory evidence in the display. Then we show, counter to recent findings, that neither marker is modulated by either feature or motor expectations, despite a robust effect of expectations on behavior. Instead, violating expectations about likely sensory features and motor responses impacts posterior alpha and frontal theta oscillations, signals thought to index overall processing time and cognitive conflict. These findings are inconsistent with recent theoretical accounts and suggest instead that expectations primarily influence decisions by modulating post-perceptual stages of information processing. SIGNIFICANCE STATEMENT Expectations about likely features or motor responses play an important role in shaping behavior. Classic theoretical frameworks posit that expectations modulate decision-making by biasing late stages of decision-making including the selection and execution of motor responses. In contrast, recent accounts suggest that expectations also modulate decisions by improving the quality of early sensory processing. However, these effects could instead reflect the influence of selective attention. Here we examine the effect of expectations about sensory features and motor responses on a set of electroencephalography (EEG) markers that index early sensory processing and later post-perceptual processing. Counter to recent empirical results, expectations have little effect on early sensory processing but instead modulate EEG markers of time-on-task and cognitive conflict. Copyright © 2018 the authors 0270-6474/18/385632-17$15.00/0.
An optimal brain can be composed of conflicting agents
Livnat, Adi; Pippenger, Nicholas
2006-01-01
Many behaviors have been attributed to internal conflict within the animal and human mind. However, internal conflict has not been reconciled with evolutionary principles, in that it appears maladaptive relative to a seamless decision-making process. We study this problem through a mathematical analysis of decision-making structures. We find that, under natural physiological limitations, an optimal decision-making system can involve “selfish” agents that are in conflict with one another, even though the system is designed for a single purpose. It follows that conflict can emerge within a collective even when natural selection acts on the level of the collective only. PMID:16492775
Human rights of the mentally ill in Indonesia.
Nurjannah, I; Mills, J; Park, T; Usher, K
2015-06-01
The mentally ill are vulnerable to human rights violations, particularly in Indonesia, where shackling is widespread. The aim of this study was to understand the provision of mental health care in Indonesia, thereby identifying ways to improve care and better support carers. Grounded theory methods were used. Study participants included health professionals, non-health professionals and individuals living with a mental disorder who were well at the time (n = 49). Data were collected through interviews conducted in 2011 and 2012. The core category of this grounded theory is 'connecting care' a term coined by the authors to describe a model of care that involves health professionals and non-health professionals, such as family members. Four main factors influence care-providers' decision-making: competence, willingness, available resources and compliance with institutional policy. Health professionals are influenced most strongly by institutional policy when deciding whether to accept or shift responsibility to provide care. Non-health professionals base their decisions largely on personal circumstances. Jointly-made decisions can be matched or unmatched. Unmatched decisions can result in forced provision of care, increasing risks of human rights violations. Generalization of this grounded theory is difficult as the research was conducted in two provinces of Indonesia. Institutional policy was important in the process of connecting care for the mentally ill in Indonesia and needs to be underpinned by legislation to protect human rights. Strengthening mental health legislation in Indonesia will allow nurses to connect care more effectively. © 2014 International Council of Nurses.
[Chakrabarty today: 30 years after the United States Supreme Court Resolution].
Bergel, Salvador Darío
2010-01-01
The decision of the United States Supreme Court in the Chakrabarty case marked the beginning of a far reaching process, the development of which considerably extended the field of patentabiltiy of humans, their body parts and genetic information. The author believes that a period of three decades is sufficient to draw conclusions. A critical point has been reached from a debatable decision, which had more economic support than legal, which requires serious recapitulation of the scope and the purpose of industrial property rights.
Analysis and asynchronous detection of gradually unfolding errors during monitoring tasks
NASA Astrophysics Data System (ADS)
Omedes, Jason; Iturrate, Iñaki; Minguez, Javier; Montesano, Luis
2015-10-01
Human studies on cognitive control processes rely on tasks involving sudden-onset stimuli, which allow the analysis of these neural imprints to be time-locked and relative to the stimuli onset. Human perceptual decisions, however, comprise continuous processes where evidence accumulates until reaching a boundary. Surpassing the boundary leads to a decision where measured brain responses are associated to an internal, unknown onset. The lack of this onset for gradual stimuli hinders both the analyses of brain activity and the training of detectors. This paper studies electroencephalographic (EEG)-measurable signatures of human processing for sudden and gradual cognitive processes represented as a trajectory mismatch under a monitoring task. Time-locked potentials and brain-source analysis of the EEG of sudden mismatches revealed the typical components of event-related potentials and the involvement of brain structures related to cognitive control processing. For gradual mismatch events, time-locked analyses did not show any discernible EEG scalp pattern, despite related brain areas being, to a lesser extent, activated. However, and thanks to the use of non-linear pattern recognition algorithms, it is possible to train an asynchronous detector on sudden events and use it to detect gradual mismatches, as well as obtaining an estimate of their unknown onset. Post-hoc time-locked scalp and brain-source analyses revealed that the EEG patterns of detected gradual mismatches originated in brain areas related to cognitive control processing. This indicates that gradual events induce latency in the evaluation process but that similar brain mechanisms are present in sudden and gradual mismatch events. Furthermore, the proposed asynchronous detection model widens the scope of applications of brain-machine interfaces to other gradual processes.
COMPUTERIZED RISK AND BIOACCUMULATION SYSTEM (VERSION 1.0)
CRABS is a combination of a rule-based expert system and more traditional procedural programming techniques. ule-based expert systems attempt to emulate the decision making process of human experts within a clearly defined subject area. xpert systems consist of an "inference engi...
Treatment with Tyrosine, a Neurotransmitter Precursor, Reduces Environmental Stress in Humans,
1988-03-01
knowledge to problems, processing spatial and verbal information, performing mathematical calculations, and making decisions (16). We also measured... decaffeinated coffee were also available. Subjects refrained from alcohol consumption at least twenty four hours before each test day. The evening
Content-specific evidence accumulation in inferior temporal cortex during perceptual decision-making
Tremel, Joshua J.; Wheeler, Mark E.
2015-01-01
During a perceptual decision, neuronal activity can change as a function of time-integrated evidence. Such neurons may serve as decision variables, signaling a choice when activity reaches a boundary. Because the signals occur on a millisecond timescale, translating to human decision-making using functional neuroimaging has been challenging. Previous neuroimaging work in humans has identified patterns of neural activity consistent with an accumulation account. However, the degree to which the accumulating neuroimaging signals reflect specific sources of perceptual evidence is unknown. Using an extended face/house discrimination task in conjunction with cognitive modeling, we tested whether accumulation signals, as measured using functional magnetic resonance imaging (fMRI), are stimulus-specific. Accumulation signals were defined as a change in the slope of the rising edge of activation corresponding with response time (RT), with higher slopes associated with faster RTs. Consistent with an accumulation account, fMRI activity in face- and house-selective regions in the inferior temporal cortex increased at a rate proportional to decision time in favor of the preferred stimulus. This finding indicates that stimulus-specific regions perform an evidence integrative function during goal-directed behavior and that different sources of evidence accumulate separately. We also assessed the decision-related function of other regions throughout the brain and found that several regions were consistent with classifications from prior work, suggesting a degree of domain generality in decision processing. Taken together, these results provide support for an integration-to-boundary decision mechanism and highlight possible roles of both domain-specific and domain-general regions in decision evidence evaluation. PMID:25562821
Modeling the Spatial Dynamics of International Tuna Fleets
2016-01-01
We developed an iterative sequential random utility model to investigate the social and environmental determinants of the spatiotemporal decision process of tuna purse-seine fishery fishing effort in the eastern Pacific Ocean. Operations of the fishing gear mark checkpoints in a continuous complex decision-making process. Individual fisher behavior is modeled by identifying diversified choices over decision-space for an entire fishing trip, which allows inclusion of prior and current vessel locations and conditions among the explanatory variables. Among these factors are vessel capacity; departure and arrival port; duration of the fishing trip; daily and cumulative distance travelled, which provides a proxy for operation costs; expected revenue; oceanographic conditions; and tons of fish on board. The model uses a two-step decision process to capture the probability of a vessel choosing a specific fishing region for the first set and the probability of switching to (or staying in) a specific region to fish before returning to its landing port. The model provides a means to anticipate the success of marine resource management, and it can be used to evaluate fleet diversity in fisher behavior, the impact of climate variability, and the stability and resilience of complex coupled human and natural systems. PMID:27537545
Coercive and legitimate authority impact tax honesty: evidence from behavioral and ERP experiments
Pfabigan, Daniela M.; Lamm, Claus; Kirchler, Erich; Hofmann, Eva
2017-01-01
Abstract Cooperation in social systems such as tax honesty is of central importance in our modern societies. However, we know little about cognitive and neural processes driving decisions to evade or pay taxes. This study focuses on the impact of perceived tax authority and examines the mental chronometry mirrored in ERP data allowing a deeper understanding about why humans cooperate in tax systems. We experimentally manipulated coercive and legitimate authority and studied its impact on cooperation and underlying cognitive (experiment 1, 2) and neuronal (experiment 2) processes. Experiment 1 showed that in a condition of coercive authority, tax payments are lower, decisions are faster and participants report more rational reasoning and enforced compliance, however, less voluntary cooperation than in a condition of legitimate authority. Experiment 2 confirmed most results, but did not find a difference in payments or self-reported rational reasoning. Moreover, legitimate authority led to heightened cognitive control (expressed by increased MFN amplitudes) and disrupted attention processing (expressed by decreased P300 amplitudes) compared to coercive authority. To conclude, the neuronal data surprisingly revealed that legitimate authority may led to higher decision conflict and thus to higher cognitive demands in tax decisions than coercive authority. PMID:28402477
The design of patient decision support interventions: addressing the theory-practice gap.
Elwyn, Glyn; Stiel, Mareike; Durand, Marie-Anne; Boivin, Jacky
2011-08-01
Although an increasing number of decision support interventions for patients (including decision aids) are produced, few make explicit use of theory. We argue the importance of using theory to guide design. The aim of this work was to address this theory-practice gap and to examine how a range of selected decision-making theories could inform the design and evaluation of decision support interventions. We reviewed the decision-making literature and selected relevant theories. We assessed their key principles, theoretical pathways and predictions in order to determine how they could inform the design of two core components of decision support interventions, namely, information and deliberation components and to specify theory-based outcome measures. Eight theories were selected: (1) the expected utility theory; (2) the conflict model of decision making; (3) prospect theory; (4) fuzzy-trace theory; (5) the differentiation and consolidation theory; (6) the ecological rationality theory; (7) the rational-emotional model of decision avoidance; and finally, (8) the Attend, React, Explain, Adapt model of affective forecasting. Some theories have strong relevance to the information design (e.g. prospect theory); some are more relevant to deliberation processes (conflict theory, differentiation theory and ecological validity). None of the theories in isolation was sufficient to inform the design of all the necessary components of decision support interventions. It was also clear that most work in theory-building has focused on explaining or describing how humans think rather than on how tools could be designed to help humans make good decisions. It is not surprising therefore that a large theory-practice gap exists as we consider decision support for patients. There was no relevant theory that integrated all the necessary contributions to the task of making good decisions in collaborative interactions. Initiatives such as the International Patient Decision Aids Standards Collaboration influence standards for the design of decision support interventions. However, this analysis points to the need to undertake more work in providing theoretical foundations for these interventions. © 2010 Blackwell Publishing Ltd.
NASA Astrophysics Data System (ADS)
Yaeger, Mary A.; Housh, Mashor; Cai, Ximing; Sivapalan, Murugesu
2014-12-01
To better address the dynamic interactions between human and hydrologic systems, we develop an integrated modeling framework that employs a System of Systems optimization model to emulate human development decisions which are then incorporated into a watershed model to estimate the resulting hydrologic impacts. The two models are run interactively to simulate the coevolution of coupled human-nature systems, such that reciprocal feedbacks between hydrologic processes and human decisions (i.e., human impacts on critical low flows and hydrologic impacts on human decisions on land and water use) can be assessed. The framework is applied to a Midwestern U.S. agricultural watershed, in the context of proposed biofuels development. This operation is illustrated by projecting three possible future coevolution trajectories, two of which use dedicated biofuel crops to reduce annual watershed nitrate export while meeting ethanol production targets. Imposition of a primary external driver (biofuel mandate) combined with different secondary drivers (water quality targets) results in highly nonlinear and multiscale responses of both the human and hydrologic systems, including multiple tradeoffs, impacting the future coevolution of the system in complex, heterogeneous ways. The strength of the hydrologic response is sensitive to the magnitude of the secondary driver; 45% nitrate reduction target leads to noticeable impacts at the outlet, while a 30% reduction leads to noticeable impacts that are mainly local. The local responses are conditioned by previous human-hydrologic modifications and their spatial relationship to the new biofuel development, highlighting the importance of past coevolutionary history in predicting future trajectories of change.
Nihonsugi, Tsuyoshi; Ihara, Aya; Haruno, Masahiko
2015-02-25
The intention behind another's action and the impact of the outcome are major determinants of human economic behavior. It is poorly understood, however, whether the two systems share a core neural computation. Here, we investigated whether the two systems are causally dissociable in the brain by integrating computational modeling, functional magnetic resonance imaging, and transcranial direct current stimulation experiments in a newly developed trust game task. We show not only that right dorsolateral prefrontal cortex (DLPFC) activity is correlated with intention-based economic decisions and that ventral striatum and amygdala activity are correlated with outcome-based decisions, but also that stimulation to the DLPFC selectively enhances intention-based decisions. These findings suggest that the right DLPFC is involved in the implementation of intention-based decisions in the processing of cooperative decisions. This causal dissociation of cortical and subcortical backgrounds may indicate evolutionary and developmental differences in the two decision systems. Copyright © 2015 the authors 0270-6474/15/53412-08$15.00/0.
User-centered design and the development of patient decision aids: protocol for a systematic review.
Witteman, Holly O; Dansokho, Selma Chipenda; Colquhoun, Heather; Coulter, Angela; Dugas, Michèle; Fagerlin, Angela; Giguere, Anik Mc; Glouberman, Sholom; Haslett, Lynne; Hoffman, Aubri; Ivers, Noah; Légaré, France; Légaré, Jean; Levin, Carrie; Lopez, Karli; Montori, Victor M; Provencher, Thierry; Renaud, Jean-Sébastien; Sparling, Kerri; Stacey, Dawn; Vaisson, Gratianne; Volk, Robert J; Witteman, William
2015-01-26
Providing patient-centered care requires that patients partner in their personal health-care decisions to the full extent desired. Patient decision aids facilitate processes of shared decision-making between patients and their clinicians by presenting relevant scientific information in balanced, understandable ways, helping clarify patients' goals, and guiding decision-making processes. Although international standards stipulate that patients and clinicians should be involved in decision aid development, little is known about how such involvement currently occurs, let alone best practices. This systematic review consisting of three interlinked subreviews seeks to describe current practices of user involvement in the development of patient decision aids, compare these to practices of user-centered design, and identify promising strategies. A research team that includes patient and clinician representatives, decision aid developers, and systematic review method experts will guide this review according to the Cochrane Handbook and PRISMA reporting guidelines. A medical librarian will hand search key references and use a peer-reviewed search strategy to search MEDLINE, EMBASE, PubMed, Web of Science, the Cochrane Library, the ACM library, IEEE Xplore, and Google Scholar. We will identify articles across all languages and years describing the development or evaluation of a patient decision aid, or the application of user-centered design or human-centered design to tools intended for patient use. Two independent reviewers will assess article eligibility and extract data into a matrix using a structured pilot-tested form based on a conceptual framework of user-centered design. We will synthesize evidence to describe how research teams have included users in their development process and compare these practices to user-centered design methods. If data permit, we will develop a measure of the user-centeredness of development processes and identify practices that are likely to be optimal. This systematic review will provide evidence of current practices to inform approaches for involving patients and other stakeholders in the development of patient decision aids. We anticipate that the results will help move towards the establishment of best practices for the development of patient-centered tools and, in turn, help improve the experiences of people who face difficult health decisions. PROSPERO CRD42014013241.
An fMRI-Based Neural Signature of Decisions to Smoke Cannabis.
Bedi, Gillinder; Lindquist, Martin A; Haney, Margaret
2015-11-01
Drug dependence may be at its core a pathology of choice, defined by continued decisions to use drugs irrespective of negative consequences. Despite evidence of dysregulated decision making in addiction, little is known about the neural processes underlying the most clinically relevant decisions drug users make: decisions to use drugs. Here, we combined functional magnetic resonance imaging (fMRI), machine learning, and human laboratory drug administration to investigate neural activation underlying decisions to smoke cannabis. Nontreatment-seeking daily cannabis smokers completed an fMRI choice task, making repeated decisions to purchase or decline 1-12 placebo or active cannabis 'puffs' ($0.25-$5/puff). One randomly selected decision was implemented. If the selected choice had been bought, the cost was deducted from study earnings and the purchased cannabis smoked in the laboratory; alternatively, the participant remained in the laboratory without cannabis. Machine learning with leave-one-subject-out cross-validation identified distributed neural activation patterns discriminating decisions to buy cannabis from declined offers. A total of 21 participants were included in behavioral analyses; 17 purchased cannabis and were thus included in fMRI analyses. Purchasing varied lawfully with dose and cost. The classifier discriminated with 100% accuracy between fMRI activation patterns for purchased vs declined cannabis at the level of the individual. Dorsal striatum, insula, posterior parietal regions, anterior and posterior cingulate, and dorsolateral prefrontal cortex all contributed reliably to this neural signature of decisions to smoke cannabis. These findings provide the basis for a brain-based characterization of drug-related decision making in drug abuse, including effects of psychological and pharmacological interventions on these processes.
NASA Astrophysics Data System (ADS)
Kase, Sue E.; Vanni, Michelle; Caylor, Justine; Hoye, Jeff
2017-05-01
The Human-Assisted Machine Information Exploitation (HAMIE) investigation utilizes large-scale online data collection for developing models of information-based problem solving (IBPS) behavior in a simulated time-critical operational environment. These types of environments are characteristic of intelligence workflow processes conducted during human-geo-political unrest situations when the ability to make the best decision at the right time ensures strategic overmatch. The project takes a systems approach to Human Information Interaction (HII) by harnessing the expertise of crowds to model the interaction of the information consumer and the information required to solve a problem at different levels of system restrictiveness and decisional guidance. The design variables derived from Decision Support Systems (DSS) research represent the experimental conditions in this online single-player against-the-clock game where the player, acting in the role of an intelligence analyst, is tasked with a Commander's Critical Information Requirement (CCIR) in an information overload scenario. The player performs a sequence of three information processing tasks (annotation, relation identification, and link diagram formation) with the assistance of `HAMIE the robot' who offers varying levels of information understanding dependent on question complexity. We provide preliminary results from a pilot study conducted with Amazon Mechanical Turk (AMT) participants on the Volunteer Science scientific research platform.
Integrating human health and ecological concerns in risk assessments.
Cirone, P A; Bruce Duncan, P
2000-11-03
The interconnections between ecosystems, human health and welfare have been increasingly recognized by the US government, academia, and the public. This paper continues this theme by addressing the use of risk assessment to integrate people into a single assessment. In a broad overview of the risk assessment process we stress the need to build a conceptual model of the whole system including multiple species (humans and other ecological entities), stressors, and cumulative effects. We also propose converging landscape ecology and evaluation of ecosystem services with risk assessment to address these cumulative responses. We first look at how this integration can occur within the problem formulation step in risk assessment where the system is defined, a conceptual model created, a subset of components and functions selected, and the analytical framework decided in a context that includes the management decisions. A variety of examples of problem formulations (salmon, wild insects, hyporheic ecosystems, ultraviolet (UV) radiation, nitrogen fertilization, toxic chemicals, and oil spills) are presented to illustrate how treating humans as components of the landscape can add value to risk assessments. We conclude that the risk assessment process should help address the urgent needs of society in proportion to importance, to provide a format to communicate knowledge and understanding, and to inform policy and management decisions.
Integrated Environmental Modelling: Human decisions, human challenges
Glynn, Pierre D.
2015-01-01
Integrated Environmental Modelling (IEM) is an invaluable tool for understanding the complex, dynamic ecosystems that house our natural resources and control our environments. Human behaviour affects the ways in which the science of IEM is assembled and used for meaningful societal applications. In particular, human biases and heuristics reflect adaptation and experiential learning to issues with frequent, sharply distinguished, feedbacks. Unfortunately, human behaviour is not adapted to the more diffusely experienced problems that IEM typically seeks to address. Twelve biases are identified that affect IEM (and science in general). These biases are supported by personal observations and by the findings of behavioural scientists. A process for critical analysis is proposed that addresses some human challenges of IEM and solicits explicit description of (1) represented processes and information, (2) unrepresented processes and information, and (3) accounting for, and cognizance of, potential human biases. Several other suggestions are also made that generally complement maintaining attitudes of watchful humility, open-mindedness, honesty and transparent accountability. These suggestions include (1) creating a new area of study in the behavioural biogeosciences, (2) using structured processes for engaging the modelling and stakeholder communities in IEM, and (3) using ‘red teams’ to increase resilience of IEM constructs and use.
Decision processes in choice overload: a product of delay and probability discounting?
Kaplan, Brent A; Reed, Derek D
2013-07-01
Recent research in the behavioral decision making literature has demonstrated that humans hyperbolically discount the subjective value of options as the number of options increases (Reed et al., 2012). These findings provide a cognitive-behavioral synthesis of the "choice overload" phenomenon, also known as the "paradox of choice." Specifically, these findings suggest that temporal discounting may serve as the underlying process contributing to this effect. As an extension, this study examined the effects of reward magnitude sizes had on rates temporal and options discounting. This manipulation was conducted to determine what role temporal discounting plays in discounting of options. The present results suggest that temporal discounting may not be the only process contributing to the choice overload effect. Copyright © 2013 Elsevier B.V. All rights reserved.
A Sensemaking Perspective on Situation Awareness in Power Grid Operations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Greitzer, Frank L.; Schur, Anne; Paget, Mia L.
2008-07-21
With increasing complexity and interconnectivity of the electric power grid, the scope and complexity of grid operations continues to grow. New paradigms are needed to guide research to improve operations by enhancing situation awareness of operators. Research on human factors/situation awareness is described within a taxonomy of tools and approaches that address different levels of cognitive processing. While user interface features and visualization approaches represent the predominant focus of human factors studies of situation awareness, this paper argues that a complementary level, sensemaking, deserves further consideration by designers of decision support systems for power grid operations. A sensemaking perspective onmore » situation aware-ness may reveal new insights that complement ongoing human factors research, where the focus of the investigation of errors is to understand why the decision makers experienced the situation the way they did, or why what they saw made sense to them at the time.« less
Hough transform for human action recognition
NASA Astrophysics Data System (ADS)
Siemon, Mia S. N.
2016-09-01
Nowadays, the demand of computer analysis, especially regarding team sports, continues drastically growing. More and more decisions are made by electronic devices for the live to become `easier' to a certain context. There already exist application areas in sports, during which critical situations are being handled by means of digital software. This paper aims at the evaluation and introduction to the necessary foundation which would make it possible to develop a concept similar to that of `hawk-eye', a decision-making program to evaluate the impact of a ball with respect to a target line and to apply it to the sport of volleyball. The pattern recognition process is in this case performed by means of the mathematical model of Hough transform which is able of identifying relevant lines and circles in the image in order to later on use them for the necessary evaluation of the image and the decision-making process.
Salience driven value integration explains decision biases and preference reversal
Tsetsos, Konstantinos; Chater, Nick; Usher, Marius
2012-01-01
Human choice behavior exhibits many paradoxical and challenging patterns. Traditional explanations focus on how values are represented, but little is known about how values are integrated. Here we outline a psychophysical task for value integration that can be used as a window on high-level, multiattribute decisions. Participants choose between alternative rapidly presented streams of numerical values. By controlling the temporal distribution of the values, we demonstrate that this process underlies many puzzling choice paradoxes, such as temporal, risk, and framing biases, as well as preference reversals. These phenomena can be explained by a simple mechanism based on the integration of values, weighted by their salience. The salience of a sampled value depends on its temporal order and momentary rank in the decision context, whereas the direction of the weighting is determined by the task framing. We show that many known choice anomalies may arise from the microstructure of the value integration process. PMID:22635271
Malik, Aisha Y.
2011-01-01
Background: International guidelines for medical research involving human subjects maintain the primacy of informed consent while recognizing cultural diversity. Methods: This article draws on empirical data obtained from interviews with physician-researchers in teaching hospitals of Lahore, Pakistan, to identify social and cultural factors that affect the consent process for participants in research. Results: This article presents variable findings with regards to communication, comprehension, and decision making. While some physicians consider that social factors such as lack of education, a patriarchal family system, and skepticism about research can make patients dependent on either the physician-researcher or the family, others believe that patients do make independent decisions. Conclusions: In light of the findings, the article ends with a recommendation for communication and decision making that is sensitive to the local sociocultural environment while at the same time meeting the ethical imperative of respect for persons. PMID:22816063
Malik, Aisha Y
2011-07-01
Background: International guidelines for medical research involving human subjects maintain the primacy of informed consent while recognizing cultural diversity. Methods: This article draws on empirical data obtained from interviews with physician-researchers in teaching hospitals of Lahore, Pakistan, to identify social and cultural factors that affect the consent process for participants in research. Results: This article presents variable findings with regards to communication, comprehension, and decision making. While some physicians consider that social factors such as lack of education, a patriarchal family system, and skepticism about research can make patients dependent on either the physician-researcher or the family, others believe that patients do make independent decisions. Conclusions: In light of the findings, the article ends with a recommendation for communication and decision making that is sensitive to the local sociocultural environment while at the same time meeting the ethical imperative of respect for persons.
Implementation Issues for Departure Planning Systems
NASA Technical Reports Server (NTRS)
Hansman, R. John; Feron, Eric; Clarke, John-Paul; Odoni, Amedeo
1999-01-01
The objective of the proposed effort is to investigate issues associated with the design and implementation of decision aiding tools to assist in improving the departure process at congested airports. This effort follows a preliminary investigation of potential Departure Planning approaches and strategies, which identified potential benefits in departure efficiency, and also in reducing the environmental impact of aircraft in the departure queue. The preliminary study bas based, in large part, on observations and analysis of departure processes at Boston, Logan airport. The objective of this follow-on effort is to address key implementation issues and to expand the observational base to include airports with different constraints and traffic demand. Specifically, the objectives of this research are to: (1) Expand the observational base to include airports with different underlying operational dynamics. (2) Develop prototype decision aiding algorithms/approaches and assess potential benefits. and (3) Investigate Human Machine Integration (HMI) issues associated with decision aids in tower environments.
Salamone, John D; Yohn, Samantha E; López-Cruz, Laura; San Miguel, Noemí; Correa, Mercè
2016-05-01
Motivation has been defined as the process that allows organisms to regulate their internal and external environment, and control the probability, proximity and availability of stimuli. As such, motivation is a complex process that is critical for survival, which involves multiple behavioural functions mediated by a number of interacting neural circuits. Classical theories of motivation suggest that there are both directional and activational aspects of motivation, and activational aspects (i.e. speed and vigour of both the instigation and persistence of behaviour) are critical for enabling organisms to overcome work-related obstacles or constraints that separate them from significant stimuli. The present review discusses the role of brain dopamine and related circuits in behavioural activation, exertion of effort in instrumental behaviour, and effort-related decision-making, based upon both animal and human studies. Impairments in behavioural activation and effort-related aspects of motivation are associated with psychiatric symptoms such as anergia, fatigue, lassitude and psychomotor retardation, which cross multiple pathologies, including depression, schizophrenia, and Parkinson's disease. Therefore, this review also attempts to provide an interdisciplinary approach that integrates findings from basic behavioural neuroscience, behavioural economics, clinical neuropsychology, psychiatry, and neurology, to provide a coherent framework for future research and theory in this critical field. Although dopamine systems are a critical part of the brain circuitry regulating behavioural activation, exertion of effort, and effort-related decision-making, mesolimbic dopamine is only one part of a distributed circuitry that includes multiple neurotransmitters and brain areas. Overall, there is a striking similarity between the brain areas involved in behavioural activation and effort-related processes in rodents and in humans. Animal models of effort-related decision-making are highly translatable to humans, and an emerging body of evidence indicates that alterations in effort-based decision-making are evident in several psychiatric and neurological disorders. People with major depression, schizophrenia, and Parkinson's disease show evidence of decision-making biases towards a lower exertion of effort. Translational studies linking research with animal models, human volunteers, and clinical populations are greatly expanding our knowledge about the neural basis of effort-related motivational dysfunction, and it is hoped that this research will ultimately lead to improved treatment for motivational and psychomotor symptoms in psychiatry and neurology. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Ruibal, Alba
2014-11-01
In 2006, the Constitutional Court of Colombia issued Decision C-355/2006, which liberalized the country's abortion law. The reform was groundbreaking in its argumentation, being one of the first judicial decisions in the world to uphold abortion rights on equality grounds, and the first by a constitutional court to rule on the constitutionality of abortion within a human rights framework. It was also the first of a series of reforms that would liberalize the abortion regulation in four other Latin American countries. The Colombian case is also notable for the process of strategic litigation carried out by feminist organizations after the Court's decision, in order to ensure its implementation and counter the opposition from conservative actors working in State institutions, as well as for the active role played by the Court in that process. Based on fieldwork carried out in Colombia in 2013, this article analyzes the process of progressive implementation and reactionary backlash after Decision C-355/2006, with an emphasis on strategic litigation by the feminist movement and subsequent decisions by the Constitutional Court, which consolidated its jurisprudence in the field of abortion rights. It highlights the role of both feminists and of conservative activists within State institutions as opposing social movements, and the dynamics of political and legal mobilization and counter-mobilization in that process. Copyright © 2014 Reproductive Health Matters. Published by Elsevier Ltd. All rights reserved.
Hsu, Chun-Wei; Goh, Joshua O. S.
2016-01-01
When comparing between the values of different choices, human beings can rely on either more cognitive processes, such as using mathematical computation, or more affective processes, such as using emotion. However, the neural correlates of how these two types of processes operate during value-based decision-making remain unclear. In this study, we investigated the extent to which neural regions engaged during value-based decision-making overlap with those engaged during mathematical and emotional processing in a within-subject manner. In a functional magnetic resonance imaging experiment, participants viewed stimuli that always consisted of numbers and emotional faces that depicted two choices. Across tasks, participants decided between the two choices based on the expected value of the numbers, a mathematical result of the numbers, or the emotional face stimuli. We found that all three tasks commonly involved various cortical areas including frontal, parietal, motor, somatosensory, and visual regions. Critically, the mathematical task shared common areas with the value but not emotion task in bilateral striatum. Although the emotion task overlapped with the value task in parietal, motor, and sensory areas, the mathematical task also evoked responses in other areas within these same cortical structures. Minimal areas were uniquely engaged for the value task apart from the other two tasks. The emotion task elicited a more expansive area of neural activity whereas value and mathematical task responses were in more focal regions. Whole-brain spatial correlation analysis showed that valuative processing engaged functional brain responses more similarly to mathematical processing than emotional processing. While decisions on expected value entail both mathematical and emotional processing regions, mathematical processes have a more prominent contribution particularly in subcortical processes. PMID:27375466
Hsu, Chun-Wei; Goh, Joshua O S
2016-01-01
When comparing between the values of different choices, human beings can rely on either more cognitive processes, such as using mathematical computation, or more affective processes, such as using emotion. However, the neural correlates of how these two types of processes operate during value-based decision-making remain unclear. In this study, we investigated the extent to which neural regions engaged during value-based decision-making overlap with those engaged during mathematical and emotional processing in a within-subject manner. In a functional magnetic resonance imaging experiment, participants viewed stimuli that always consisted of numbers and emotional faces that depicted two choices. Across tasks, participants decided between the two choices based on the expected value of the numbers, a mathematical result of the numbers, or the emotional face stimuli. We found that all three tasks commonly involved various cortical areas including frontal, parietal, motor, somatosensory, and visual regions. Critically, the mathematical task shared common areas with the value but not emotion task in bilateral striatum. Although the emotion task overlapped with the value task in parietal, motor, and sensory areas, the mathematical task also evoked responses in other areas within these same cortical structures. Minimal areas were uniquely engaged for the value task apart from the other two tasks. The emotion task elicited a more expansive area of neural activity whereas value and mathematical task responses were in more focal regions. Whole-brain spatial correlation analysis showed that valuative processing engaged functional brain responses more similarly to mathematical processing than emotional processing. While decisions on expected value entail both mathematical and emotional processing regions, mathematical processes have a more prominent contribution particularly in subcortical processes.
ERIC Educational Resources Information Center
Dzwik, Leigh Settlemoir
2017-01-01
The purpose of this study was to assess faculty unionization's impact on academic human resource decision making for department chairs. The academic human resource decisions included in the study were: academic hiring; re-employment, promotion and tenure; other faculty evaluation decisions; and discipline and discharge. The first purpose of this…
Fujiwara, Esther; Tomlinson, Sara E; Purdon, Scot E; Gill, M John; Power, Christopher
2015-01-01
Human immunodeficiency virus (HIV) can affect the frontal-striatal brain regions, which are known to subserve decision-making functions. Previous studies have reported impaired decision making among HIV+ individuals using the Iowa Gambling Task, a task that assesses decision making under ambiguity. Previous study populations often had significant comorbidities such as past or present substance use disorders and/or hepatitis C virus coinfection, complicating conclusions about the unique contributions of HIV-infection to decision making. Decision making under explicit risk has very rarely been examined in HIV+ individuals and was tested here using the Game of Dice Task (GDT). We examined decision making under explicit risk in the GDT in 20 HIV+ individuals without substance use disorder or HCV coinfection, including a demographically matched healthy control group (n = 20). Groups were characterized on a standard neuropsychological test battery. For the HIV+ group, several disease-related parameters (viral load, current and nadir CD4 T-cell count) were included. Analyses focused on the GDT and spanned between-group (t-tests; analysis of covariance, ANCOVA) as well as within-group comparisons (Pearson/Spearman correlations). HIV+ individuals were impaired in the GDT, compared to healthy controls (p = .02). Their decision-making impairments were characterized by less advantageous choices and more random choice strategies, especially towards the end of the task. Deficits in the GDT in the HIV+ group were related to executive dysfunctions, slowed processing/motor speed, and current immune system status (CD4+ T-cell levels, ps < .05). Decision making under explicit risk in the GDT can occur in HIV-infected individuals without comorbidities. The correlational patterns may point to underlying fronto-subcortical dysfunctions in HIV+ individuals. The GDT provides a useful measure to assess risky decision making in this population and should be tested in larger studies.
Proteomics for Adverse Outcome Pathway Discovery using Human Kidney Cells?
An Adverse Outcome Pathway (AOP) is a conceptual framework that applies molecular-based data for use in risk assessment and regulatory decision support. AOP development is based on effects data of chemicals on biological processes (i.e., molecular initiating events, key intermedi...
Corporate Funding of Human Services Agencies.
ERIC Educational Resources Information Center
Zippay, Allison
1992-01-01
Conducted case study of philanthropic giving among 29 companies in Cambridge, Massachusetts. Found that most corporations used informal rather than formal process for making funding decisions, with many firms relying on tradition, social contacts, and intuition to guide allocations. Findings suggest ways that social services administrators can…
78 FR 25436 - SFIREG Environmental Quality Issues Committee; Notice of Public Meeting
Federal Register 2010, 2011, 2012, 2013, 2014
2013-05-01
... human health, environmental exposure to pesticides, and insight into EPA's decision-making process. You.... SUMMARY: The Association of American Pesticide Control Officials (AAPCO)/State FIFRA Issues Research and... External Affairs Division (7506P), Office of Pesticide Programs, Environmental Protection Agency, 1200...
Understanding Meta-Decisions: The Key To Effecting Organizational Change. Introduction
ERIC Educational Resources Information Center
Billings, Charles R.
1974-01-01
Discusses the need for individuals to become aware of the decisionmaking process of institutions that directly affect them. Past attempts to effect change within organizational systems are reviewed in terms of the traditional human relations approach and of a systems approach. (Author/WM)
The neural substrates of social influence on decision making.
Tomlin, Damon; Nedic, Andrea; Prentice, Deborah A; Holmes, Philip; Cohen, Jonathan D
2013-01-01
The mechanisms that govern human learning and decision making under uncertainty have been the focus of intense behavioral and, more recently, neuroscientific investigation. Substantial progress has been made in building models of the processes involved, and identifying underlying neural mechanisms using simple, two-alternative forced choice decision tasks. However, less attention has been given to how social information influences these processes, and the neural systems that mediate this influence. Here we sought to address these questions by using tasks similar to ones that have been used to study individual decision making behavior, and adding conditions in which participants were given trial-by-trial information about the performance of other individuals (their choices and/or their rewards) simultaneously playing the same tasks. We asked two questions: How does such information about the behavior of others influence performance in otherwise simple decision tasks, and what neural systems mediate this influence? We found that bilateral insula exhibited a parametric relationship to the degree of misalignment of the individual's performance with those of others in the group. Furthermore, activity in the bilateral insula significantly predicted participants' subsequent choices to align their behavior with others in the group when they were misaligned either in their choices (independent of success) or their degree of success (independent of specific choices). These findings add to the growing body of empirical data suggesting that the insula participates in an important way in social information processing and decision making.
Superior pattern processing is the essence of the evolved human brain
Mattson, Mark P.
2014-01-01
Humans have long pondered the nature of their mind/brain and, particularly why its capacities for reasoning, communication and abstract thought are far superior to other species, including closely related anthropoids. This article considers superior pattern processing (SPP) as the fundamental basis of most, if not all, unique features of the human brain including intelligence, language, imagination, invention, and the belief in imaginary entities such as ghosts and gods. SPP involves the electrochemical, neuronal network-based, encoding, integration, and transfer to other individuals of perceived or mentally-fabricated patterns. During human evolution, pattern processing capabilities became increasingly sophisticated as the result of expansion of the cerebral cortex, particularly the prefrontal cortex and regions involved in processing of images. Specific patterns, real or imagined, are reinforced by emotional experiences, indoctrination and even psychedelic drugs. Impaired or dysregulated SPP is fundamental to cognitive and psychiatric disorders. A broader understanding of SPP mechanisms, and their roles in normal and abnormal function of the human brain, may enable the development of interventions that reduce irrational decisions and destructive behaviors. PMID:25202234
NASA Astrophysics Data System (ADS)
Jakeman, A. J.; Guillaume, J. H. A.; El Sawah, S.; Hamilton, S.
2014-12-01
Integrated modelling and assessment (IMA) is best regarded as a process that can support environmental decision-making when issues are strongly contested and uncertainties pervasive. To be most useful, the process must be multi-dimensional and phased. Principally, it must be tailored to the problem context to encompass diverse issues of concern, management settings and stakeholders. This in turn requires the integration of multiple processes and components of natural and human systems and their corresponding spatial and temporal scales. Modellers therefore need to be able to integrate multiple disciplines, methods, models, tools and data, and many sources and types of uncertainty. These dimensions are incorporated into iteration between the various phases of the IMA process, including scoping, problem framing and formulation, assessing options and communicating findings. Two case studies in Australia are employed to share the lessons of how integration can be achieved in these IMA phases using a mix of stakeholder participation processes and modelling tools. One case study aims to improve the relevance of modelling by incorporating stakeholder's views of irrigated viticulture and water management decision making. It used a novel methodology with the acronym ICTAM, consisting of Interviews to elicit mental models, Cognitive maps to represent and analyse individual and group mental models, Time-sequence diagrams to chronologically structure the decision making process, an All-encompassing conceptual model, and computational Models of stakeholder decision making. The second case uses a hydro-economic river network model to examine basin-wide impacts of water allocation cuts and adoption of farm innovations. The knowledge exchange approach used in each case was designed to integrate data and knowledge bearing in mind the contextual dimensions of the problem at hand, and the specific contributions that environmental modelling was thought to be able to make.
Decision Making In A High-Tech World: Automation Bias and Countermeasures
NASA Technical Reports Server (NTRS)
Mosier, Kathleen L.; Skitka, Linda J.; Burdick, Mark R.; Heers, Susan T.; Rosekind, Mark R. (Technical Monitor)
1996-01-01
Automated decision aids and decision support systems have become essential tools in many high-tech environments. In aviation, for example, flight management systems computers not only fly the aircraft, but also calculate fuel efficient paths, detect and diagnose system malfunctions and abnormalities, and recommend or carry out decisions. Air Traffic Controllers will soon be utilizing decision support tools to help them predict and detect potential conflicts and to generate clearances. Other fields as disparate as nuclear power plants and medical diagnostics are similarly becoming more and more automated. Ideally, the combination of human decision maker and automated decision aid should result in a high-performing team, maximizing the advantages of additional cognitive and observational power in the decision-making process. In reality, however, the presence of these aids often short-circuits the way that even very experienced decision makers have traditionally handled tasks and made decisions, and introduces opportunities for new decision heuristics and biases. Results of recent research investigating the use of automated aids have indicated the presence of automation bias, that is, errors made when decision makers rely on automated cues as a heuristic replacement for vigilant information seeking and processing. Automation commission errors, i.e., errors made when decision makers inappropriately follow an automated directive, or automation omission errors, i.e., errors made when humans fail to take action or notice a problem because an automated aid fails to inform them, can result from this tendency. Evidence of the tendency to make automation-related omission and commission errors has been found in pilot self reports, in studies using pilots in flight simulations, and in non-flight decision making contexts with student samples. Considerable research has found that increasing social accountability can successfully ameliorate a broad array of cognitive biases and resultant errors. To what extent these effects generalize to performance situations is not yet empirically established. The two studies to be presented represent concurrent efforts, with student and professional pilot samples, to determine the effects of accountability pressures on automation bias and on the verification of the accurate functioning of automated aids. Students (Experiment 1) and commercial pilots (Experiment 2) performed simulated flight tasks using automated aids. In both studies, participants who perceived themselves as accountable for their strategies of interaction with the automation were significantly more likely to verify its correctness, and committed significantly fewer automation-related errors than those who did not report this perception.
A control-theory model for human decision-making
NASA Technical Reports Server (NTRS)
Levison, W. H.; Tanner, R. B.
1971-01-01
A model for human decision making is an adaptation of an optimal control model for pilot/vehicle systems. The models for decision and control both contain concepts of time delay, observation noise, optimal prediction, and optimal estimation. The decision making model was intended for situations in which the human bases his decision on his estimate of the state of a linear plant. Experiments are described for the following task situations: (a) single decision tasks, (b) two-decision tasks, and (c) simultaneous manual control and decision making. Using fixed values for model parameters, single-task and two-task decision performance can be predicted to within an accuracy of 10 percent. Agreement is less good for the simultaneous decision and control situation.
Human Information Processing Guidelines for Decision-Aiding Displays.
1981-12-01
recall when they are used together. Also, context plays an important part in verifying the truth or falsity of sentences . For example, "A robin... interferes with the processing and storing of * additional items (Loftus, 1979). However, rehearsal, by recycling the number of items in STM, allows...remembered better than the middle letters in the series. It was hypothesized that encoding the name of the
The Israeli Patient's Rights Law: evidence for deprofessionalization?
Anson, O
1999-01-01
In this paper, the Israeli Patient's Rights Law of 1996 is discussed within the framework of Haug's predicted process of deprofessionalization. It is argued that the law reflects global processes such as the diffusion of knowledge, consumerism, and values that emphasize human rights and democracy. By guaranteeing patients' access to medical information, by submitting medical decisions to extra-professional regulation, the law erodes professional power.
Cortical Components of Reaction-Time during Perceptual Decisions in Humans.
Dmochowski, Jacek P; Norcia, Anthony M
2015-01-01
The mechanisms of perceptual decision-making are frequently studied through measurements of reaction time (RT). Classical sequential-sampling models (SSMs) of decision-making posit RT as the sum of non-overlapping sensory, evidence accumulation, and motor delays. In contrast, recent empirical evidence hints at a continuous-flow paradigm in which multiple motor plans evolve concurrently with the accumulation of sensory evidence. Here we employ a trial-to-trial reliability-based component analysis of encephalographic data acquired during a random-dot motion task to directly image continuous flow in the human brain. We identify three topographically distinct neural sources whose dynamics exhibit contemporaneous ramping to time-of-response, with the rate and duration of ramping discriminating fast and slow responses. Only one of these sources, a parietal component, exhibits dependence on strength-of-evidence. The remaining two components possess topographies consistent with origins in the motor system, and their covariation with RT overlaps in time with the evidence accumulation process. After fitting the behavioral data to a popular SSM, we find that the model decision variable is more closely matched to the combined activity of the three components than to their individual activity. Our results emphasize the role of motor variability in shaping RT distributions on perceptual decision tasks, suggesting that physiologically plausible computational accounts of perceptual decision-making must model the concurrent nature of evidence accumulation and motor planning.
Autonomous spacecraft landing through human pre-attentive vision.
Schiavone, Giuseppina; Izzo, Dario; Simões, Luís F; de Croon, Guido C H E
2012-06-01
In this work, we exploit a computational model of human pre-attentive vision to guide the descent of a spacecraft on extraterrestrial bodies. Providing the spacecraft with high degrees of autonomy is a challenge for future space missions. Up to present, major effort in this research field has been concentrated in hazard avoidance algorithms and landmark detection, often by reference to a priori maps, ranked by scientists according to specific scientific criteria. Here, we present a bio-inspired approach based on the human ability to quickly select intrinsically salient targets in the visual scene; this ability is fundamental for fast decision-making processes in unpredictable and unknown circumstances. The proposed system integrates a simple model of the spacecraft and optimality principles which guarantee minimum fuel consumption during the landing procedure; detected salient sites are used for retargeting the spacecraft trajectory, under safety and reachability conditions. We compare the decisions taken by the proposed algorithm with that of a number of human subjects tested under the same conditions. Our results show how the developed algorithm is indistinguishable from the human subjects with respect to areas, occurrence and timing of the retargeting.
Higher incentives can impair performance: neural evidence on reinforcement and rationality
Achtziger, Anja; Hügelschäfer, Sabine; Steinhauser, Marco
2015-01-01
Standard economic thinking postulates that increased monetary incentives should increase performance. Human decision makers, however, frequently focus on past performance, a form of reinforcement learning occasionally at odds with rational decision making. We used an incentivized belief-updating task from economics to investigate this conflict through measurements of neural correlates of reward processing. We found that higher incentives fail to improve performance when immediate feedback on decision outcomes is provided. Subsequent analysis of the feedback-related negativity, an early event-related potential following feedback, revealed the mechanism behind this paradoxical effect. As incentives increase, the win/lose feedback becomes more prominent, leading to an increased reliance on reinforcement and more errors. This mechanism is relevant for economic decision making and the debate on performance-based payment. PMID:25816816
Elsawah, Sondoss; Guillaume, Joseph H A; Filatova, Tatiana; Rook, Josefine; Jakeman, Anthony J
2015-03-15
This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders (qualitative) into formal simulation models (quantitative) with the ultimate goal of improving understanding and communication about decision making in complex socio-ecological systems. The methodology integrates cognitive mapping and agent based modelling. It cascades through a sequence of qualitative/soft and numerical methods comprising: (1) Interviews to elicit mental models; (2) Cognitive maps to represent and analyse individual and group mental models; (3) Time-sequence diagrams to chronologically structure the decision making process; (4) All-encompassing conceptual model of decision making, and (5) computational (in this case agent-based) Model. We apply the proposed methodology (labelled ICTAM) in a case study of viticulture irrigation in South Australia. Finally, we use strengths-weakness-opportunities-threats (SWOT) analysis to reflect on the methodology. Results show that the methodology leverages the use of cognitive mapping to capture the richness of decision making and mental models, and provides a combination of divergent and convergent analysis methods leading to the construction of an Agent Based Model. Copyright © 2014 Elsevier Ltd. All rights reserved.
Human perspectives and conservation of grizzly bears in Banff National Park, Canada.
Chamberlain, Emily C; Rutherford, Murray B; Gibeau, Michael L
2012-06-01
Some conservation initiatives provoke intense conflict among stakeholders. The need for action, the nature of the conservation measures, and the effects of these measures on human interests may be disputed. Tools are needed to depolarize such situations, foster understanding of the perspectives of people involved, and find common ground. We used Q methodology to explore stakeholders' perspectives on conservation and management of grizzly bears (Ursus arctos horribilis) in Banff National Park and the Bow River watershed of Alberta, Canada. Twenty-nine stakeholders participated in the study, including local residents, scientists, agency employees, and representatives of nongovernmental conservation organizations and other interest groups. Participants rank ordered a set of statements to express their opinions on the problems of grizzly bear management (I-IV) and a second set of statements on possible solutions to the problems (A-C). Factor analysis revealed that participants held 4 distinct views of the problems: individuals associated with factor I emphasized deficiencies in goals and plans; those associated with factor II believed that problems had been exaggerated; those associated with factor III blamed institutional flaws such as disjointed management and inadequate resources; and individuals associated with factor IV blamed politicized decision making. There were 3 distinct views about the best solutions to the problems: individuals associated with factor A called for increased conservation efforts; those associated with factor B wanted reforms in decision-making processes; and individuals associated with factor C supported active landscape management. We connected people's definitions of the problem with their preferred solutions to form 5 overall problem narratives espoused by groups in the study: the problem is deficient goals and plans, the solution is to prioritize conservation efforts (planning-oriented conservation advocates); the problem is flawed institutions, the solution is to prioritize conservation efforts (institutionally-oriented conservation advocates); the problems have been exaggerated, but there is a need to improve decision-making processes (optimistic decision-process reformers); the problems have been exaggerated, but managers should more actively manage the landscape (optimistic landscape managers); and the problem is politicized decision making, solutions vary (democratizers). Although these 5 groups differed on many issues, they agreed that the population of grizzly bears is vulnerable to extirpation, human use of the area should be designed around ecological constraints, and more inclusive decision-making processes are needed. We used our results to inform a series of workshops in which stakeholders developed and agreed on new management strategies that were implemented by Parks Canada. Our research demonstrates the usefulness of Q method to illuminate people's perspectives and identify common ground in settings where conservation is contested. ©2012 Society for Conservation Biology.