Editorial: Cognitive Architectures, Model Comparison and AGI

NASA Astrophysics Data System (ADS)

Lebiere, Christian; Gonzalez, Cleotilde; Warwick, Walter

2010-12-01

Cognitive Science and Artificial Intelligence share compatible goals of understanding and possibly generating broadly intelligent behavior. In order to determine if progress is made, it is essential to be able to evaluate the behavior of complex computational models, especially those built on general cognitive architectures, and compare it to benchmarks of intelligent behavior such as human performance. Significant methodological challenges arise, however, when trying to extend approaches used to compare model and human performance from tightly controlled laboratory tasks to complex tasks involving more open-ended behavior. This paper describes a model comparison challenge built around a dynamic control task, the Dynamic Stocks and Flows. We present and discuss distinct approaches to evaluating performance and comparing models. Lessons drawn from this challenge are discussed in light of the challenge of using cognitive architectures to achieve Artificial General Intelligence.

Enhancing Tele-robotics with Immersive Virtual Reality

DTIC Science & Technology

2017-11-03

graduate and undergraduate students within the Digital Gaming and Simulation, Computer Science, and psychology programs have actively collaborated...investigates the use of artificial intelligence and visual computing. Numerous fields across the human-computer interaction and gaming research areas...invested in digital gaming and simulation to cognitively stimulate humans by computers, forming a $10.5B industry [1]. On the other hand, cognitive

Proceedings of the International Conference on the Learning Sciences (5th, Evanston, Illinois, August 1991).

ERIC Educational Resources Information Center

Birnbaum, Lawrence, Ed.

This volume contains the papers presented at the fifth International Conference on the Learning Sciences (formerly the International Conference on Artificial Intelligence and Education). As the change in name signifies, a strong effort has been made to open the conference to a broader audience, including educational and cognitive psychologists…

Enhancing the Scientific Process with Artificial Intelligence: Forest Science Applications

Treesearch

Ronald E. McRoberts; Daniel L. Schmoldt; H. Michael Rauscher

1991-01-01

Forestry, as a science, is a process for investigating nature. It consists of repeatedly cycling through a number of steps, including identifying knowledge gaps, creating knowledge to fill them, and organizing, evaluating, and delivering this knowledge. Much of this effort is directed toward creating abstract models of natural phenomena. The cognitive techniques of AI...

The Biological Relevance of Artificial Life: Lessons from Artificial Intelligence

NASA Technical Reports Server (NTRS)

Colombano, Silvano

2000-01-01

There is no fundamental reason why A-life couldn't simply be a branch of computer science that deals with algorithms that are inspired by, or emulate biological phenomena. However, if these are the limits we place on this field, we miss the opportunity to help advance Theoretical Biology and to contribute to a deeper understanding of the nature of life. The history of Artificial Intelligence provides a good example, in that early interest in the nature of cognition quickly was lost to the process of building tools, such as "expert systems" that, were certainly useful, but provided little insight in the nature of cognition. Based on this lesson, I will discuss criteria for increasing the biological relevance of A-life and the probability that this field may provide a theoretical foundation for Biology.

Virtual Reality for Artificial Intelligence: human-centered simulation for social science.

PubMed

Cipresso, Pietro; Riva, Giuseppe

2015-01-01

There is a long last tradition in Artificial Intelligence as use of Robots endowing human peculiarities, from a cognitive and emotional point of view, and not only in shape. Today Artificial Intelligence is more oriented to several form of collective intelligence, also building robot simulators (hardware or software) to deeply understand collective behaviors in human beings and society as a whole. Modeling has also been crucial in the social sciences, to understand how complex systems can arise from simple rules. However, while engineers' simulations can be performed in the physical world using robots, for social scientist this is impossible. For decades, researchers tried to improve simulations by endowing artificial agents with simple and complex rules that emulated human behavior also by using artificial intelligence (AI). To include human beings and their real intelligence within artificial societies is now the big challenge. We present an hybrid (human-artificial) platform where experiments can be performed by simulated artificial worlds in the following manner: 1) agents' behaviors are regulated by the behaviors shown in Virtual Reality involving real human beings exposed to specific situations to simulate, and 2) technology transfers these rules into the artificial world. These form a closed-loop of real behaviors inserted into artificial agents, which can be used to study real society.

Educational Technology: Integration?

ERIC Educational Resources Information Center

Christensen, Dean L.; Tennyson, Robert D.

This paper presents a perspective of the current state of technology-assisted instruction integrating computer language, artificial intelligence (AI), and a review of cognitive science applied to instruction. The following topics are briefly discussed: (1) the language of instructional technology, i.e., programming languages, including authoring…

Conceptual Commitments of the LIDA Model of Cognition

NASA Astrophysics Data System (ADS)

Franklin, Stan; Strain, Steve; McCall, Ryan; Baars, Bernard

2013-06-01

Significant debate on fundamental issues remains in the subfields of cognitive science, including perception, memory, attention, action selection, learning, and others. Psychology, neuroscience, and artificial intelligence each contribute alternative and sometimes conflicting perspectives on the supervening problem of artificial general intelligence (AGI). Current efforts toward a broad-based, systems-level model of minds cannot await theoretical convergence in each of the relevant subfields. Such work therefore requires the formulation of tentative hypotheses, based on current knowledge, that serve to connect cognitive functions into a theoretical framework for the study of the mind. We term such hypotheses "conceptual commitments" and describe the hypotheses underlying one such model, the Learning Intelligent Distribution Agent (LIDA) Model. Our intention is to initiate a discussion among AGI researchers about which conceptual commitments are essential, or particularly useful, toward creating AGI agents.

A conceptual and computational model of moral decision making in human and artificial agents.

PubMed

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.

Intelligent Computer-Assisted Language Learning.

ERIC Educational Resources Information Center

Harrington, Michael

1996-01-01

Introduces the field of intelligent computer assisted language learning (ICALL) and relates them to current practice in computer assisted language learning (CALL) and second language learning. Points out that ICALL applies expertise from artificial intelligence and the computer and cognitive sciences to the development of language learning…

Multi-layer robot skin with embedded sensors and muscles

NASA Astrophysics Data System (ADS)

Tomar, Ankit; Tadesse, Yonas

2016-04-01

Soft artificial skin with embedded sensors and actuators is proposed for a crosscutting study of cognitive science on a facial expressive humanoid platform. This paper focuses on artificial muscles suitable for humanoid robots and prosthetic devices for safe human-robot interactions. Novel composite artificial skin consisting of sensors and twisted polymer actuators is proposed. The artificial skin is conformable to intricate geometries and includes protective layers, sensor layers, and actuation layers. Fluidic channels are included in the elastomeric skin to inject fluids in order to control actuator response time. The skin can be used to develop facially expressive humanoid robots or other soft robots. The humanoid robot can be used by computer scientists and other behavioral science personnel to test various algorithms, and to understand and develop more perfect humanoid robots with facial expression capability. The small-scale humanoid robots can also assist ongoing therapeutic treatment research with autistic children. The multilayer skin can be used for many soft robots enabling them to detect both temperature and pressure, while actuating the entire structure.

Response to Nicholas Allix.

ERIC Educational Resources Information Center

Gardner, Howard; Connell, Michael

2000-01-01

Replies to "The Theory of Multiple Intelligences: A Case of Missing Cognitive Matter," also in this issue. Disagrees about the role theory of knowledge plays in the context of justification of multiple intelligences. Specifically, asserts that the article's criticisms based on philosophy of science claims and work with artificial neural…

"Artificial humans": Psychology and neuroscience perspectives on embodiment and nonverbal communication.

PubMed

Vogeley, Kai; Bente, Gary

2010-01-01

"Artificial humans", so-called "Embodied Conversational Agents" and humanoid robots, are assumed to facilitate human-technology interaction referring to the unique human capacities of interpersonal communication and social information processing. While early research and development in artificial intelligence (AI) focused on processing and production of natural language, the "new AI" has also taken into account the emotional and relational aspects of communication with an emphasis both on understanding and production of nonverbal behavior. This shift in attention in computer science and engineering is reflected in recent developments in psychology and social cognitive neuroscience. This article addresses key challenges which emerge from the goal to equip machines with socio-emotional intelligence and to enable them to interpret subtle nonverbal cues and to respond to social affordances with naturally appearing behavior from both perspectives. In particular, we propose that the creation of credible artificial humans not only defines the ultimate test for our understanding of human communication and social cognition but also provides a unique research tool to improve our knowledge about the underlying psychological processes and neural mechanisms. Copyright © 2010. Published by Elsevier Ltd.

Educational Assessment Using Intelligent Systems. Research Report. ETS RR-08-68

ERIC Educational Resources Information Center

Shute, Valerie J.; Zapata-Rivera, Diego

2008-01-01

Recent advances in educational assessment, cognitive science, and artificial intelligence have made it possible to integrate valid assessment and instruction in the form of modern computer-based intelligent systems. These intelligent systems leverage assessment information that is gathered from various sources (e.g., summative and formative). This…

Computer Assisted Instructional Design for Computer-Based Instruction. Final Report. Working Papers.

ERIC Educational Resources Information Center

Russell, Daniel M.; Pirolli, Peter

Recent advances in artificial intelligence and the cognitive sciences have made it possible to develop successful intelligent computer-aided instructional systems for technical and scientific training. In addition, computer-aided design (CAD) environments that support the rapid development of such computer-based instruction have also been recently…

Incremental Bayesian Category Learning from Natural Language

ERIC Educational Resources Information Center

Frermann, Lea; Lapata, Mirella

2016-01-01

Models of category learning have been extensively studied in cognitive science and primarily tested on perceptual abstractions or artificial stimuli. In this paper, we focus on categories acquired from natural language stimuli, that is, words (e.g., "chair" is a member of the furniture category). We present a Bayesian model that, unlike…

Intelligence: Real or artificial?

PubMed Central

Schlinger, Henry D.

1992-01-01

Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally referred to behavior-environment relations and not to inferred internal structures and processes. It is concluded that if workers in artificial intelligence are to succeed in their general goal, then they must design machines that are adaptive, that is, that can learn. Thus, artificial intelligence researchers must discard their essentialist model of natural intelligence and adopt a selectionist model instead. Such a strategic change should lead them to the science of behavior analysis. PMID:22477051

Inner rehearsal modeling for cognitive robotics

NASA Astrophysics Data System (ADS)

Braun, Jerome J.; Bergen, Karianne; Dasey, Timothy J.

2011-05-01

This paper presents a biomimetic approach involving cognitive process modeling, for use in intelligent robot decisionmaking. The principle of inner rehearsal, a process believed to occur in human and animal cognition, involves internal rehearsing of actions prior to deciding on and executing an overt action, such as a motor action. The inner-rehearsal algorithmic approach we developed is posed and investigated in the context of a relatively complex cognitive task, an under-rubble search and rescue. The paper presents the approach developed, a synthetic environment which was also developed to enable its studies, and the results to date. The work reported here is part of a Cognitive Robotics effort in which we are currently engaged, focused on exploring techniques inspired by cognitive science and neuroscience insights, towards artificial cognition for robotics and autonomous systems.

Earl Busby Hunt (1933-2016).

PubMed

Greenwald, Anthony G

2017-01-01

Presents an obituary for Earl Busby Hunt-known to family, friends, and colleagues as Buz-who died at home in Bellevue, Washington, on April 12, 2016. Buz specialized in artificial intelligence (AI) and had a main focus in cognitive psychology. In fact he was editor of Cognitive Psychology from 1974-1987. Buz's honors include the Lifetime Achievement Award from the International Society for Intelligence Research (2009) and the Cattell Award from the Association for Psychological Science (2011) for lifetime contributions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Embodied artificial agents for understanding human social cognition.

PubMed

Wykowska, Agnieszka; Chaminade, Thierry; Cheng, Gordon

2016-05-05

In this paper, we propose that experimental protocols involving artificial agents, in particular the embodied humanoid robots, provide insightful information regarding social cognitive mechanisms in the human brain. Using artificial agents allows for manipulation and control of various parameters of behaviour, appearance and expressiveness in one of the interaction partners (the artificial agent), and for examining effect of these parameters on the other interaction partner (the human). At the same time, using artificial agents means introducing the presence of artificial, yet human-like, systems into the human social sphere. This allows for testing in a controlled, but ecologically valid, manner human fundamental mechanisms of social cognition both at the behavioural and at the neural level. This paper will review existing literature that reports studies in which artificial embodied agents have been used to study social cognition and will address the question of whether various mechanisms of social cognition (ranging from lower- to higher-order cognitive processes) are evoked by artificial agents to the same extent as by natural agents, humans in particular. Increasing the understanding of how behavioural and neural mechanisms of social cognition respond to artificial anthropomorphic agents provides empirical answers to the conundrum 'What is a social agent?' © 2016 The Authors.

What is the Value of Embedding Artificial Emotional Prosody in Human–Computer Interactions? Implications for Theory and Design in Psychological Science

PubMed Central

Mitchell, Rachel L. C.; Xu, Yi

2015-01-01

In computerized technology, artificial speech is becoming increasingly important, and is already used in ATMs, online gaming and healthcare contexts. However, today’s artificial speech typically sounds monotonous, a main reason for this being the lack of meaningful prosody. One particularly important function of prosody is to convey different emotions. This is because successful encoding and decoding of emotions is vital for effective social cognition, which is increasingly recognized in human–computer interaction contexts. Current attempts to artificially synthesize emotional prosody are much improved relative to early attempts, but there remains much work to be done due to methodological problems, lack of agreed acoustic correlates, and lack of theoretical grounding. If the addition of synthetic emotional prosody is not of sufficient quality, it may risk alienating users instead of enhancing their experience. So the value of embedding emotion cues in artificial speech may ultimately depend on the quality of the synthetic emotional prosody. However, early evidence on reactions to synthesized non-verbal cues in the facial modality bodes well. Attempts to implement the recognition of emotional prosody into artificial applications and interfaces have perhaps been met with greater success, but the ultimate test of synthetic emotional prosody will be to critically compare how people react to synthetic emotional prosody vs. natural emotional prosody, at the behavioral, socio-cognitive and neural levels. PMID:26617563

Programs as Causal Models: Speculations on Mental Programs and Mental Representation

ERIC Educational Resources Information Center

Chater, Nick; Oaksford, Mike

2013-01-01

Judea Pearl has argued that counterfactuals and causality are central to intelligence, whether natural or artificial, and has helped create a rich mathematical and computational framework for formally analyzing causality. Here, we draw out connections between these notions and various current issues in cognitive science, including the nature of…

Modelling for Prediction vs. Modelling for Understanding: Commentary on Musso et al. (2013)

ERIC Educational Resources Information Center

Edelsbrunner, Peter; Schneider, Michael

2013-01-01

Musso et al. (2013) predict students' academic achievement with high accuracy one year in advance from cognitive and demographic variables, using artificial neural networks (ANNs). They conclude that ANNs have high potential for theoretical and practical improvements in learning sciences. ANNs are powerful statistical modelling tools but they can…

Linguistics as a Cognitive Science and Its Role in an Undergraduate Curriculum. Linguistics in the Undergraduate Curriculum, Appendix 4-F.

ERIC Educational Resources Information Center

Lakoff, George

In most colleges and universities, linguistics is taught very little, while disciplines intellectually dependent on results in linguistics are taught almost universally. An understanding of the central issues in philosophy, psychology, anthropology, literature, and artificial intelligence requires an understanding of linguistics, but most…

The Application of Cognitive Diagnostic Approaches via Neural Network Analysis of Serious Educational Games

NASA Astrophysics Data System (ADS)

Lamb, Richard L.

Serious Educational Games (SEGs) have been a topic of increased popularity within the educational realm since the early millennia. SEGs are generalized form of Serious Games to mean games for purposes other than entertainment but, that also specifically include training, educational purpose and pedagogy within their design. This rise in popularity (for SEGs) has occurred at a time when school systems have increased the type, number, and presentations of student achievement tests for decision-making purposes. These tests often task the form of end of course (year) tests and periodic benchmark testing. As the use of these tests, has increased policymakers have suggested their use as a measure for teacher accountability. The change in testing resulted from a push by school districts and policy makers at various component levels for a data-driven decision-making (D3M) approach. With the data-driven decision making approaches by school districts, there has been an increased focus on the measurement and assessment of student content knowledge with little focus on the contributing factors and cognitive attributes within learning that cross multiple-content areas. One-way to increase the focus on these aspects of learning (factors and attributes) that are additional to content learning is through assessments based in cognitive diagnostics. Cognitive diagnostics are a family of methodological approaches in which tasks tie to specific cognitive attributes for analytical purposes. This study explores data derived from computer data logging (n=158,000) in an observational design, using traditional statistical techniques such as clustering (exploratory and confirmatory), item response theory and through data mining techniques such as artificial neural network analysis. From these analyses, a model of student learning emerges illustrating student thinking and learning while engaged in SEG Design. This study seeks to use cognitive diagnostic type approaches to measure student learning while designing science task based SEGs. In addition, the study suggests that it may be possible to use SEGs to provide a means to administer cognitive diagnostic based assessments in real time. Results of this study suggest the confirmation of four families (factors) of traits illustrating a simple factor loading structure. Item response theory (IRT) results illustrate a 2-parameter logistic model (2PLM) fit allowing for parameterization using the IRT-True Score Method (chi2=1.70, df=1, p=0.19). Finally, fit statistics for the artificial neural network suggest the developed model adequately fits the current data set and provides a means to explore cognitive attributes and their effect on task outcomes. This study has developed a justification for combining and developing two distinct areas of research related to student learning. The first is the use of cognitive diagnostic approaches to assess student learning as it relates to the cognitive attributes used during science processing. The second area is an examination and modeling of the relationship between attributes as propagated in an artificial neural network. Results of the study provide for an ANN model of student cognition while designing science based SEGs (r 2=0.73, RMSE= 0.21) at a convergence of 1000 training iterations. The literature presented in this dissertation work integrates work from multiple field areas. Fields represented in this work range from science education, educational psychology, measurement, and computational psychology.

George A. Miller (1920-2012).

PubMed

Pinker, Steven

2013-09-01

Presents an obituary for George A. Miller (1920-2012). Miller ranks among the most important psychologists of the 20th century. In addition to writing one of the best known papers in the history of psychology ("The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information," published in Psychological Review in 1956), Miller also fomented the cognitive revolution, invented psycholinguistics and cognitive psychology, imported powerful ideas from the theories of information, communication, grammar, semantics, and artificial intelligence, and left us a sparkling oeuvre that proves that a rigorous scientist needn't write in soggy prose. Honors rained down on Miller. APA gave him the Award for Distinguished Scientific Contributions (1963), the American Psychological Foundation Gold Medal Award for Life Achievement in Psychological Science (1990), the William James Book Award (1992, for The Science of Words), and the Award for Lifetime Contributions to Psychology (2003), and named a prize after him, as did the Cognitive Neuroscience Society. Miller was also honored by the Association for Psychological Science and the American Speech and Hearing Association. In 2000, he won the John P. McGovern Award in the Behavioral Sciences from the American Association for the Advancement of Science, and in 1991, the National Medal of Science, the country's highest scientific honor. © 2013 APA, all rights reserved.

Probabilistic machine learning and artificial intelligence.

PubMed

Ghahramani, Zoubin

2015-05-28

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

Baby, Where Did You Get Those Eyes?: IEEE Pulse talks with Mark Sagar about the new face of artificial intelligence.

PubMed

Campbell, Sarah

2015-01-01

Mark Sagar is changing the way we look at computers by giving them faces?disconcertingly realistic human faces. Sagar first gained widespread recognition for his pioneering work in rendering faces for Hollywood movies, including Avatar and King Kong. With a Ph.D. degree in bioengineering and two Academy Awards under his belt, Sagar now directs a research lab at the University of Auckland, New Zealand, a combinatorial hub where artificial intelligence (AI), neuroscience, computer science, philosophy, and cognitive psychology intersect in creating interactive, intelligent technologies.

Probabilistic machine learning and artificial intelligence

NASA Astrophysics Data System (ADS)

Ghahramani, Zoubin

2015-05-01

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

Formally grounding spatio-temporal thinking.

PubMed

Klippel, Alexander; Wallgrün, Jan Oliver; Yang, Jinlong; Li, Rui; Dylla, Frank

2012-08-01

To navigate through daily life, humans use their ability to conceptualize spatio-temporal information, which ultimately leads to a system of categories. Likewise, the spatial sciences rely heavily on conceptualization and categorization as means to create knowledge when they process spatio-temporal data. In the spatial sciences and in related branches of artificial intelligence, an approach has been developed for processing spatio-temporal data on the level of coarse categories: qualitative spatio-temporal representation and reasoning (QSTR). Calculi developed in QSTR allow for the meaningful processing of and reasoning with spatio-temporal information. While qualitative calculi are widely acknowledged in the cognitive sciences, there is little behavioral assessment whether these calculi are indeed cognitively adequate. This is an astonishing conundrum given that these calculi are ubiquitous, are often intended to improve processes at the human-machine interface, and are on several occasions claimed to be cognitively adequate. We have systematically evaluated several approaches to formally characterize spatial relations from a cognitive-behavioral perspective for both static and dynamically changing spatial relations. This contribution will detail our framework, which is addressing the question how formal characterization of space can help us understand how people think with, in, and about space.

The Spatial and the Visual in Mental Spatial Reasoning: An Ill-Posed Distinction

NASA Astrophysics Data System (ADS)

Schultheis, Holger; Bertel, Sven; Barkowsky, Thomas; Seifert, Inessa

It is an ongoing and controversial debate in cognitive science which aspects of knowledge humans process visually and which ones they process spatially. Similarly, artificial intelligence (AI) and cognitive science research, in building computational cognitive systems, tended to use strictly spatial or strictly visual representations. The resulting systems, however, were suboptimal both with respect to computational efficiency and cognitive plau sibility. In this paper, we propose that the problems in both research strands stem from a mis conception of the visual and the spatial in mental spatial knowl edge pro cessing. Instead of viewing the visual and the spatial as two clearly separable categories, they should be conceptualized as the extremes of a con tinuous dimension of representation. Regarding psychology, a continuous di mension avoids the need to exclusively assign processes and representations to either one of the cate gories and, thus, facilitates a more unambiguous rating of processes and rep resentations. Regarding AI and cognitive science, the con cept of a continuous spatial / visual dimension provides the possibility of rep re sentation structures which can vary continuously along the spatial / visual di mension. As a first step in exploiting these potential advantages of the pro posed conception we (a) introduce criteria allowing for a non-dichotomic judgment of processes and representations and (b) present an approach towards rep re sentation structures that can flexibly vary along the spatial / visual dimension.

Active Learning with Statistical Models.

DTIC Science & Technology

1995-01-01

Active Learning with Statistical Models ASC-9217041, NSF CDA-9309300 6. AUTHOR(S) David A. Cohn, Zoubin Ghahramani, and Michael I. Jordan 7. PERFORMING...TERMS 15. NUMBER OF PAGES Al, MIT, Artificial Intelligence, active learning , queries, locally weighted 6 regression, LOESS, mixtures of gaussians...COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES A.I. Memo No. 1522 January 9. 1995 C.B.C.L. Paper No. 110 Active Learning with

Multiscale Modeling of Gene-Behavior Associations in an Artificial Neural Network Model of Cognitive Development.

PubMed

Thomas, Michael S C; Forrester, Neil A; Ronald, Angelica

2016-01-01

In the multidisciplinary field of developmental cognitive neuroscience, statistical associations between levels of description play an increasingly important role. One example of such associations is the observation of correlations between relatively common gene variants and individual differences in behavior. It is perhaps surprising that such associations can be detected despite the remoteness of these levels of description, and the fact that behavior is the outcome of an extended developmental process involving interaction of the whole organism with a variable environment. Given that they have been detected, how do such associations inform cognitive-level theories? To investigate this question, we employed a multiscale computational model of development, using a sample domain drawn from the field of language acquisition. The model comprised an artificial neural network model of past-tense acquisition trained using the backpropagation learning algorithm, extended to incorporate population modeling and genetic algorithms. It included five levels of description-four internal: genetic, network, neurocomputation, behavior; and one external: environment. Since the mechanistic assumptions of the model were known and its operation was relatively transparent, we could evaluate whether cross-level associations gave an accurate picture of causal processes. We established that associations could be detected between artificial genes and behavioral variation, even under polygenic assumptions of a many-to-one relationship between genes and neurocomputational parameters, and when an experience-dependent developmental process interceded between the action of genes and the emergence of behavior. We evaluated these associations with respect to their specificity (to different behaviors, to function vs. structure), to their developmental stability, and to their replicability, as well as considering issues of missing heritability and gene-environment interactions. We argue that gene-behavior associations can inform cognitive theory with respect to effect size, specificity, and timing. The model demonstrates a means by which researchers can undertake multiscale modeling with respect to cognition and develop highly specific and complex hypotheses across multiple levels of description. Copyright © 2015 Cognitive Science Society, Inc.

An Examination of Application of Artificial Neural Network in Cognitive Radios

NASA Astrophysics Data System (ADS)

Bello Salau, H.; Onwuka, E. N.; Aibinu, A. M.

2013-12-01

Recent advancement in software radio technology has led to the development of smart device known as cognitive radio. This type of radio fuses powerful techniques taken from artificial intelligence, game theory, wideband/multiple antenna techniques, information theory and statistical signal processing to create an outstanding dynamic behavior. This cognitive radio is utilized in achieving diverse set of applications such as spectrum sensing, radio parameter adaptation and signal classification. This paper contributes by reviewing different cognitive radio implementation that uses artificial intelligence such as the hidden markov models, metaheuristic algorithm and artificial neural networks (ANNs). Furthermore, different areas of application of ANNs and their performance metrics based approach are also examined.

Cognitive science in the era of artificial intelligence: A roadmap for reverse-engineering the infant language-learner.

PubMed

Dupoux, Emmanuel

2018-04-01

Spectacular progress in the information processing sciences (machine learning, wearable sensors) promises to revolutionize the study of cognitive development. Here, we analyse the conditions under which 'reverse engineering' language development, i.e., building an effective system that mimics infant's achievements, can contribute to our scientific understanding of early language development. We argue that, on the computational side, it is important to move from toy problems to the full complexity of the learning situation, and take as input as faithful reconstructions of the sensory signals available to infants as possible. On the data side, accessible but privacy-preserving repositories of home data have to be setup. On the psycholinguistic side, specific tests have to be constructed to benchmark humans and machines at different linguistic levels. We discuss the feasibility of this approach and present an overview of current results. Copyright © 2017 Elsevier B.V. All rights reserved.

Efficient coding explains the universal law of generalization in human perception.

PubMed

Sims, Chris R

2018-05-11

Perceptual generalization and discrimination are fundamental cognitive abilities. For example, if a bird eats a poisonous butterfly, it will learn to avoid preying on that species again by generalizing its past experience to new perceptual stimuli. In cognitive science, the "universal law of generalization" seeks to explain this ability and states that generalization between stimuli will follow an exponential function of their distance in "psychological space." Here, I challenge existing theoretical explanations for the universal law and offer an alternative account based on the principle of efficient coding. I show that the universal law emerges inevitably from any information processing system (whether biological or artificial) that minimizes the cost of perceptual error subject to constraints on the ability to process or transmit information. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Towards An Integrative Theory Of Consciousness: Part 2 (An Anthology Of Various Other Models)

PubMed Central

De Sousa, Avinash

2013-01-01

The study of consciousness has today moved beyond neurobiology and cognitive models. In the past few years, there has been a surge of research into various newer areas. The present article looks at the non-neurobiological and non-cognitive theories regarding this complex phenomenon, especially ones that self-psychology, self-theory, artificial intelligence, quantum physics, visual cognitive science and philosophy have to offer. Self-psychology has proposed the need to understand the self and its development, and the ramifications of the self for morality and empathy, which will help us understand consciousness better. There have been inroads made from the fields of computer science, machine technology and artificial intelligence, including robotics, into understanding the consciousness of these machines and their implications for human consciousness. These areas are explored. Visual cortex and emotional theories along with their implications are discussed. The phylogeny and evolution of the phenomenon of consciousness is also highlighted, with theories on the emergence of consciousness in fetal and neonatal life. Quantum physics and its insights into the mind, along with the implications of consciousness and physics and their interface are debated. The role of neurophilosophy to understand human consciousness, the functions of such a concept, embodiment, the dark side of consciousness, future research needs and limitations of a scientific theory of consciousness complete the review. The importance and salient features of each theory are discussed along with certain pitfalls, if present. A need for the integration of various theories to understand consciousness from a holistic perspective is stressed. PMID:23678242

Towards an integrative theory of consciousness: part 2 (an anthology of various other models).

PubMed

De Sousa, Avinash

2013-01-01

The study of consciousness has today moved beyond neurobiology and cognitive models. In the past few years, there has been a surge of research into various newer areas. The present article looks at the non-neurobiological and non-cognitive theories regarding this complex phenomenon, especially ones that self-psychology, self-theory, artificial intelligence, quantum physics, visual cognitive science and philosophy have to offer. Self-psychology has proposed the need to understand the self and its development, and the ramifications of the self for morality and empathy, which will help us understand consciousness better. There have been inroads made from the fields of computer science, machine technology and artificial intelligence, including robotics, into understanding the consciousness of these machines and their implications for human consciousness. These areas are explored. Visual cortex and emotional theories along with their implications are discussed. The phylogeny and evolution of the phenomenon of consciousness is also highlighted, with theories on the emergence of consciousness in fetal and neonatal life. Quantum physics and its insights into the mind, along with the implications of consciousness and physics and their interface are debated. The role of neurophilosophy to understand human consciousness, the functions of such a concept, embodiment, the dark side of consciousness, future research needs and limitations of a scientific theory of consciousness complete the review. The importance and salient features of each theory are discussed along with certain pitfalls, if present. A need for the integration of various theories to understand consciousness from a holistic perspective is stressed.

The Relationship Between Artificial and Second Language Learning.

PubMed

Ettlinger, Marc; Morgan-Short, Kara; Faretta-Stutenberg, Mandy; Wong, Patrick C M

2016-05-01

Artificial language learning (ALL) experiments have become an important tool in exploring principles of language and language learning. A persistent question in all of this work, however, is whether ALL engages the linguistic system and whether ALL studies are ecologically valid assessments of natural language ability. In the present study, we considered these questions by examining the relationship between performance in an ALL task and second language learning ability. Participants enrolled in a Spanish language class were evaluated using a number of different measures of Spanish ability and classroom performance, which was compared to IQ and a number of different measures of ALL performance. The results show that success in ALL experiments, particularly more complex artificial languages, correlates positively with indices of L2 learning even after controlling for IQ. These findings provide a key link between studies involving ALL and our understanding of second language learning in the classroom. Copyright © 2015 Cognitive Science Society, Inc.

From automata to animate beings: the scope and limits of attributing socialness to artificial agents.

PubMed

Hortensius, Ruud; Cross, Emily S

2018-05-11

Understanding the mechanisms and consequences of attributing socialness to artificial agents has important implications for how we can use technology to lead more productive and fulfilling lives. Here, we integrate recent findings on the factors that shape behavioral and brain mechanisms that support social interactions between humans and artificial agents. We review how visual features of an agent, as well as knowledge factors within the human observer, shape attributions across dimensions of socialness. We explore how anthropomorphism and dehumanization further influence how we perceive and interact with artificial agents. Based on these findings, we argue that the cognitive reconstruction within the human observer is likely to be far more crucial in shaping our interactions with artificial agents than previously thought, while the artificial agent's visual features are possibly of lesser importance. We combine these findings to provide an integrative theoretical account based on the "like me" hypothesis, and discuss the key role played by the Theory-of-Mind network, especially the temporal parietal junction, in the shift from mechanistic to social attributions. We conclude by highlighting outstanding questions on the impact of long-term interactions with artificial agents on the behavioral and brain mechanisms of attributing socialness to these agents. © 2018 New York Academy of Sciences.

Soar: A Unified Theory of Cognition?

ERIC Educational Resources Information Center

Waldrop, M. Mitchell

1988-01-01

Describes an artificial intelligence system known as SOAR that approximates a theory of human cognition. Discusses cognition as problem solving, working memory, long term memory, autonomy and adaptability, and learning from experience as they relate to artificial intelligence generally and to SOAR specifically. Highlights the status of the…

After-School and Informal STEM Projects: the Effect of Participant Self-Selection

NASA Astrophysics Data System (ADS)

Vallett, David B.; Lamb, Richard; Annetta, Leonard

2017-12-01

This research represents an unforeseen outcome of the authors' National Science Foundation Innovation Technology Experiences for Students and Teachers (ITEST) program grant in science education. The grant itself focused on the use of serious educational games (SEGs) in the science classroom, both during and after school, to teach science content and affect student perceptions of science and technology. This study consists of a Bayesian artificial neural network analysis, using the preintervention measures of affect, interest, personality, and cognitive ability, in members of both the treatment and comparison groups to generate the probabilities that students would opt into the treatment group or choose not to participate. It appears, from this sample and the sampling methods of other related studies within the field, that despite sometimes profound results from technology interventions in science, interventions are affecting only those who already have a strong interest in STEM due to the manner in which participants are recruited.

Computational models of music perception and cognition I: The perceptual and cognitive processing chain

NASA Astrophysics Data System (ADS)

Purwins, Hendrik; Herrera, Perfecto; Grachten, Maarten; Hazan, Amaury; Marxer, Ricard; Serra, Xavier

2008-09-01

We present a review on perception and cognition models designed for or applicable to music. An emphasis is put on computational implementations. We include findings from different disciplines: neuroscience, psychology, cognitive science, artificial intelligence, and musicology. The article summarizes the methodology that these disciplines use to approach the phenomena of music understanding, the localization of musical processes in the brain, and the flow of cognitive operations involved in turning physical signals into musical symbols, going from the transducers to the memory systems of the brain. We discuss formal models developed to emulate, explain and predict phenomena involved in early auditory processing, pitch processing, grouping, source separation, and music structure computation. We cover generic computational architectures of attention, memory, and expectation that can be instantiated and tuned to deal with specific musical phenomena. Criteria for the evaluation of such models are presented and discussed. Thereby, we lay out the general framework that provides the basis for the discussion of domain-specific music models in Part II.

Building brains for bodies

NASA Technical Reports Server (NTRS)

Brooks, Rodney Allen; Stein, Lynn Andrea

1994-01-01

We describe a project to capitalize on newly available levels of computational resources in order to understand human cognition. We will build an integrated physical system including vision, sound input and output, and dextrous manipulation, all controlled by a continuously operating large scale parallel MIMD computer. The resulting system will learn to 'think' by building on its bodily experiences to accomplish progressively more abstract tasks. Past experience suggests that in attempting to build such an integrated system we will have to fundamentally change the way artificial intelligence, cognitive science, linguistics, and philosophy think about the organization of intelligence. We expect to be able to better reconcile the theories that will be developed with current work in neuroscience.

Artificial Intelligence, Counseling, and Cognitive Psychology.

ERIC Educational Resources Information Center

Brack, Greg; And Others

With the exception of a few key writers, counselors largely ignore the benefits that Artificial Intelligence (AI) and Cognitive Psychology (CP) can bring to counseling. It is demonstrated that AI and CP can be integrated into the counseling literature. How AI and CP can offer new perspectives on information processing, cognition, and helping is…

Experimental Evaluation of Performance Feedback Using the Dismounted Infantry Virtual After Action Review System. Long Range Navy and Marine Corps Science and Technology Program

DTIC Science & Technology

2007-11-14

Artificial intelligence and 4 23 education , Volume 1: Learning environments and tutoring systems. Hillsdale, NJ: Erlbaum. Wickens, C.D. (1984). Processing...and how to use it to best optimize the learning process. Some researchers (see Loftin & Savely, 1991) have proposed adding intelligent systems to the...is experienced as the cognitive centers in an individual’s brain process visual, tactile, kinesthetic , olfactory, proprioceptive, and auditory

Artificial intelligence and synthetic biology: A tri-temporal contribution.

PubMed

Bianchini, Francesco

2016-10-01

Artificial intelligence can make numerous contributions to synthetic biology. I would like to suggest three that are related to the past, present and future of artificial intelligence. From the past, works in biology and artificial systems by Turing and von Neumann prove highly interesting to explore within the new framework of synthetic biology, especially with regard to the notions of self-modification and self-replication and their links to emergence and the bottom-up approach. The current epistemological inquiry into emergence and research on swarm intelligence, superorganisms and biologically inspired cognitive architecture may lead to new achievements on the possibilities of synthetic biology in explaining cognitive processes. Finally, the present-day discussion on the future of artificial intelligence and the rise of superintelligence may point to some research trends for the future of synthetic biology and help to better define the boundary of notions such as "life", "cognition", "artificial" and "natural", as well as their interconnections in theoretical synthetic biology. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Teaching problem solving: Don't forget the problem solver(s)

NASA Astrophysics Data System (ADS)

Ranade, Saidas M.; Corrales, Angela

2013-05-01

The importance of intrapersonal and interpersonal intelligences has long been known but educators have debated whether to and how to incorporate those topics in an already crowded engineering curriculum. In 2010, the authors used the classroom as a laboratory to observe the usefulness of including selected case studies and exercises from the fields of neurology, artificial intelligence, cognitive sciences and social psychology in a new problem-solving course. To further validate their initial findings, in 2012, the authors conducted an online survey of engineering students and engineers. The main conclusion is that engineering students will benefit from learning more about the impact of emotions, culture, diversity and cognitive biases when solving problems. Specifically, the work shows that an augmented problem-solving curriculum needs to include lessons on labelling emotions and cognitive biases, 'evidence-based' data on the importance of culture and diversity and additional practice on estimating conditional probability.

Understanding Minds in Real-World Environments: Toward a Mobile Cognition Approach.

PubMed

Ladouce, Simon; Donaldson, David I; Dudchenko, Paul A; Ietswaart, Magdalena

2016-01-01

There is a growing body of evidence that important aspects of human cognition have been marginalized, or overlooked, by traditional cognitive science. In particular, the use of laboratory-based experiments in which stimuli are artificial, and response options are fixed, inevitably results in findings that are less ecologically valid in relation to real-world behavior. In the present review we highlight the opportunities provided by a range of new mobile technologies that allow traditionally lab-bound measurements to now be collected during natural interactions with the world. We begin by outlining the theoretical support that mobile approaches receive from the development of embodied accounts of cognition, and we review the widening evidence that illustrates the importance of examining cognitive processes in their context. As we acknowledge, in practice, the development of mobile approaches brings with it fresh challenges, and will undoubtedly require innovation in paradigm design and analysis. If successful, however, the mobile cognition approach will offer novel insights in a range of areas, including understanding the cognitive processes underlying navigation through space and the role of attention during natural behavior. We argue that the development of real-world mobile cognition offers both increased ecological validity, and the opportunity to examine the interactions between perception, cognition and action-rather than examining each in isolation.

Understanding Minds in Real-World Environments: Toward a Mobile Cognition Approach

PubMed Central

Ladouce, Simon; Donaldson, David I.; Dudchenko, Paul A.; Ietswaart, Magdalena

2017-01-01

There is a growing body of evidence that important aspects of human cognition have been marginalized, or overlooked, by traditional cognitive science. In particular, the use of laboratory-based experiments in which stimuli are artificial, and response options are fixed, inevitably results in findings that are less ecologically valid in relation to real-world behavior. In the present review we highlight the opportunities provided by a range of new mobile technologies that allow traditionally lab-bound measurements to now be collected during natural interactions with the world. We begin by outlining the theoretical support that mobile approaches receive from the development of embodied accounts of cognition, and we review the widening evidence that illustrates the importance of examining cognitive processes in their context. As we acknowledge, in practice, the development of mobile approaches brings with it fresh challenges, and will undoubtedly require innovation in paradigm design and analysis. If successful, however, the mobile cognition approach will offer novel insights in a range of areas, including understanding the cognitive processes underlying navigation through space and the role of attention during natural behavior. We argue that the development of real-world mobile cognition offers both increased ecological validity, and the opportunity to examine the interactions between perception, cognition and action—rather than examining each in isolation. PMID:28127283

A Symbolic Model of the Nonconscious Acquisition of Information.

ERIC Educational Resources Information Center

Ling, Charles X.; Marinov, Marin

1994-01-01

Challenges Smolensky's theory that human intuitive/nonconscious cognitive processes can only be accurately explained in terms of subsymbolic computations in artificial neural networks. Symbolic learning models of two cognitive tasks involving nonconscious acquisition of information are presented: learning production rules and artificial finite…

A Contrast-Based Computational Model of Surprise and Its Applications.

PubMed

Macedo, Luis; Cardoso, Amílcar

2017-11-19

We review our work on a contrast-based computational model of surprise and its applications. The review is contextualized within related research from psychology, philosophy, and particularly artificial intelligence. Influenced by psychological theories of surprise, the model assumes that surprise-eliciting events initiate a series of cognitive processes that begin with the appraisal of the event as unexpected, continue with the interruption of ongoing activity and the focusing of attention on the unexpected event, and culminate in the analysis and evaluation of the event and the revision of beliefs. It is assumed that the intensity of surprise elicited by an event is a nonlinear function of the difference or contrast between the subjective probability of the event and that of the most probable alternative event (which is usually the expected event); and that the agent's behavior is partly controlled by actual and anticipated surprise. We describe applications of artificial agents that incorporate the proposed surprise model in three domains: the exploration of unknown environments, creativity, and intelligent transportation systems. These applications demonstrate the importance of surprise for decision making, active learning, creative reasoning, and selective attention. Copyright © 2017 Cognitive Science Society, Inc.

Exploiting multiple sources of information in learning an artificial language: human data and modeling.

PubMed

Perruchet, Pierre; Tillmann, Barbara

2010-03-01

This study investigates the joint influences of three factors on the discovery of new word-like units in a continuous artificial speech stream: the statistical structure of the ongoing input, the initial word-likeness of parts of the speech flow, and the contextual information provided by the earlier emergence of other word-like units. Results of an experiment conducted with adult participants show that these sources of information have strong and interactive influences on word discovery. The authors then examine the ability of different models of word segmentation to account for these results. PARSER (Perruchet & Vinter, 1998) is compared to the view that word segmentation relies on the exploitation of transitional probabilities between successive syllables, and with the models based on the Minimum Description Length principle, such as INCDROP. The authors submit arguments suggesting that PARSER has the advantage of accounting for the whole pattern of data without ad-hoc modifications, while relying exclusively on general-purpose learning principles. This study strengthens the growing notion that nonspecific cognitive processes, mainly based on associative learning and memory principles, are able to account for a larger part of early language acquisition than previously assumed. Copyright © 2009 Cognitive Science Society, Inc.

Advanced Artificial Science. The development of an artificial science and engineering research infrastructure to facilitate innovative computational modeling, analysis, and application to interdisciplinary areas of scientific investigation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saffer, Shelley

2014-12-01

This is a final report of the DOE award DE-SC0001132, Advanced Artificial Science. The development of an artificial science and engineering research infrastructure to facilitate innovative computational modeling, analysis, and application to interdisciplinary areas of scientific investigation. This document describes the achievements of the goals, and resulting research made possible by this award.

Statistical Classification for Cognitive Diagnostic Assessment: An Artificial Neural Network Approach

ERIC Educational Resources Information Center

Cui, Ying; Gierl, Mark; Guo, Qi

2016-01-01

The purpose of the current investigation was to describe how the artificial neural networks (ANNs) can be used to interpret student performance on cognitive diagnostic assessments (CDAs) and evaluate the performances of ANNs using simulation results. CDAs are designed to measure student performance on problem-solving tasks and provide useful…

The importance of motivation and emotion for explaining human cognition.

PubMed

Güss, C Dominik; Dörner, Dietrich

2017-01-01

Lake et al. discuss building blocks of human intelligence that are quite different from those of artificial intelligence. We argue that a theory of human intelligence has to incorporate human motivations and emotions. The interaction of motivation, emotion, and cognition is the real strength of human intelligence and distinguishes it from artificial intelligence.

Instrumentation for Scientific Computing in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics.

DTIC Science & Technology

1987-10-01

include Security Classification) Instrumentation for scientific computing in neural networks, information science, artificial intelligence, and...instrumentation grant to purchase equipment for support of research in neural networks, information science, artificail intellignece , and applied mathematics...in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics Contract AFOSR 86-0282 Principal Investigator: Stephen

Incremental Bayesian Category Learning From Natural Language.

PubMed

Frermann, Lea; Lapata, Mirella

2016-08-01

Models of category learning have been extensively studied in cognitive science and primarily tested on perceptual abstractions or artificial stimuli. In this paper, we focus on categories acquired from natural language stimuli, that is, words (e.g., chair is a member of the furniture category). We present a Bayesian model that, unlike previous work, learns both categories and their features in a single process. We model category induction as two interrelated subproblems: (a) the acquisition of features that discriminate among categories, and (b) the grouping of concepts into categories based on those features. Our model learns categories incrementally using particle filters, a sequential Monte Carlo method commonly used for approximate probabilistic inference that sequentially integrates newly observed data and can be viewed as a plausible mechanism for human learning. Experimental results show that our incremental learner obtains meaningful categories which yield a closer fit to behavioral data compared to related models while at the same time acquiring features which characterize the learned categories. (An earlier version of this work was published in Frermann and Lapata .). Copyright © 2015 Cognitive Science Society, Inc.

Cognitive Inference Device for Activity Supervision in the Elderly

PubMed Central

2014-01-01

Human activity, life span, and quality of life are enhanced by innovations in science and technology. Aging individual needs to take advantage of these developments to lead a self-regulated life. However, maintaining a self-regulated life at old age involves a high degree of risk, and the elderly often fail at this goal. Thus, the objective of our study is to investigate the feasibility of implementing a cognitive inference device (CI-device) for effective activity supervision in the elderly. To frame the CI-device, we propose a device design framework along with an inference algorithm and implement the designs through an artificial neural model with different configurations, mapping the CI-device's functions to minimise the device's prediction error. An analysis and discussion are then provided to validate the feasibility of CI-device implementation for activity supervision in the elderly. PMID:25405211

BACS: The Brussels Artificial Character Sets for studies in cognitive psychology and neuroscience.

PubMed

Vidal, Camille; Content, Alain; Chetail, Fabienne

2017-12-01

Written symbols such as letters have been used extensively in cognitive psychology, whether to understand their contributions to written word recognition or to examine the processes involved in other mental functions. Sometimes, however, researchers want to manipulate letters while removing their associated characteristics. A powerful solution to do so is to use new characters, devised to be highly similar to letters, but without the associated sound or name. Given the growing use of artificial characters in experimental paradigms, the aim of the present study was to make available the Brussels Artificial Character Sets (BACS): two full, strictly controlled, and portable sets of artificial characters for a broad range of experimental situations.

How to make an autonomous robot as a partner with humans: design approach versus emergent approach.

PubMed

Fujita, M

2007-01-15

In this paper, we discuss what factors are important to realize an autonomous robot as a partner with humans. We believe that it is important to interact with people without boring them, using verbal and non-verbal communication channels. We have already developed autonomous robots such as AIBO and QRIO, whose behaviours are manually programmed and designed. We realized, however, that this design approach has limitations; therefore we propose a new approach, intelligence dynamics, where interacting in a real-world environment using embodiment is considered very important. There are pioneering works related to this approach from brain science, cognitive science, robotics and artificial intelligence. We assert that it is important to study the emergence of entire sets of autonomous behaviours and present our approach towards this goal.

Long term effect of breast feeding: cognitive function in the Caerphilly cohort

PubMed Central

Elwood, P; Pickering, J.; Gallacher, J; Hughes, J.; Davies, D.

2005-01-01

Study objective: There is evidence suggesting that artificial feeding is associated with a reduction in cognitive function in infants and children, in contrast with breast feeding, but the available evidence suffers from confounding by social and educational factors. An opportunity arose in the Caerphilly cohort study to examine relations between cognitive function in older men and their feeding as infants, when breast feeding was usual. Design: A prospective cohort study. Setting: Caerphilly, South Wales, UK, was a deprived coal mining community when the men had been born in 1920–35. Most had been breast fed as infants. Participants: 779 men aged 60–74 years when tested. The men had earlier been asked to obtain from their mothers their birth weight, and how they had been fed as infants. Results: Complete data were obtained for 779 men. In those whose birth weight had been at or above the median, the adjusted mean cognitive function was only slightly and non-significantly lower in those who had been artificially fed. In the men whose birth weight had been below the median, having been artificially fed was associated with significantly lower results in both a test of reasoning (the AH4) and word power (the national adult reading test (NART)). Two standard deviations below the median birth weight, artificial feeding was associated with a reduction of six points (70% of a SD) on word power (the NART). Conclusions: In men whose birth weight had been low, having been artificially fed is associated with poorer cognitive function in late adult life. PMID:15650144

The emergence of mind and brain: an evolutionary, computational, and philosophical approach.

PubMed

Mainzer, Klaus

2008-01-01

Modern philosophy of mind cannot be understood without recent developments in computer science, artificial intelligence (AI), robotics, neuroscience, biology, linguistics, and psychology. Classical philosophy of formal languages as well as symbolic AI assume that all kinds of knowledge must explicitly be represented by formal or programming languages. This assumption is limited by recent insights into the biology of evolution and developmental psychology of the human organism. Most of our knowledge is implicit and unconscious. It is not formally represented, but embodied knowledge, which is learnt by doing and understood by bodily interacting with changing environments. That is true not only for low-level skills, but even for high-level domains of categorization, language, and abstract thinking. The embodied mind is considered an emergent capacity of the brain as a self-organizing complex system. Actually, self-organization has been a successful strategy of evolution to handle the increasing complexity of the world. Genetic programs are not sufficient and cannot prepare the organism for all kinds of complex situations in the future. Self-organization and emergence are fundamental concepts in the theory of complex dynamical systems. They are also applied in organic computing as a recent research field of computer science. Therefore, cognitive science, AI, and robotics try to model the embodied mind in an artificial evolution. The paper analyzes these approaches in the interdisciplinary framework of complex dynamical systems and discusses their philosophical impact.

Autonomous Driver Based on an Intelligent System of Decision-Making.

PubMed

Czubenko, Michał; Kowalczuk, Zdzisław; Ordys, Andrew

The paper presents and discusses a system ( xDriver ) which uses an Intelligent System of Decision-making (ISD) for the task of car driving. The principal subject is the implementation, simulation and testing of the ISD system described earlier in our publications (Kowalczuk and Czubenko in artificial intelligence and soft computing lecture notes in computer science, lecture notes in artificial intelligence, Springer, Berlin, 2010, 2010, In Int J Appl Math Comput Sci 21(4):621-635, 2011, In Pomiary Autom Robot 2(17):60-5, 2013) for the task of autonomous driving. The design of the whole ISD system is a result of a thorough modelling of human psychology based on an extensive literature study. Concepts somehow similar to the ISD system can be found in the literature (Muhlestein in Cognit Comput 5(1):99-105, 2012; Wiggins in Cognit Comput 4(3):306-319, 2012), but there are no reports of a system which would model the human psychology for the purpose of autonomously driving a car. The paper describes assumptions for simulation, the set of needs and reactions (characterizing the ISD system), the road model and the vehicle model, as well as presents some results of simulation. It proves that the xDriver system may behave on the road as a very inexperienced driver.

Multimodal interactions in typically and atypically developing children: natural versus artificial environments.

PubMed

Giannopulu, Irini

2013-11-01

This review addresses the central role played by multimodal interactions in neurocognitive development. We first analyzed our studies of multimodal verbal and nonverbal cognition and emotional interactions within neuronal, that is, natural environments in typically developing children. We then tried to relate them to the topic of creating artificial environments using mobile toy robots to neurorehabilitate severely autistic children. By doing so, both neural/natural and artificial environments are considered as the basis of neuronal organization and reorganization. The common thread underlying the thinking behind this approach revolves around the brain's intrinsic properties: neuroplasticity and the fact that the brain is neurodynamic. In our approach, neural organization and reorganization using natural or artificial environments aspires to bring computational perspectives into cognitive developmental neuroscience.

Philosophy for the rest of cognitive science.

PubMed

Stepp, Nigel; Chemero, Anthony; Turvey, Michael T

2011-04-01

Cognitive science has always included multiple methodologies and theoretical commitments. The philosophy of cognitive science should embrace, or at least acknowledge, this diversity. Bechtel's (2009a) proposed philosophy of cognitive science, however, applies only to representationalist and mechanist cognitive science, ignoring the substantial minority of dynamically oriented cognitive scientists. As an example of nonrepresentational, dynamical cognitive science, we describe strong anticipation as a model for circadian systems (Stepp & Turvey, 2009). We then propose a philosophy of science appropriate to nonrepresentational, dynamical cognitive science. Copyright © 2011 Cognitive Science Society, Inc.

Psychophysiological Effects of a Single, Short, and Moderately Bright Room Light Exposure on Mildly Depressed Geriatric Inpatients: A Pilot Study.

PubMed

Canazei, Markus; Pohl, Wilfried; Bauernhofer, Kathrin; Papousek, Ilona; Lackner, Helmut K; Bliem, Harald R; Marksteiner, Josef; Weiss, Elisabeth M

2017-01-01

Light interventions typically exert their mood-related effects during morning bright light exposures over several weeks. Evidence about immediate ambient room light effects on depressed individuals is still sparse. The present study aimed at examining the acute effects of a single moderately bright room light exposure on mood, and behavioural and cardiac stress reactions of mildly depressed geriatric inpatients during a short cognitive stimulation and while resting. Twenty-one inpatients were tested in a balanced cross-over design on 2 consecutive days under either conventional room light (standard light) or artificial sunlight conditions for 30 min. Room illumination was implemented with an artificial skylight, which perfectly imitated solar indoor illumination (e.g., cloudless sky and bright artificial sun). Light-induced changes of mood, heart rate, and heart rate variability were recorded while performing a perseveration test (acted as cognitive stimulation) twice. Additionally, light-related behaviour was observed during a resting period between the cognitive tests and various subjective ratings were obtained. Compared to standard light, exposure to artificial sunlight had a subjective calming effect over time (p = 0.029) as well as decreased heart rate and increased vagal tone (root mean squared of successive inter-beat intervals), both under cognitive workload and in resting conditions. Effect sizes of reported cardiac reactions were large. Cognitive variables were not influenced by light. Additionally, under the higher corneal illuminance of the artificial sunlight, patients perceived stronger glare (p = 0.030) and kept their eyes closed for longer times (p = 0.033) during the resting period. However, patients did not avoid bright light exposure while resting but voluntarily stayed within the area directly lit by the artificial sun nearly all the time (97%). To our knowledge, this study for the first time demonstrated immediate psychophysiological effects of a single, short room light exposure in mildly depressed geriatric inpatients during a short cognitive stimulation and while resting. The findings complement reported evidence on immediate alerting and mood-related effects of bright light exposures. © 2017 S. Karger AG, Basel.

Artificial Intelligence and Language Comprehension.

ERIC Educational Resources Information Center

National Inst. of Education (DHEW), Washington, DC. Basic Skills Group. Learning Div.

The three papers in this volume concerning artificial intelligence and language comprehension were commissioned by the National Institute of Education to further the understanding of the cognitive processes that enable people to comprehend what they read. The first paper, "Artificial Intelligence and Language Comprehension," by Terry Winograd,…

Neurobiomimetic constructs for intelligent unmanned systems and robotics

NASA Astrophysics Data System (ADS)

Braun, Jerome J.; Shah, Danelle C.; DeAngelus, Marianne A.

2014-06-01

This paper discusses a paradigm we refer to as neurobiomimetic, which involves emulations of brain neuroanatomy and neurobiology aspects and processes. Neurobiomimetic constructs include rudimentary and down-scaled computational representations of brain regions, sub-regions, and synaptic connectivity. Many different instances of neurobiomimetic constructs are possible, depending on various aspects such as the initial conditions of synaptic connectivity, number of neuron elements in regions, connectivity specifics, and more, and we refer to these instances as `animats'. While downscaled for computational feasibility, the animats are very large constructs; the animats implemented in this work contain over 47,000 neuron elements and over 720,000 synaptic connections. The paper outlines aspects of the animats implemented, spatial memory and learning cognitive task, the virtual-reality environment constructed to study the animat performing that task, and discussion of results. In a broad sense, we argue that the neurobiomimetic paradigm pursued in this work constitutes a particularly promising path to artificial cognition and intelligent unmanned systems. Biological brains readily cope with challenges of real-life tasks that consistently prove beyond even the most sophisticated algorithmic approaches known. At the cross-over point of neuroscience, cognitive science and computer science, paradigms such as the one pursued in this work aim to mimic the mechanisms of biological brains and as such, we argue, may lead to machines with abilities closer to those of biological species.

Comparison between artificial neural network and multilinear regression models in an evaluation of cognitive workload in a flight simulator.

PubMed

Hannula, Manne; Huttunen, Kerttu; Koskelo, Jukka; Laitinen, Tomi; Leino, Tuomo

2008-01-01

In this study, the performances of artificial neural network (ANN) analysis and multilinear regression (MLR) model-based estimation of heart rate were compared in an evaluation of individual cognitive workload. The data comprised electrocardiography (ECG) measurements and an evaluation of cognitive load that induces psychophysiological stress (PPS), collected from 14 interceptor fighter pilots during complex simulated F/A-18 Hornet air battles. In our data, the mean absolute error of the ANN estimate was 11.4 as a visual analog scale score, being 13-23% better than the mean absolute error of the MLR model in the estimation of cognitive workload.

Artificial Neural Networks and Instructional Technology.

ERIC Educational Resources Information Center

Carlson, Patricia A.

1991-01-01

Artificial neural networks (ANN), part of artificial intelligence, are discussed. Such networks are fed sample cases (training sets), learn how to recognize patterns in the sample data, and use this experience in handling new cases. Two cognitive roles for ANNs (intelligent filters and spreading, associative memories) are examined. Prototypes…

The Outline of Personhood Law Regarding Artificial Intelligences and Emulated Human Entities

NASA Astrophysics Data System (ADS)

Muzyka, Kamil

2013-12-01

On the verge of technological breakthroughs, which define and revolutionize our understanding of intelligence, cognition, and personhood, especially when speaking of artificial intelligences and mind uploads, one must consider the legal implications of granting personhood rights to artificial intelligences or emulated human entities

Quantum-like Probabilistic Models Outside Physics

NASA Astrophysics Data System (ADS)

Khrennikov, Andrei

We present a quantum-like (QL) model in that contexts (complexes of e.g. mental, social, biological, economic or even political conditions) are represented by complex probability amplitudes. This approach gives the possibility to apply the mathematical quantum formalism to probabilities induced in any domain of science. In our model quantum randomness appears not as irreducible randomness (as it is commonly accepted in conventional quantum mechanics, e.g. by von Neumann and Dirac), but as a consequence of obtaining incomplete information about a system. We pay main attention to the QL description of processing of incomplete information. Our QL model can be useful in cognitive, social and political sciences as well as economics and artificial intelligence. In this paper we consider in a more detail one special application — QL modeling of brain's functioning. The brain is modeled as a QL-computer.

Constructing a philosophy of science of cognitive science.

PubMed

Bechtel, William

2009-07-01

Philosophy of science is positioned to make distinctive contributions to cognitive science by providing perspective on its conceptual foundations and by advancing normative recommendations. The philosophy of science I embrace is naturalistic in that it is grounded in the study of actual science. Focusing on explanation, I describe the recent development of a mechanistic philosophy of science from which I draw three normative consequences for cognitive science. First, insofar as cognitive mechanisms are information-processing mechanisms, cognitive science needs an account of how the representations invoked in cognitive mechanisms carry information about contents, and I suggest that control theory offers the needed perspective on the relation of representations to contents. Second, I argue that cognitive science requires, but is still in search of, a catalog of cognitive operations that researchers can draw upon in explaining cognitive mechanisms. Last, I provide a new perspective on the relation of cognitive science to brain sciences, one which embraces both reductive research on neural components that figure in cognitive mechanisms and a concern with recomposing higher-level mechanisms from their components and situating them in their environments. Copyright © 2009 Cognitive Science Society, Inc.

Data Mining and Knowledge Discover - IBM Cognitive Alternatives for NASA KSC

NASA Technical Reports Server (NTRS)

Velez, Victor Hugo

2016-01-01

Skillful tools in cognitive computing to transform industries have been found favorable and profitable for different Directorates at NASA KSC. In this study is shown how cognitive computing systems can be useful for NASA when computers are trained in the same way as humans are to gain knowledge over time. Increasing knowledge through senses, learning and a summation of events is how the applications created by the firm IBM empower the artificial intelligence in a cognitive computing system. NASA has explored and applied for the last decades the artificial intelligence approach specifically with cognitive computing in few projects adopting similar models proposed by IBM Watson. However, the usage of semantic technologies by the dedicated business unit developed by IBM leads these cognitive computing applications to outperform the functionality of the inner tools and present outstanding analysis to facilitate the decision making for managers and leads in a management information system.

Artificial gravity as a multi-system countermeasure: effects on cognitive function.

PubMed

Seaton, Kimberly A; Slack, Kelley J; Sipes, Walter; Bowie, Kendra

2007-07-01

The Space Flight Cognitive Assessment Tool for Windows (WinSCAT) is used on the International Space Station to evaluate cognitive functioning after physical insult or trauma. The current study uses WinSCAT to assess cognitive functioning in a space flight analog (bed rest) environment where intermittent artificial gravity (AG) is being tested as a countermeasure. Fifteen male subjects (8 treatment, 7 control), who participated in 21 days of 6 degree head-down tilt bed rest, were assessed during the acclimatization phase, bed rest phase, and recovery phase. Individual differences were found within both the treatment and control groups. The treatment group accounted for more off-nominal WinSCAT scores than the control group. The length of time spent in bed rest was not associated with a change in cognitive function. Individual differences in underlying cognitive ability and motivation level are other possible explanations for the current findings.

Expertise, Task Complexity, and Artificial Intelligence: A Conceptual Framework.

ERIC Educational Resources Information Center

Buckland, Michael K.; Florian, Doris

1991-01-01

Examines the relationship between users' expertise, task complexity of information system use, and artificial intelligence to provide the basis for a conceptual framework for considering the role that artificial intelligence might play in information systems. Cognitive and conceptual models are discussed, and cost effectiveness is considered. (27…

Cognitive anthropology is a cognitive science.

PubMed

Boster, James S

2012-07-01

Cognitive anthropology contributes to cognitive science as a complement to cognitive psychology. The chief threat to its survival has not been rejection by other cognitive scientists but by other cultural anthropologists. It will remain a part of cognitive science as long as cognitive anthropologists research, teach, and publish. Copyright © 2012 Cognitive Science Society, Inc.

Artificial Intelligence in Medical Practice: The Question to the Answer?

PubMed

Miller, D Douglas; Brown, Eric W

2018-02-01

Computer science advances and ultra-fast computing speeds find artificial intelligence (AI) broadly benefitting modern society-forecasting weather, recognizing faces, detecting fraud, and deciphering genomics. AI's future role in medical practice remains an unanswered question. Machines (computers) learn to detect patterns not decipherable using biostatistics by processing massive datasets (big data) through layered mathematical models (algorithms). Correcting algorithm mistakes (training) adds to AI predictive model confidence. AI is being successfully applied for image analysis in radiology, pathology, and dermatology, with diagnostic speed exceeding, and accuracy paralleling, medical experts. While diagnostic confidence never reaches 100%, combining machines plus physicians reliably enhances system performance. Cognitive programs are impacting medical practice by applying natural language processing to read the rapidly expanding scientific literature and collate years of diverse electronic medical records. In this and other ways, AI may optimize the care trajectory of chronic disease patients, suggest precision therapies for complex illnesses, reduce medical errors, and improve subject enrollment into clinical trials. Copyright © 2018 Elsevier Inc. All rights reserved.

The Effects of Mood, Cognitive Style, and Cognitive Ability on Implicit Learning

ERIC Educational Resources Information Center

Pretz, Jean E.; Totz, Kathryn Sentman; Kaufman, Scott Barry

2010-01-01

In an experiment with 109 undergraduates, we examined the effect of mood, cognitive style, and cognitive ability on implicit learning in the Artificial Grammar (AG) and Serial Reaction Time (SRT) tasks. Negative mood facilitated AG learning, but had no significant effect on SRT learning. Rational cognitive style predicted greater learning on both…

Self-organizing high-order cognitive functions in artificial agents: implications for possible prefrontal cortex mechanisms.

PubMed

Maniadakis, Michail; Trahanias, Panos; Tani, Jun

2012-09-01

In our daily life, we often adapt plans and behaviors according to dynamically changing world circumstances, selecting activities that make us feel more confident about the future. In this adaptation, the prefrontal cortex (PFC) is believed to have an important role, applying executive control on other cognitive processes to achieve context switching and confidence monitoring; however, many questions remain open regarding the nature of neural processes supporting executive control. The current work explores possible mechanisms of this high-order cognitive function, transferring executing control in the domain of artificial cognitive systems. In particular, we study the self-organization of artificial neural networks accomplishing a robotic rule-switching task analogous to the Wisconsin Card Sorting Test. The obtained results show that behavioral rules may be encoded in neuro-dynamic attractors, with their geometric arrangements in phase space affecting the shaping of confidence. Analysis of the emergent dynamical structures suggests possible explanations of the interactions of high-level and low-level processes in the real brain. Copyright © 2012 Elsevier Ltd. All rights reserved.

Little AI: Playing a constructivist robot

NASA Astrophysics Data System (ADS)

Georgeon, Olivier L.

Little AI is a pedagogical game aimed at presenting the founding concepts of constructivist learning and developmental Artificial Intelligence. It primarily targets students in computer science and cognitive science but it can also interest the general public curious about these topics. It requires no particular scientific background; even children can find it entertaining. Professors can use it as a pedagogical resource in class or in online courses. The player presses buttons to control a simulated "baby robot". The player cannot see the robot and its environment, and initially ignores the effects of the commands. The only information received by the player is feedback from the player's commands. The player must learn, at the same time, the functioning of the robot's body and the structure of the environment from patterns in the stream of commands and feedback. We argue that this situation is analogous to how infants engage in early-stage developmental learning (e.g., Piaget (1937), [1]).

Student Science Training Program in Mathematics, Physics and Computer Science. Final Report to the National Science Foundation. Artificial Intelligence Memo No. 393.

ERIC Educational Resources Information Center

Abelson, Harold; diSessa, Andy

During the summer of 1976, the MIT Artificial Intelligence Laboratory sponsored a Student Science Training Program in Mathematics, Physics, and Computer Science for high ability secondary school students. This report describes, in some detail, the style of the program, the curriculum and the projects the students under-took. It is hoped that this…

Constructing Artificial Rock Outcrops as Tools for Fostering Earth and Environmental Science Thinking

NASA Astrophysics Data System (ADS)

Totten, I. M.; Hall, F.; Buxton, C.

2004-12-01

The Earth and Environmental Science Education Group at the University of New Orleans has created an innovative visualization teaching tool. Through funding made available by the National Science Foundation a 12'x10'x5' artificial rock outcrop was fabricated at the University of New Orleans. An accompanying curriculum, which includes a series of artificial rock outcrop labs, was also created for the outcrop. The labs incorporated fundamental concepts from the geosciences and the field of science education. The overarching philosophy behind the unity of the content knowledge and the pedagogy was to develop a more inclusive and deliberate teaching approach that utilized strategies known to enhance student learning in the sciences. The artificial outcrop lab series emphasized the following geoscience topics: relative dating, rock movement, and depositional environments. The series also integrated pedagogical ideas such as inquiry-based learning, conceptual mapping, constructivist teaching, pattern recognition, and contextualized knowledge development. Each component of the curriculum was purposefully designed to address what the body of research in science education reveals as critical to science teaching and learning. After developing the artificial rock outcrop curriculum a pilot study was done with 40 pre-service elementary education undergraduates. In the pilot study students completed the following assessments: three outcrop labs, journal reflections for each lab, pre/post attitude surveys, group video-recordings, and preconception and final interviews. Data from these assessments were analyzed using qualitative and quantitative methodologies. The following conclusions were revealed from the data: student's attitudes towards learning earth science increased after working with the artificial rock outcrop, students conceptual understanding of the concepts were clearer after working with the outcrop, students were able to answer multifaceted, higher order questions as a result of working with the outcrop, and students confidence in their abilities to think scientifically improved after their experience with the outcrop. The artificial rock outcrop has consequently been incorporated into several courses that have large enrollments from the following student populations: pre-service elementary education majors, undergraduate non-science majors, geology majors, and in-service MAST (Masters of Art in Science Teaching) students. Approximately, 1300 college students and 500 students in the 4th-12th grade levels from the local metropolitan school area work with the artificial rock outcrop annually. The artificial rock outcrop curriculum was a much-needed teaching tool in New Orleans considering the absence of natural rock outcrops along the entire coastal plain province.

Modeling and Evaluating Emotions Impact on Cognition

DTIC Science & Technology

2013-07-01

Causality and Responsibility Judgment in Multi-Agent Interactions: Extended abstract. 23rd International Joint Conference on Artificial Inteligence ...responsibility judgment in multi-agent interactions." Journal of Artificial Intelligence Research v44(1), 223- 273. • Morteza Dehghani, Jonathan Gratch... Artificial Intelligence (AAAI’11). Grant related invited talks: • Keynote speaker, Workshop on Empathic and Emotional Agents at the International

Application of Cognitive Science Principles: Instructional Heuristics and Mechanisms for Use.

ERIC Educational Resources Information Center

Montague, William E.

Cognitive science is briefly reviewed, and its implications for instructional design are discussed. The application of cognitive science to instruction requires knowledge of cognitive science, the subject content taught, and the system in which the instruction is imbedded. The central concept of cognitive science is mental representation--the…

Cognitive Psychology and Mathematical Thinking.

ERIC Educational Resources Information Center

Greer, Brian

1981-01-01

This review illustrates aspects of cognitive psychology relevant to the understanding of how people think mathematically. Developments in memory research, artificial intelligence, visually mediated processes, and problem-solving research are discussed. (MP)

Analysis of cognitive theories in artificial intelligence and psychology in relation to the qualitative process of emotion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Semrau, P.

The purpose of this study was to analyze selected cognitive theories in the areas of artificial intelligence (A.I.) and psychology to determine the role of emotions in the cognitive or intellectual processes. Understanding the relationship of emotions to processes of intelligence has implications for constructing theories of aesthetic response and A.I. systems in art. Psychological theories were examined that demonstrated the changing nature of the research in emotion related to cognition. The basic techniques in A.I. were reviewed and the A.I. research was analyzed to determine the process of cognition and the role of emotion. The A.I. research emphasized themore » digital, quantifiable character of the computer and associated cognitive models and programs. In conclusion, the cognitive-emotive research in psychology and the cognitive research in A.I. emphasized quantification methods over analog and qualitative characteristics required for a holistic explanation of cognition. Further A.I. research needs to examine the qualitative aspects of values, attitudes, and beliefs on influencing the creative thinking processes. Inclusion of research related to qualitative problem solving in art provides a more comprehensive base of study for examining the area of intelligence in computers.« less

Proactive learning for artificial cognitive systems

NASA Astrophysics Data System (ADS)

Lee, Soo-Young

2010-04-01

The Artificial Cognitive Systems (ACS) will be developed for human-like functions such as vision, auditory, inference, and behavior. Especially, computational models and artificial HW/SW systems will be devised for Proactive Learning (PL) and Self-Identity (SI). The PL model provides bilateral interactions between robot and unknown environment (people, other robots, cyberspace). For the situation awareness in unknown environment it is required to receive audiovisual signals and to accumulate knowledge. If the knowledge is not enough, the PL should improve by itself though internet and others. For human-oriented decision making it is also required for the robot to have self-identify and emotion. Finally, the developed models and system will be mounted on a robot for the human-robot co-existing society. The developed ACS will be tested against the new Turing Test for the situation awareness. The Test problems will consist of several video clips, and the performance of the ACSs will be compared against those of human with several levels of cognitive ability.

How can philosophy be a true cognitive science discipline?

PubMed

Bechtel, William

2010-07-01

Although philosophy has been only a minor contributor to cognitive science to date, this paper describes two projects in naturalistic philosophy of mind and one in naturalistic philosophy of science that have been pursued during the past 30 years and that can make theoretical and methodological contributions to cognitive science. First, stances on the mind-body problem (identity theory, functionalism, and heuristic identity theory) are relevant to cognitive science as it negotiates its relation to neuroscience and cognitive neuroscience. Second, analyses of mental representations address both their vehicles and their contents; new approaches to characterizing how representations have content are particularly relevant to understanding the relation of cognitive agents to their environments. Third, the recently formulated accounts of mechanistic explanation in philosophy of science both provide perspective on the explanatory project of cognitive science and may offer normative guidance to cognitive science (e.g., by providing perspective on how multiple disciplinary perspectives can be integrated in understanding a given mechanism). Copyright © 2010 Cognitive Science Society, Inc.

Human-like machines: Transparency and comprehensibility.

PubMed

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.

Generalized anxiety disorder and online intelligence: A phenomenological account of why worrying is unhelpful

PubMed Central

2011-01-01

Worrying is the central feature of generalized anxiety disorder (GAD). Many people worry from time to time, but in GAD the worrying is prolonged and difficult to control. Worrying is a specific way of coping with perceived threats and feared situations. Meanwhile, it is not considered to be a helpful coping strategy, and the phenomenological account developed in this paper aims to show why. It builds on several phenomenological notions and in particular on Michael Wheeler's application of these notions to artificial intelligence and the cognitive sciences. Wheeler emphasizes the value of 'online intelligence' as contrasted to 'offline intelligence'. I discuss and apply these concepts with respect to worrying as it occurs in GAD, suggesting that GAD patients overrate the value of detached contemplation (offline intelligence), while underrating their embodied-embedded adaptive skills (online intelligence). I argue that this phenomenological account does not only help explaining why worrying is used as a coping strategy, but also why cognitive behavioral therapy is successful in treating GAD. PMID:21539727

Generalized anxiety disorder and online intelligence: a phenomenological account of why worrying is unhelpful.

PubMed

Meynen, Gerben

2011-05-03

Worrying is the central feature of generalized anxiety disorder (GAD). Many people worry from time to time, but in GAD the worrying is prolonged and difficult to control. Worrying is a specific way of coping with perceived threats and feared situations. Meanwhile, it is not considered to be a helpful coping strategy, and the phenomenological account developed in this paper aims to show why. It builds on several phenomenological notions and in particular on Michael Wheeler's application of these notions to artificial intelligence and the cognitive sciences. Wheeler emphasizes the value of 'online intelligence' as contrasted to 'offline intelligence'. I discuss and apply these concepts with respect to worrying as it occurs in GAD, suggesting that GAD patients overrate the value of detached contemplation (offline intelligence), while underrating their embodied-embedded adaptive skills (online intelligence). I argue that this phenomenological account does not only help explaining why worrying is used as a coping strategy, but also why cognitive behavioral therapy is successful in treating GAD.

Second Language Experience Facilitates Statistical Learning of Novel Linguistic Materials.

PubMed

Potter, Christine E; Wang, Tianlin; Saffran, Jenny R

2017-04-01

Recent research has begun to explore individual differences in statistical learning, and how those differences may be related to other cognitive abilities, particularly their effects on language learning. In this research, we explored a different type of relationship between language learning and statistical learning: the possibility that learning a new language may also influence statistical learning by changing the regularities to which learners are sensitive. We tested two groups of participants, Mandarin Learners and Naïve Controls, at two time points, 6 months apart. At each time point, participants performed two different statistical learning tasks: an artificial tonal language statistical learning task and a visual statistical learning task. Only the Mandarin-learning group showed significant improvement on the linguistic task, whereas both groups improved equally on the visual task. These results support the view that there are multiple influences on statistical learning. Domain-relevant experiences may affect the regularities that learners can discover when presented with novel stimuli. Copyright © 2016 Cognitive Science Society, Inc.

Why cognitive science needs philosophy and vice versa.

PubMed

Thagard, Paul

2009-04-01

Contrary to common views that philosophy is extraneous to cognitive science, this paper argues that philosophy has a crucial role to play in cognitive science with respect to generality and normativity. General questions include the nature of theories and explanations, the role of computer simulation in cognitive theorizing, and the relations among the different fields of cognitive science. Normative questions include whether human thinking should be Bayesian, whether decision making should maximize expected utility, and how norms should be established. These kinds of general and normative questions make philosophical reflection an important part of progress in cognitive science. Philosophy operates best, however, not with a priori reasoning or conceptual analysis, but rather with empirically informed reflection on a wide range of findings in cognitive science. Copyright © 2009 Cognitive Science Society, Inc.

Psychology in cognitive science: 1978-2038.

PubMed

Gentner, Dedre

2010-07-01

This paper considers the past and future of Psychology within Cognitive Science. In the history section, I focus on three questions: (a) how has the position of Psychology evolved within Cognitive Science, relative to the other disciplines that make up Cognitive Science; (b) how have particular Cognitive Science areas within Psychology waxed or waned; and (c) what have we gained and lost. After discussing what's happened since the late 1970s, when the Society and the journal began, I speculate about where the field is going. Copyright © 2010 Cognitive Science Society, Inc.

A Modular Artificial Intelligence Inference Engine System (MAIS) for support of on orbit experiments

NASA Technical Reports Server (NTRS)

Hancock, Thomas M., III

1994-01-01

This paper describes a Modular Artificial Intelligence Inference Engine System (MAIS) support tool that would provide health and status monitoring, cognitive replanning, analysis and support of on-orbit Space Station, Spacelab experiments and systems.

Cognitive science contributions to decision science.

PubMed

Busemeyer, Jerome R

2015-02-01

This article briefly reviews the history and interplay between decision theory, behavioral decision-making research, and cognitive psychology. The review reveals the increasingly important impact that psychology and cognitive science have on decision science. One of the main contributions of cognitive science to decision science is the development of dynamic models that describe the cognitive processes that underlay the evolution of preferences during deliberation phase of making a decision. Copyright © 2014 Elsevier B.V. All rights reserved.

Causality

NASA Astrophysics Data System (ADS)

Pearl, Judea

2000-03-01

Written by one of the pre-eminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable.

Should the study of Homo sapiens be part of cognitive science?

PubMed

Clark Barrett, H; Stich, Stephen; Laurence, Stephen

2012-07-01

Beller, Bender, and Medin argue that a reconciliation between anthropology and cognitive science seems unlikely. We disagree. In our view, Beller et al.'s view of the scope of what anthropology can offer cognitive science is too narrow. In focusing on anthropology's role in elucidating cultural particulars, they downplay the fact that anthropology can reveal both variation and universals in human cognition, and is in a unique position to do so relative to the other subfields of cognitive science. Indeed, without cross-cultural research, the universality of any aspect of human cognition cannot truly be established. Therefore, if the goal of cognitive science is to understand the cognitive capacities of our species as a whole, then it cannot do without anthropology. We briefly review a growing body of anthropological work aimed at answering questions about human cognition and offer suggestions for future work. Copyright © 2012 Cognitive Science Society, Inc.

Cognon Neural Model Software Verification and Hardware Implementation Design

NASA Astrophysics Data System (ADS)

Haro Negre, Pau

Little is known yet about how the brain can recognize arbitrary sensory patterns within milliseconds using neural spikes to communicate information between neurons. In a typical brain there are several layers of neurons, with each neuron axon connecting to ˜104 synapses of neurons in an adjacent layer. The information necessary for cognition is contained in theses synapses, which strengthen during the learning phase in response to newly presented spike patterns. Continuing on the model proposed in "Models for Neural Spike Computation and Cognition" by David H. Staelin and Carl H. Staelin, this study seeks to understand cognition from an information theoretic perspective and develop potential models for artificial implementation of cognition based on neuronal models. To do so we focus on the mathematical properties and limitations of spike-based cognition consistent with existing neurological observations. We validate the cognon model through software simulation and develop concepts for an optical hardware implementation of a network of artificial neural cognons.

The emergence of cognitive hearing science.

PubMed

Arlinger, Stig; Lunner, Thomas; Lyxell, Björn; Pichora-Fuller, M Kathleen

2009-10-01

Cognitive Hearing Science or Auditory Cognitive Science is an emerging field of interdisciplinary research concerning the interactions between hearing and cognition. It follows a trend over the last half century for interdisciplinary fields to develop, beginning with Neuroscience, then Cognitive Science, then Cognitive Neuroscience, and then Cognitive Vision Science. A common theme is that an interdisciplinary approach is necessary to understand complex human behaviors, to develop technologies incorporating knowledge of these behaviors, and to find solutions for individuals with impairments that undermine typical behaviors. Accordingly, researchers in traditional academic disciplines, such as Psychology, Physiology, Linguistics, Philosophy, Anthropology, and Sociology benefit from collaborations with each other, and with researchers in Computer Science and Engineering working on the design of technologies, and with health professionals working with individuals who have impairments. The factors that triggered the emergence of Cognitive Hearing Science include the maturation of the component disciplines of Hearing Science and Cognitive Science, new opportunities to use complex digital signal-processing to design technologies suited to performance in challenging everyday environments, and increasing social imperatives to help people whose communication problems span hearing and cognition. Cognitive Hearing Science is illustrated in research on three general topics: (1) language processing in challenging listening conditions; (2) use of auditory communication technologies or the visual modality to boost performance; (3) changes in performance with development, aging, and rehabilitative training. Future directions for modeling and the translation of research into practice are suggested.

The Theory of Multiple Intelligences: A Case of Missing Cognitive Matter.

ERIC Educational Resources Information Center

Allix, Nicholas M.

2000-01-01

Argues that although Gardner's conception of human cognition, characterized by a set of multiple and distinct cognitive capabilities, is an advance over the narrow conception of IQ, it runs into fundamental difficulties of a methodological kind and is based on a discredited empiricist theory of knowledge which work with artificial neural networks…

Biological and artificial cognition: what can we learn about mechanisms by modelling physical cognition problems using artificial intelligence planning techniques?

PubMed Central

Chappell, Jackie; Hawes, Nick

2012-01-01

Do we fully understand the structure of the problems we present to our subjects in experiments on animal cognition, and the information required to solve them? While we currently have a good understanding of the behavioural and neurobiological mechanisms underlying associative learning processes, we understand much less about the mechanisms underlying more complex forms of cognition in animals. In this study, we present a proposal for a new way of thinking about animal cognition experiments. We describe a process in which a physical cognition task domain can be decomposed into its component parts, and models constructed to represent both the causal events of the domain and the information available to the agent. We then implement a simple set of models, using the planning language MAPL within the MAPSIM simulation environment, and applying it to a puzzle tube task previously presented to orangutans. We discuss the results of the models and compare them with the results from the experiments with orangutans, describing the advantages of this approach, and the ways in which it could be extended. PMID:22927571

Biological and artificial cognition: what can we learn about mechanisms by modelling physical cognition problems using artificial intelligence planning techniques?

PubMed

Chappell, Jackie; Hawes, Nick

2012-10-05

Do we fully understand the structure of the problems we present to our subjects in experiments on animal cognition, and the information required to solve them? While we currently have a good understanding of the behavioural and neurobiological mechanisms underlying associative learning processes, we understand much less about the mechanisms underlying more complex forms of cognition in animals. In this study, we present a proposal for a new way of thinking about animal cognition experiments. We describe a process in which a physical cognition task domain can be decomposed into its component parts, and models constructed to represent both the causal events of the domain and the information available to the agent. We then implement a simple set of models, using the planning language MAPL within the MAPSIM simulation environment, and applying it to a puzzle tube task previously presented to orangutans. We discuss the results of the models and compare them with the results from the experiments with orangutans, describing the advantages of this approach, and the ways in which it could be extended.

The P600 in Implicit Artificial Grammar Learning.

PubMed

Silva, Susana; Folia, Vasiliki; Hagoort, Peter; Petersson, Karl Magnus

2017-01-01

The suitability of the artificial grammar learning (AGL) paradigm to capture relevant aspects of the acquisition of linguistic structures has been empirically tested in a number of EEG studies. Some have shown a syntax-related P600 component, but it has not been ruled out that the AGL P600 effect is a response to surface features (e.g., subsequence familiarity) rather than the underlying syntax structure. Therefore, in this study, we controlled for the surface characteristics of the test sequences (associative chunk strength) and recorded the EEG before (baseline preference classification) and after (preference and grammaticality classification) exposure to a grammar. After exposure, a typical, centroparietal P600 effect was elicited by grammatical violations and not by unfamiliar subsequences, suggesting that the AGL P600 effect signals a response to structural irregularities. Moreover, preference and grammaticality classification showed a qualitatively similar ERP profile, strengthening the idea that the implicit structural mere-exposure paradigm in combination with preference classification is a suitable alternative to the traditional grammaticality classification test. Copyright © 2016 Cognitive Science Society, Inc.

Cognitive and artificial representations in handwriting recognition

NASA Astrophysics Data System (ADS)

Lenaghan, Andrew P.; Malyan, Ron

1996-03-01

Both cognitive processes and artificial recognition systems may be characterized by the forms of representation they build and manipulate. This paper looks at how handwriting is represented in current recognition systems and the psychological evidence for its representation in the cognitive processes responsible for reading. Empirical psychological work on feature extraction in early visual processing is surveyed to show that a sound psychological basis for feature extraction exists and to describe the features this approach leads to. The first stage of the development of an architecture for a handwriting recognition system which has been strongly influenced by the psychological evidence for the cognitive processes and representations used in early visual processing, is reported. This architecture builds a number of parallel low level feature maps from raw data. These feature maps are thresholded and a region labeling algorithm is used to generate sets of features. Fuzzy logic is used to quantify the uncertainty in the presence of individual features.

Strategic Computing. New-Generation Computing Technology: A Strategic Plan for Its Development and Application to Critical Problems in Defense

DTIC Science & Technology

1983-10-28

Computing. By seizing an opportunity to leverage recent advances in artificial intelligence, computer science, and microelectronics, the Agency plans...occurred in many separated areas of artificial intelligence, computer science, and microelectronics. Advances in "expert system" technology now...and expert knowledge o Advances in Artificial Intelligence: Mechanization of speech recognition, vision, and natural language understanding. o

Footstep Planning on Uneven Terrain with Mixed-Integer Convex Optimization

DTIC Science & Technology

2014-08-01

ORGANIZATION NAME(S) AND ADDRESS(ES) Massachusetts Institute of Technology,Computer Science and Artificial Intellegence Laboratory,Cambridge,MA,02139...the MIT Energy Initiative, MIT CSAIL, and the DARPA Robotics Challenge. 1Robin Deits is with the Computer Science and Artificial Intelligence Laboratory

Artificial Life Art, Creativity, and Techno-hybridization (editor's introduction).

PubMed

Dorin, Alan

2015-01-01

Artists and engineers have devised lifelike technology for millennia. Their ingenious devices have often prompted inquiry into our preferences, prejudices, and beliefs about living systems, especially regarding their origins, status, constitution, and behavior. A recurring fabrication technique is shared across artificial life art, science, and engineering. This involves aggregating representations or re-creations of familiar biological parts-techno-hybridization-but the motives of practitioners may differ markedly. This article, and the special issue it introduces, explores how ground familiar to contemporary artificial life science and engineering has been assessed and interpreted in parallel by (a) artists and (b) theorists studying creativity explicitly. This activity offers thoughtful, alternative perspectives on artificial life science and engineering, highlighting and sometimes undermining the fields' underlying assumptions, or exposing avenues that are yet to be explored outside of art. Additionally, art has the potential to engage the general public, supporting and exploring the findings of scientific research and engineering. This adds considerably to the maturity of a culture tackling the issues the discipline of artificial life raises.

Cognitive methodology for forecasting oil and gas industry using pattern-based neural information technologies

NASA Astrophysics Data System (ADS)

Gafurov, O.; Gafurov, D.; Syryamkin, V.

2018-05-01

The paper analyses a field of computer science formed at the intersection of such areas of natural science as artificial intelligence, mathematical statistics, and database theory, which is referred to as "Data Mining" (discovery of knowledge in data). The theory of neural networks is applied along with classical methods of mathematical analysis and numerical simulation. The paper describes the technique protected by the patent of the Russian Federation for the invention “A Method for Determining Location of Production Wells during the Development of Hydrocarbon Fields” [1–3] and implemented using the geoinformation system NeuroInformGeo. There are no analogues in domestic and international practice. The paper gives an example of comparing the forecast of the oil reservoir quality made by the geophysicist interpreter using standard methods and the forecast of the oil reservoir quality made using this technology. The technical result achieved shows the increase of efficiency, effectiveness, and ecological compatibility of development of mineral deposits and discovery of a new oil deposit.

Cognitive neuroscience: the troubled marriage of cognitive science and neuroscience.

PubMed

Cooper, Richard P; Shallice, Tim

2010-07-01

We discuss the development of cognitive neuroscience in terms of the tension between the greater sophistication in cognitive concepts and methods of the cognitive sciences and the increasing power of more standard biological approaches to understanding brain structure and function. There have been major technological developments in brain imaging and advances in simulation, but there have also been shifts in emphasis, with topics such as thinking, consciousness, and social cognition becoming fashionable within the brain sciences. The discipline has great promise in terms of applications to mental health and education, provided it does not abandon the cognitive perspective and succumb to reductionism. Copyright © 2010 Cognitive Science Society, Inc.

How Meaning Is Born.

ERIC Educational Resources Information Center

Hunt, Madgie Mae

In an effort to create a multilevel, interactive, and hypothesis-based model of the reading comprehension process that bridges interdisciplinary gaps in the theory of learning, this report focuses on descriptions of cognitive processes developed in the fields of cognitive psychology, artificial intelligence, sociolinguistics, linguistics, and…

Using an Artificial Rock Outcrop to Teach Geology

ERIC Educational Resources Information Center

Totten, Iris

2005-01-01

Teaching Earth science without exposure to rock outcrops limits students depth of understanding of Earth's processes, limits the concept of scale from their spatial visualization imaging, and distorts their perception of geologic time (Totten 2003). Through a grant funded by the National Science Foundation, an artificial rock outcrop was…

Twelve Issues for Cognitive Science.

ERIC Educational Resources Information Center

Norman, Donald A.

Cognitive science is a science of intelligence, of knowledge and its uses. Research is psychological theory follows four major themes: Perception, Attention, Memory, and Performance. Only when the range of cognitive mechanisms and functions is known, can possible theoretical approaches characterizing human thought and cognition be distinguished.…

When physics is not "just physics": complexity science invites new measurement frames for exploring the physics of cognitive and biological development.

PubMed

Kelty-Stephen, Damian; Dixon, James A

2012-01-01

The neurobiological sciences have struggled to resolve the physical foundations for biological and cognitive phenomena with a suspicion that biological and cognitive systems, capable of exhibiting and contributing to structure within themselves and through their contexts, are fundamentally distinct or autonomous from purely physical systems. Complexity science offers new physics-based approaches to explaining biological and cognitive phenomena. In response to controversy over whether complexity science might seek to "explain away" biology and cognition as "just physics," we propose that complexity science serves as an application of recent advances in physics to phenomena in biology and cognition without reducing or undermining the integrity of the phenomena to be explained. We highlight that physics is, like the neurobiological sciences, an evolving field and that the threat of reduction is overstated. We propose that distinctions between biological and cognitive systems from physical systems are pretheoretical and thus optional. We review our own work applying insights from post-classical physics regarding turbulence and fractal fluctuations to the problems of developing cognitive structure. Far from hoping to reduce biology and cognition to "nothing but" physics, we present our view that complexity science offers new explanatory frameworks for considering physical foundations of biological and cognitive phenomena.

Toward physics of the mind: Concepts, emotions, consciousness, and symbols

NASA Astrophysics Data System (ADS)

Perlovsky, Leonid I.

2006-03-01

Mathematical approaches to modeling the mind since the 1950s are reviewed, including artificial intelligence, pattern recognition, and neural networks. I analyze difficulties faced by these algorithms and neural networks and relate them to the fundamental inconsistency of logic discovered by Gödel. Mathematical discussions are related to those in neurobiology, psychology, cognitive science, and philosophy. Higher cognitive functions are reviewed including concepts, emotions, instincts, understanding, imagination, intuition, consciousness. Then, I describe a mathematical formulation, unifying the mind mechanisms in a psychologically and neuro-biologically plausible system. A mechanism of the knowledge instinct drives our understanding of the world and serves as a foundation for higher cognitive functions. This mechanism relates aesthetic emotions and perception of beauty to “everyday” functioning of the mind. The article reviews mechanisms of human symbolic ability. I touch on future directions: joint evolution of the mind, language, consciousness, and cultures; mechanisms of differentiation and synthesis; a manifold of aesthetic emotions in music and differentiated instinct for knowledge. I concentrate on elucidating the first principles; review aspects of the theory that have been proven in laboratory research, relationships between the mind and brain; discuss unsolved problems, and outline a number of theoretical predictions, which will have to be tested in future mathematical simulations and neuro-biological research.

Iconicity and the Emergence of Combinatorial Structure in Language.

PubMed

Verhoef, Tessa; Kirby, Simon; de Boer, Bart

2016-11-01

In language, recombination of a discrete set of meaningless building blocks forms an unlimited set of possible utterances. How such combinatorial structure emerged in the evolution of human language is increasingly being studied. It has been shown that it can emerge when languages culturally evolve and adapt to human cognitive biases. How the emergence of combinatorial structure interacts with the existence of holistic iconic form-meaning mappings in a language is still unknown. The experiment presented in this paper studies the role of iconicity and human cognitive learning biases in the emergence of combinatorial structure in artificial whistled languages. Participants learned and reproduced whistled words for novel objects with the use of a slide whistle. Their reproductions were used as input for the next participant, to create transmission chains and simulate cultural transmission. Two conditions were studied: one in which the persistence of iconic form-meaning mappings was possible and one in which this was experimentally made impossible. In both conditions, cultural transmission caused the whistled languages to become more learnable and more structured, but this process was slightly delayed in the first condition. Our findings help to gain insight into when and how words may lose their iconic origins when they become part of an organized linguistic system. Copyright © 2015 Cognitive Science Society, Inc.

Editor's Introduction and Review: Coordination and Context in Cognitive Science.

PubMed

Kello, Christopher T

2018-01-01

The role of coordination in cognitive science has been on the rise in recent years, in terms of coordination among neurons, coordination among sensory and motor systems, and coordination among individuals. Research has shown that coordination patterns corresponding to cognitive activities depend on the various contexts in which the underlying interactions are situated. The present issue of Topics in Cognitive Science centers on studies of coordination that address the role of context in shaping or interpreting dynamical patterns of human behavior. This introductory article reviews some of the prior literature leading up to current and future research on coordination and context in cognitive science. Copyright © 2017 Cognitive Science Society, Inc.

Cognitive Enhancement and Education

ERIC Educational Resources Information Center

Buchanan, Allen

2011-01-01

Cognitive enhancement--augmenting normal cognitive capacities--is not new. Literacy, numeracy, computers, and the practices of science are all cognitive enhancements. Science is now making new cognitive enhancements possible. Biomedical cognitive enhancements (BCEs) include the administration of drugs, implants of genetically engineered or…

Predicting Item Difficulty in a Reading Comprehension Test with an Artificial Neural Network.

ERIC Educational Resources Information Center

Perkins, Kyle; And Others

1995-01-01

This article reports the results of using a three-layer back propagation artificial neural network to predict item difficulty in a reading comprehension test. Three classes of variables were examined: text structure, propositional analysis, and cognitive demand. Results demonstrate that the networks can consistently predict item difficulty. (JL)

Patterns recognition of electric brain activity using artificial neural networks

NASA Astrophysics Data System (ADS)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

Conditions for quantum interference in cognitive sciences.

PubMed

Yukalov, Vyacheslav I; Sornette, Didier

2014-01-01

We present a general classification of the conditions under which cognitive science, concerned, e.g. with decision making, requires the use of quantum theoretical notions. The analysis is done in the frame of the mathematical approach based on the theory of quantum measurements. We stress that quantum effects in cognition can arise only when decisions are made under uncertainty. Conditions for the appearance of quantum interference in cognitive sciences and the conditions when interference cannot arise are formulated. Copyright © 2013 Cognitive Science Society, Inc.

Heuristic thinking makes a chemist smart.

PubMed

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.

Learning the Hidden Structure of Speech.

DTIC Science & Technology

1987-02-01

STRUCTURE OF SPEECH J. L. Elman and D. Zipser February 1987 ICS Report 8701 COGNITIVE SCIENCE ,a - ~QIt b’eez INSTITUTE FOR COGNITIVE SCIENCE...Zipser February 1987 ICS Report 8701 *0:-.:-! ,%. ., Jeffrey L. Elman David Zipser Department of Linguistics Institute for Cognitive Science...any purpose of the United States Government. Requests for reprints should be sent to the Institute for Cognitive Science, C-015; University of

Characteristics of High School Students' and Science Teachers' Cognitive Frame about Effective Teaching Method for High School Science Subject

NASA Astrophysics Data System (ADS)

Chung, Duk Ho; Park, Kyeong-Jin; Cho, Kyu Seong

2016-04-01

We investigated the cognitive frame of high school students and inservice high school science teachers about effective teaching method, and we also explored how they understood about the teaching methods suggested by the 2009 revised Science Curriculum. Data were collected from 275 high school science teachers and 275 high school students. We analyzed data in terms of the words and the cognitive frame using the Semantic Network Analysis. The results were as follows. First, the teachers perceived that an activity oriented class was the effective science class that helped improve students'' problem-solving abilities and their inquiry skills. The students had the cognitive frame that their teacher had to present relevant and enough teaching materials to students, and that they should also receive assistance from teachers in science class to better prepare for college entrance exam. Second, both students and teachers retained the cognitive frame about the efficient science class that was not reflected 2009 revised Science Curriculum exactly. Especially, neither groups connected the elements of ''convergence'' as well as ''integration'' embedded across science subject areas to their cognitive frame nor cognized the fact that many science learning contents were closed related to one another. Therefore, various professional development opportunities should be offered so that teachers succinctly comprehend the essential features and the intents of the 2009 revised Science Curriculum and thereby implement it in their science lessons effectively. Keywords : semantic network analysis, cognitive frame, teaching method, science lesson

Improving Team Performance: Proceedings of the Rand Team Performance Workshop.

DTIC Science & Technology

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

Survey of Artificial Intelligence and Expert Systems in Library and Information Science Literature.

ERIC Educational Resources Information Center

Hsieh, Cynthia C.; Hall, Wendy

1989-01-01

Examines the definition and history of artificial intelligence (AI) and investigates the body of literature on AI found in "Library Literature" and "Library and Information Science Abstracts." The results reported include the number of articles by year and per journal, and the percentage of articles dealing with library…

Explaining how the mind works: on the relation between cognitive science and philosophy.

PubMed

Trigg, Jonathan; Kalish, Michael

2011-04-01

In this paper, we argue that under certain prevalent interpretations of the nature and aims of cognitive science, theories of cognition generate a forced choice between a conception of cognition which depends on the possibility of a private language, and a conception of cognition which depends on mereological confusions. We argue, further, that this should not pose a fundamental problem for cognitive scientists since a plausible interpretation of the nature and aims of cognitive science is available that does not generate this forced choice. The crucial difference between these interpretations is that on the one hand the aim of theories of cognition is to tell us what thinking (etc.) is, and on the other it is to tell us what is causally necessary if an intelligent creature is to be able to think. Our argument draws heavily on a Wittgensteinian conception of philosophy in which no philosophical theory can explain what thinking, perceiving, remembering, etc. are, either. The positive, strictly therapeutic, purpose of a philosophy of cognitive science should be to show that, since the traditional problems which constitute the philosophy of mind are chimerical, there is nothing for philosophical theorizing in cognitive science to achieve. Copyright © 2011 Cognitive Science Society, Inc.

Association between MRI structural features and cognitive measures in pediatric multiple sclerosis

NASA Astrophysics Data System (ADS)

Amoroso, N.; Bellotti, R.; Fanizzi, A.; Lombardi, A.; Monaco, A.; Liguori, M.; Margari, L.; Simone, M.; Viterbo, R. G.; Tangaro, S.

2017-09-01

Multiple sclerosis (MS) is an inflammatory and demyelinating disease associated with neurodegenerative processes that lead to brain structural changes. The disease affects mostly young adults, but 3-5% of cases has a pediatric onset (POMS). Magnetic Resonance Imaging (MRI) is generally used for diagnosis and follow-up in MS patients, however the most common MRI measures (e.g. new or enlarging T2-weighted lesions, T1-weighted gadolinium- enhancing lesions) have often failed as surrogate markers of MS disability and progression. MS is clinically heterogenous with symptoms that can include both physical changes (such as visual loss or walking difficulties) and cognitive impairment. 30-50% of POMS experience prominent cognitive dysfunction. In order to investigate the association between cognitive measures and brain morphometry, in this work we present a fully automated pipeline for processing and analyzing MRI brain scans. Relevant anatomical structures are segmented with FreeSurfer; besides, statistical features are computed. Thus, we describe the data referred to 12 patients with early POMS (mean age at MRI: 15.5 +/- 2.7 years) with a set of 181 structural features. The major cognitive abilities measured are verbal and visuo-spatial learning, expressive language and complex attention. Data was collected at the Department of Basic Sciences, Neurosciences and Sense Organs, University of Bari, and exploring different abilities like the verbal and visuo-spatial learning, expressive language and complex attention. Different regression models and parameter configurations are explored to assess the robustness of the results, in particular Generalized Linear Models, Bayes Regression, Random Forests, Support Vector Regression and Artificial Neural Networks are discussed.

The Hospital of the Future. Megatrends, Driving Forces, Barriers to Implementation, Overarching Perspectives, Major Trends into the Future, Implications for TATRC And Specific Recommendations for Action

DTIC Science & Technology

2008-10-01

Healthcare Systems Will Be Those That Work With Data/Info In New Ways • Artificial Intelligence Will Come to the Fore o Effectively Acquire...Education • Artificial Intelligence Will Assist in o History and Physical Examination o Imaging Selection via algorithms o Test Selection via algorithms...medical language into a simulation model based upon artificial intelligence , and • the content verification and validation of the cognitive

AAAIC '88 - Aerospace Applications of Artificial Intelligence; Proceedings of the Fourth Annual Conference, Dayton, OH, Oct. 25-27, 1988. Volumes 1 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, J.R.; Netrologic, Inc., San Diego, CA)

1988-01-01

Topics presented include integrating neural networks and expert systems, neural networks and signal processing, machine learning, cognition and avionics applications, artificial intelligence and man-machine interface issues, real time expert systems, artificial intelligence, and engineering applications. Also considered are advanced problem solving techniques, combinational optimization for scheduling and resource control, data fusion/sensor fusion, back propagation with momentum, shared weights and recurrency, automatic target recognition, cybernetics, optical neural networks.

Cognitive and Neural Sciences Division 1991 Programs

DTIC Science & Technology

1991-08-01

FUNDING NUMBERS Cognitive and Neural Sciences Division 1991 Programs PE 61153N 6. AUTHOR(S) Edited by Willard S. Vaughan 7. PERFORMING ORGANIZATION...NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER Office of Naval Research 0CNR !1491-19 Cognitive and Neural Sciences Division Code 1142...NOTES iN This is a compilation of abstracts representing R&D sponsored by the ONR Cognitive and Neural Sciences Division. 12a. DISTRIBUTION

Using reinforcement learning to examine dynamic attention allocation during reading.

PubMed

Liu, Yanping; Reichle, Erik D; Gao, Ding-Guo

2013-01-01

A fundamental question in reading research concerns whether attention is allocated strictly serially, supporting lexical processing of one word at a time, or in parallel, supporting concurrent lexical processing of two or more words (Reichle, Liversedge, Pollatsek, & Rayner, 2009). The origins of this debate are reviewed. We then report three simulations to address this question using artificial reading agents (Liu & Reichle, 2010; Reichle & Laurent, 2006) that learn to dynamically allocate attention to 1-4 words to "read" as efficiently as possible. These simulation results indicate that the agents strongly preferred serial word processing, although they occasionally attended to more than one word concurrently. The reason for this preference is discussed, along with implications for the debate about how humans allocate attention during reading. Copyright © 2013 Cognitive Science Society, Inc.

Investigation of the Relationships Between Personality Types of Eighth-Grade Science Students and Cognitive Preference Orientation.

ERIC Educational Resources Information Center

Novak, John Anthony

This study investigated the relationship among personality types, cognitive preference orientation, science achievement, intelligence, attitudes toward science and scientists, sex, and geographic area of eighth-grade science students using the following four instruments: (1) Myers-Briggs Type Indication (MBTI); (2) Cognitive Preference Examination…

Learning of pitch and time structures in an artificial grammar setting.

PubMed

Prince, Jon B; Stevens, Catherine J; Jones, Mari Riess; Tillmann, Barbara

2018-04-12

Despite the empirical evidence for the power of the cognitive capacity of implicit learning of structures and regularities in several modalities and materials, it remains controversial whether implicit learning extends to the learning of temporal structures and regularities. We investigated whether (a) an artificial grammar can be learned equally well when expressed in duration sequences as when expressed in pitch sequences, (b) learning of the artificial grammar in either duration or pitch (as the primary dimension) sequences can be influenced by the properties of the secondary dimension (invariant vs. randomized), and (c) learning can be boosted when the artificial grammar is expressed in both pitch and duration. After an exposure phase with grammatical sequences, learning in a subsequent test phase was assessed in a grammaticality judgment task. Participants in both the pitch and duration conditions showed incidental (not fully implicit) learning of the artificial grammar when the secondary dimension was invariant, but randomizing the pitch sequence prevented learning of the artificial grammar in duration sequences. Expressing the artificial grammar in both pitch and duration resulted in disproportionately better performance, suggesting an interaction between the learning of pitch and temporal structure. The findings are relevant to research investigating the learning of temporal structures and the learning of structures presented simultaneously in 2 dimensions (e.g., space and time, space and objects). By investigating learning, the findings provide further insight into the potential specificity of pitch and time processing, and their integrated versus independent processing, as previously debated in music cognition research. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Novelty Detection in and Between Different Modalities

NASA Astrophysics Data System (ADS)

Veflingstad, Henning; Yildirim, Sule

2008-01-01

Our general aim is to reflect the advances in artificial intelligence and cognitive science fields to space exploration studies such that next generation space rovers can benefit from these advances. We believe next generation space rovers can benefit from the studies related to employing conceptual representations in generating structured thought. This way, rovers need not be equipped with all necessary steps of an action plan to execute in space exploration but they can autonomously form representations of their world and reason on them to make intelligent decision. As part of this approach, autonomous novelty detection is an important feature of next generation space rovers. This feature allows a rover to make further decisions about exploring a rock sample more closely or not and on its own. This way, a rover will use less of its time for communication between the earth and itself and more of its time for achieving its assigned tasks in space. In this paper, we propose an artificial neural network based novelty detection mechanism that next generation space rovers can employ as part of their intelligence. We also present an implementation of such a mechanism and present its reliability in detecting novelty.

Lexical and sublexical units in speech perception.

PubMed

Giroux, Ibrahima; Rey, Arnaud

2009-03-01

Saffran, Newport, and Aslin (1996a) found that human infants are sensitive to statistical regularities corresponding to lexical units when hearing an artificial spoken language. Two sorts of segmentation strategies have been proposed to account for this early word-segmentation ability: bracketing strategies, in which infants are assumed to insert boundaries into continuous speech, and clustering strategies, in which infants are assumed to group certain speech sequences together into units (Swingley, 2005). In the present study, we test the predictions of two computational models instantiating each of these strategies i.e., Serial Recurrent Networks: Elman, 1990; and Parser: Perruchet & Vinter, 1998 in an experiment where we compare the lexical and sublexical recognition performance of adults after hearing 2 or 10 min of an artificial spoken language. The results are consistent with Parser's predictions and the clustering approach, showing that performance on words is better than performance on part-words only after 10 min. This result suggests that word segmentation abilities are not merely due to stronger associations between sublexical units but to the emergence of stronger lexical representations during the development of speech perception processes. Copyright © 2009, Cognitive Science Society, Inc.

Simulation of a Schema Theory-Based Knowledge Delivery System for Scientists.

ERIC Educational Resources Information Center

Vaughan, W. S., Jr.; Mavor, Anne S.

A future, automated, interactive, knowledge delivery system for use by researchers was tested using a manual cognitive model. Conceptualized from schema/frame/script theories in cognitive psychology and artificial intelligence, this hypothetical system was simulated by two psychologists who interacted with four researchers in microbiology to…

Carnegie Learning Curricula and Cognitive Tutor[R] Software. What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2010

2010-01-01

The combination of "Carnegie Learning Curricula and Cognitive Tutor[R] Software" merges algebra textbooks with interactive software developed around an artificial intelligence model that identifies strengths and weaknesses in an individual student's mastery of mathematical concepts. The software customizes prompts to focus on areas in…

Cognitive Tutor[R] Algebra I. What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2009

2009-01-01

The "Cognitive Tutor[R] Algebra I" curriculum, published by Carnegie Learning, is an approach that combines algebra textbooks with interactive software. The software is developed around an artificial intelligence model that identifies strengths and weaknesses in each individual student's mastery of mathematical concepts. It then customizes prompts…

Selective Attention and Control of Action: Comparative Psychology of an Artificial, Evolved Agent and People

ERIC Educational Resources Information Center

Ward, Robert; Ward, Ronnie

2008-01-01

This study examined the selective attention abilities of a simple, artificial, evolved agent and considered implications of the agent's performance for theories of selective attention and action. The agent processed two targets in continuous time, catching one and then the other. This task required many cognitive operations, including prioritizing…

Science Education for Women: Situated Cognition, Feminist Standpoint Theory, and the Status of Women in Science

ERIC Educational Resources Information Center

Pinnick, Cassandra L.

2008-01-01

This paper examines the relation between situated cognition theory in science education, and feminist standpoint theory in philosophy of science. It shows that situated cognition is an idea borrowed from a long since discredited philosophy of science. It argues that feminist standpoint theory ought not be indulged as it is a failed challenge to…

Science knowledge and cognitive strategy use among culturally and linguistically diverse students

NASA Astrophysics Data System (ADS)

Lee, Okhee; Fradd, Sandra H.; Sutman, Frank X.

Science performance is determined, to a large extent, by what students already know about science (i.e., science knowledge) and what techniques or methods students use in performing science tasks (i.e., cognitive strategies). This study describes and compares science knowledge, science vocabulary, and cognitive strategy use among four diverse groups of elementary students: (a) monolingual English Caucasian, (b) African-American, (c) bilingual Spanish, and (d) bilingual Haitian Creole. To facilitate science performance in culturally and linguistically congruent settings, the study included student dyads and teachers of the same language, culture, and gender. Science performance was observed using three science tasks: weather phenomena, simple machines, and buoyancy. Data analysis involved a range of qualitative methods focusing on major themes and patterns, and quantitative methods using coding systems to summarize frequencies and total scores. The findings reveal distinct patterns of science knowledge, science vocabulary, and cognitive strategy use among the four language and culture groups. The findings also indicate relationships among science knowledge, science vocabulary, and cognitive strategy use. These findings raise important issues about science instruction for culturally and linguistically diverse groups of students.Received: 3 January 1995;

Fuzzy Logic, Neural Networks, Genetic Algorithms: Views of Three Artificial Intelligence Concepts Used in Modeling Scientific Systems

ERIC Educational Resources Information Center

Sunal, Cynthia Szymanski; Karr, Charles L.; Sunal, Dennis W.

2003-01-01

Students' conceptions of three major artificial intelligence concepts used in the modeling of systems in science, fuzzy logic, neural networks, and genetic algorithms were investigated before and after a higher education science course. Students initially explored their prior ideas related to the three concepts through active tasks. Then,…

Does formal complexity reflect cognitive complexity? Investigating aspects of the Chomsky Hierarchy in an artificial language learning study.

PubMed

Öttl, Birgit; Jäger, Gerhard; Kaup, Barbara

2015-01-01

This study investigated whether formal complexity, as described by the Chomsky Hierarchy, corresponds to cognitive complexity during language learning. According to the Chomsky Hierarchy, nested dependencies (context-free) are less complex than cross-serial dependencies (mildly context-sensitive). In two artificial grammar learning (AGL) experiments participants were presented with a language containing either nested or cross-serial dependencies. A learning effect for both types of dependencies could be observed, but no difference between dependency types emerged. These behavioral findings do not seem to reflect complexity differences as described in the Chomsky Hierarchy. This study extends previous findings in demonstrating learning effects for nested and cross-serial dependencies with more natural stimulus materials in a classical AGL paradigm after only one hour of exposure. The current findings can be taken as a starting point for further exploring the degree to which the Chomsky Hierarchy reflects cognitive processes.

Does Formal Complexity Reflect Cognitive Complexity? Investigating Aspects of the Chomsky Hierarchy in an Artificial Language Learning Study

PubMed Central

Öttl, Birgit; Jäger, Gerhard; Kaup, Barbara

2015-01-01

This study investigated whether formal complexity, as described by the Chomsky Hierarchy, corresponds to cognitive complexity during language learning. According to the Chomsky Hierarchy, nested dependencies (context-free) are less complex than cross-serial dependencies (mildly context-sensitive). In two artificial grammar learning (AGL) experiments participants were presented with a language containing either nested or cross-serial dependencies. A learning effect for both types of dependencies could be observed, but no difference between dependency types emerged. These behavioral findings do not seem to reflect complexity differences as described in the Chomsky Hierarchy. This study extends previous findings in demonstrating learning effects for nested and cross-serial dependencies with more natural stimulus materials in a classical AGL paradigm after only one hour of exposure. The current findings can be taken as a starting point for further exploring the degree to which the Chomsky Hierarchy reflects cognitive processes. PMID:25885790

Research Directions in Remote Detection of Covert Tactical Adversarial Intent of Individuals in Asymmetric Operations

DTIC Science & Technology

2010-07-01

To be successful, the research needs to integrate kinesiological , neurophysiological, psychological, and cognitive science, and sociocultural... kinesiological neurophysiological, psychological, and cognitive science and sociocultural anthropology and information science components. Research and...successful, the research needs to integrate kinesiological , neurophysiological, psychological, and cognitive science, and sociocultural

Dimension-Based Statistical Learning Affects Both Speech Perception and Production.

PubMed

Lehet, Matthew; Holt, Lori L

2017-04-01

Multiple acoustic dimensions signal speech categories. However, dimensions vary in their informativeness; some are more diagnostic of category membership than others. Speech categorization reflects these dimensional regularities such that diagnostic dimensions carry more "perceptual weight" and more effectively signal category membership to native listeners. Yet perceptual weights are malleable. When short-term experience deviates from long-term language norms, such as in a foreign accent, the perceptual weight of acoustic dimensions in signaling speech category membership rapidly adjusts. The present study investigated whether rapid adjustments in listeners' perceptual weights in response to speech that deviates from the norms also affects listeners' own speech productions. In a word recognition task, the correlation between two acoustic dimensions signaling consonant categories, fundamental frequency (F0) and voice onset time (VOT), matched the correlation typical of English, and then shifted to an "artificial accent" that reversed the relationship, and then shifted back. Brief, incidental exposure to the artificial accent caused participants to down-weight perceptual reliance on F0, consistent with previous research. Throughout the task, participants were intermittently prompted with pictures to produce these same words. In the block in which listeners heard the artificial accent with a reversed F0 × VOT correlation, F0 was a less robust cue to voicing in listeners' own speech productions. The statistical regularities of short-term speech input affect both speech perception and production, as evidenced via shifts in how acoustic dimensions are weighted. Copyright © 2016 Cognitive Science Society, Inc.

Cognitive science in popular film: the Cognitive Science Movie Index.

PubMed

Motz, Benjamin

2013-10-01

HAL 9000. Morpheus. Skynet. These household names demonstrate the strong cultural impact of films depicting themes in cognitive science and the potential power of popular cinema for outreach and education. Considering their wide influence, there is value to aggregating these movies and reflecting on their renderings of our field. The Cognitive Science Movie Index (CSMI) serves these purposes, leveraging popular film for the advancement of the discipline. Copyright © 2013 Elsevier Ltd. All rights reserved.

On Learning the Past Tenses of English Verbs.

DTIC Science & Technology

1985-10-01

RD-AI164 233 ON LEARING THE PAST TENSES OF ENGLISH YERBS(U) vi1 r CALIFORNIA UNIV SAN DIEGO LA JOLLA INST FOR COGNITIVE SCIENCE D E RUMELNART ET AL... COGNITIVE SCIENCE O I$FE13Me~ 0C*" INSTITUTE FOR COGNITIVE SCIENCE UNIVERSITY OF CALIFORNIA, SAN DIEGO LA JOLLA, CALIFORNIA 92093 - *~-’~7...8507 . *** David E. Rurneihart James L. McClelland Institute for Cognitive Science Department of Psychology University of Calif ornia. San Diego

Music cognition and the cognitive sciences.

PubMed

Pearce, Marcus; Rohrmeier, Martin

2012-10-01

Why should music be of interest to cognitive scientists, and what role does it play in human cognition? We review three factors that make music an important topic for cognitive scientific research. First, music is a universal human trait fulfilling crucial roles in everyday life. Second, music has an important part to play in ontogenetic development and human evolution. Third, appreciating and producing music simultaneously engage many complex perceptual, cognitive, and emotional processes, rendering music an ideal object for studying the mind. We propose an integrated status for music cognition in the Cognitive Sciences and conclude by reviewing challenges and big questions in the field and the way in which these reflect recent developments. Copyright © 2012 Cognitive Science Society, Inc.

The part of cognitive science that is philosophy.

PubMed

Dennett, Daniel C

2009-04-01

There is much good work for philosophers to do in cognitive science if they adopt the constructive attitude that prevails in science, work toward testable hypotheses, and take on the task of clarifying the relationship between the scientific concepts and the everyday concepts with which we conduct our moral lives. Copyright © 2009 Cognitive Science Society, Inc.

Multiscale Modeling of Gene-Behavior Associations in an Artificial Neural Network Model of Cognitive Development

ERIC Educational Resources Information Center

Thomas, Michael S. C.; Forrester, Neil A.; Ronald, Angelica

2016-01-01

In the multidisciplinary field of developmental cognitive neuroscience, statistical associations between levels of description play an increasingly important role. One example of such associations is the observation of correlations between relatively common gene variants and individual differences in behavior. It is perhaps surprising that such…

Philosophical and Socio-Cognitive Foundations for Teaching in Higher Education through Collaborative Approaches to Student Learning

ERIC Educational Resources Information Center

Jones, Adrian

2011-01-01

This paper considers the implications for higher education of recent work on narrative theory, distributed cognition and artificial intelligence. These perspectives are contrasted with the educational implications of Heidegger's ontological phenomenology [being-there and being-aware (Da-sein)] and with the classic and classical foundations of…

Is cognitive science usefully cast as complexity science?

PubMed

Van Orden, Guy; Stephen, Damian G

2012-01-01

Readers of TopiCS are invited to join a debate about the utility of ideas and methods of complexity science. The topics of debate include empirical instances of qualitative change in cognitive activity and whether this empirical work demonstrates sufficiently the empirical flags of complexity. In addition, new phenomena discovered by complexity scientists, and motivated by complexity theory, call into question some basic assumptions of conventional cognitive science such as stable equilibria and homogeneous variance. The articles and commentaries that appear in this issue also illustrate a new debate style format for topiCS. Copyright © 2011 Cognitive Science Society, Inc.

Functional relations and cognitive psychology: Lessons from human performance and animal research.

PubMed

Proctor, Robert W; Urcuioli, Peter J

2016-02-01

We consider requirements for effective interdisciplinary communication and explore alternative interpretations of "building bridges between functional and cognitive psychology." If the bridges are intended to connect radical behaviourism and cognitive psychology, or functional contextualism and cognitive psychology, the efforts are unlikely to be successful. But if the bridges are intended to connect functional relationships and cognitive theory, no construction is needed because the bridges already exist within cognitive psychology. We use human performance and animal research to illustrate the latter point and to counter the claim that the functional approach is unique in offering a close relationship between science and practice. Effective communication will be enhanced and, indeed, may only occur if the goal of functional contextualism extends beyond just "the advancement of functional contextual cognitive and behavioral science and practice" to "the advancement of cognitive and behavioral science and practice" without restriction. © 2015 International Union of Psychological Science.

Extended cognition in science communication.

PubMed

Ludwig, David

2014-11-01

The aim of this article is to propose a methodological externalism that takes knowledge about science to be partly constituted by the environment. My starting point is the debate about extended cognition in contemporary philosophy and cognitive science. Externalists claim that human cognition extends beyond the brain and can be partly constituted by external devices. First, I show that most studies of public knowledge about science are based on an internalist framework that excludes the environment we usually utilize to make sense of science and does not allow the possibility of extended knowledge. In a second step, I argue that science communication studies should adopt a methodological externalism and accept that knowledge about science can be partly realized by external information resources such as Wikipedia. © The Author(s) 2013.

Anthropology in cognitive science.

PubMed

Bender, Andrea; Hutchins, Edwin; Medin, Douglas

2010-07-01

This paper reviews the uneven history of the relationship between Anthropology and Cognitive Science over the past 30 years, from its promising beginnings, followed by a period of disaffection, on up to the current context, which may lay the groundwork for reconsidering what Anthropology and (the rest of) Cognitive Science have to offer each other. We think that this history has important lessons to teach and has implications for contemporary efforts to restore Anthropology to its proper place within Cognitive Science. The recent upsurge of interest in the ways that thought may shape and be shaped by action, gesture, cultural experience, and language sets the stage for, but so far has not fully accomplished, the inclusion of Anthropology as an equal partner. Copyright © 2010 Cognitive Science Society, Inc.

Science of the science, drug discovery and artificial neural networks.

PubMed

Patel, Jigneshkumar

2013-03-01

Drug discovery process many times encounters complex problems, which may be difficult to solve by human intelligence. Artificial Neural Networks (ANNs) are one of the Artificial Intelligence (AI) technologies used for solving such complex problems. ANNs are widely used for primary virtual screening of compounds, quantitative structure activity relationship studies, receptor modeling, formulation development, pharmacokinetics and in all other processes involving complex mathematical modeling. Despite having such advanced technologies and enough understanding of biological systems, drug discovery is still a lengthy, expensive, difficult and inefficient process with low rate of new successful therapeutic discovery. In this paper, author has discussed the drug discovery science and ANN from very basic angle, which may be helpful to understand the application of ANN for drug discovery to improve efficiency.

Science Teachers' Epistemic Cognition in Instructional Decision Making

ERIC Educational Resources Information Center

Ponnock, Annette R.

2017-01-01

One understudied barrier to science education reform concerns teachers' cognitive processes and how they relate to instructional decision-making. Epistemic cognition--teachers' beliefs about knowledge and knowledge acquisition and goals for their students' knowledge acquisition--could provide important insights into the choices science teachers…

To naturalize or not to naturalize? An issue for cognitive science as well as anthropology.

PubMed

Stenning, Keith

2012-07-01

Several of Beller, Bender, and Medin's (2012) issues are as relevant within cognitive science as between it and anthropology. Knowledge-rich human mental processes impose hermeneutic tasks, both on subjects and researchers. Psychology's current philosophy of science is ill suited to analyzing these: Its demand for ''stimulus control'' needs to give way to ''negotiation of mutual interpretation.'' Cognitive science has ways to address these issues, as does anthropology. An example from my own work is about how defeasible logics are mathematical models of some aspects of simple hermeneutic processes. They explain processing relative to databases of knowledge and belief-that is, content. A specific example is syllogistic reasoning, which raises issues of experimenters' interpretations of subjects' reasoning. Science, especially since the advent of understandings of computation, does not have to be reductive. How does this approach transfer onto anthropological topics? Recent cognitive science approaches to anthropological topics have taken a reductive stance in terms of modules. We end with some speculations about a different cognitive approach to, for example, religion. Copyright © 2012 Cognitive Science Society, Inc.

Useful theories make predictions.

PubMed

Howes, Andrew

2012-01-01

Stephen and Van Orden (this issue) propose that there is a complex system approach to cognitive science, and collectively the authors of the papers presented in this issue believe that this approach provides the means to drive a revolution in the science of the mind. Unfortunately, however illuminating, this explanation is absent and hyperbole is all too extensive. In contrast, I argue (1) that dynamic systems theory is not new to cognitive science and does not provide a basis for a revolution, (2) it is not necessary to reject cognitive science in order to explain the constraints imposed by the body and the environment, (3) it is not necessary, as Silberstein and Chemero (this issue) appear to do, to reject cognitive science in order to explain consciousness, and (4) our understanding of pragmatics is not advanced by Gibbs and Van Orden's (this issue) "self-organized criticality".? Any debate about the future of cognitive science could usefully focus on predictive adequacy. Unfortunately, this is not the approach taken by the authors of this issue. Copyright © 2012 Cognitive Science Society, Inc.

Using Artificial Orthographies for Studying Cross-Linguistic Differences in the Cognitive and Neural Profiles of Reading

PubMed Central

Hirshorn, Elizabeth A.; Fiez, Julie A.

2017-01-01

Reading and writing are cultural inventions that have become vital skills to master in modern society. Unfortunately, writing systems are not equally learnable and many individuals struggle to become proficient readers. Languages and their writing systems often have co-varying characteristics, due to both psycholinguistic and socio-cultural forces. This makes it difficult to determine the source of cross-linguistic differences in reading and writing. Nonetheless, it is important to make progress on this issue: a more precise understanding of the factors that affect reading disparities should improve reading instruction theory and practice, and the diagnosis and treatment of reading disorders. In this review, we consider the value of artificial orthographies as a tool for unpacking the factors that create cognitive and neural differences in reading acquisition and skill. We do so by focusing on one dimension that differs among writing systems: grain size. Grain size, or the unit of spoken language that is mapped onto a visual graph, is thought to affect learning, but its impact is still not well understood. We review relevant literature about cross-linguistic writing system differences, the benefits of using artificial orthographies as a research tool, and our recent work with an artificial alphasyllabic writing system for English. We conclude that artificial orthographies can be used to elucidate cross-linguistic principles that affect reading and writing. PMID:28280288

Cognitive Neuroimaging: Cognitive Science out of the Armchair

ERIC Educational Resources Information Center

de Zubicaray, Greig I.

2006-01-01

Cognitive scientists were not quick to embrace the functional neuroimaging technologies that emerged during the late 20th century. In this new century, cognitive scientists continue to question, not unreasonably, the relevance of functional neuroimaging investigations that fail to address questions of interest to cognitive science. However, some…

Smart phone, smart science: how the use of smartphones can revolutionize research in cognitive science.

PubMed

Dufau, Stephane; Duñabeitia, Jon Andoni; Moret-Tatay, Carmen; McGonigal, Aileen; Peeters, David; Alario, F-Xavier; Balota, David A; Brysbaert, Marc; Carreiras, Manuel; Ferrand, Ludovic; Ktori, Maria; Perea, Manuel; Rastle, Kathy; Sasburg, Olivier; Yap, Melvin J; Ziegler, Johannes C; Grainger, Jonathan

2011-01-01

Investigating human cognitive faculties such as language, attention, and memory most often relies on testing small and homogeneous groups of volunteers coming to research facilities where they are asked to participate in behavioral experiments. We show that this limitation and sampling bias can be overcome by using smartphone technology to collect data in cognitive science experiments from thousands of subjects from all over the world. This mass coordinated use of smartphones creates a novel and powerful scientific "instrument" that yields the data necessary to test universal theories of cognition. This increase in power represents a potential revolution in cognitive science.

The structure of the cognitive revolution: An examination from the philosophy of science

PubMed Central

O'Donohue, William; Ferguson, Kyle E.; Naugle, Amy E.

2003-01-01

The received view is that psychology has undergone several scientific revolutions similar to those that occurred in the physical sciences. Of these, this paper will consider the cognitive revolution. Because the arguments in favor of the existence of a cognitive revolution are cast using the concepts and terms of revolutionary science, we will examine the cognitive revolution using accounts of revolutionary science advanced by five influential philosophers of science. Specifically, we will draw from the philosophical positions of Popper, Kuhn, Lakatos, Laudan, and Gross for the purpose of discussion. We conclude that no substantive revolution took place according to these accounts. This conclusion is based on data gathered from some of the major participants in the “cognitive revolution” and on a general scholarly survey of the literature. We argue that the so-called cognitive revolution is best characterized as a socio-rhetorical phenomenon. PMID:22478396

What's statistical about learning? Insights from modelling statistical learning as a set of memory processes

PubMed Central

2017-01-01

Statistical learning has been studied in a variety of different tasks, including word segmentation, object identification, category learning, artificial grammar learning and serial reaction time tasks (e.g. Saffran et al. 1996 Science 274, 1926–1928; Orban et al. 2008 Proceedings of the National Academy of Sciences 105, 2745–2750; Thiessen & Yee 2010 Child Development 81, 1287–1303; Saffran 2002 Journal of Memory and Language 47, 172–196; Misyak & Christiansen 2012 Language Learning 62, 302–331). The difference among these tasks raises questions about whether they all depend on the same kinds of underlying processes and computations, or whether they are tapping into different underlying mechanisms. Prior theoretical approaches to statistical learning have often tried to explain or model learning in a single task. However, in many cases these approaches appear inadequate to explain performance in multiple tasks. For example, explaining word segmentation via the computation of sequential statistics (such as transitional probability) provides little insight into the nature of sensitivity to regularities among simultaneously presented features. In this article, we will present a formal computational approach that we believe is a good candidate to provide a unifying framework to explore and explain learning in a wide variety of statistical learning tasks. This framework suggests that statistical learning arises from a set of processes that are inherent in memory systems, including activation, interference, integration of information and forgetting (e.g. Perruchet & Vinter 1998 Journal of Memory and Language 39, 246–263; Thiessen et al. 2013 Psychological Bulletin 139, 792–814). From this perspective, statistical learning does not involve explicit computation of statistics, but rather the extraction of elements of the input into memory traces, and subsequent integration across those memory traces that emphasize consistent information (Thiessen and Pavlik 2013 Cognitive Science 37, 310–343). This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences'. PMID:27872374

What's statistical about learning? Insights from modelling statistical learning as a set of memory processes.

PubMed

Thiessen, Erik D

2017-01-05

Statistical learning has been studied in a variety of different tasks, including word segmentation, object identification, category learning, artificial grammar learning and serial reaction time tasks (e.g. Saffran et al. 1996 Science 274: , 1926-1928; Orban et al. 2008 Proceedings of the National Academy of Sciences 105: , 2745-2750; Thiessen & Yee 2010 Child Development 81: , 1287-1303; Saffran 2002 Journal of Memory and Language 47: , 172-196; Misyak & Christiansen 2012 Language Learning 62: , 302-331). The difference among these tasks raises questions about whether they all depend on the same kinds of underlying processes and computations, or whether they are tapping into different underlying mechanisms. Prior theoretical approaches to statistical learning have often tried to explain or model learning in a single task. However, in many cases these approaches appear inadequate to explain performance in multiple tasks. For example, explaining word segmentation via the computation of sequential statistics (such as transitional probability) provides little insight into the nature of sensitivity to regularities among simultaneously presented features. In this article, we will present a formal computational approach that we believe is a good candidate to provide a unifying framework to explore and explain learning in a wide variety of statistical learning tasks. This framework suggests that statistical learning arises from a set of processes that are inherent in memory systems, including activation, interference, integration of information and forgetting (e.g. Perruchet & Vinter 1998 Journal of Memory and Language 39: , 246-263; Thiessen et al. 2013 Psychological Bulletin 139: , 792-814). From this perspective, statistical learning does not involve explicit computation of statistics, but rather the extraction of elements of the input into memory traces, and subsequent integration across those memory traces that emphasize consistent information (Thiessen and Pavlik 2013 Cognitive Science 37: , 310-343).This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).

Learning multiple rules simultaneously: Affixes are more salient than reduplications.

PubMed

Gervain, Judit; Endress, Ansgar D

2017-04-01

Language learners encounter numerous opportunities to learn regularities, but need to decide which of these regularities to learn, because some are not productive in their native language. Here, we present an account of rule learning based on perceptual and memory primitives (Endress, Dehaene-Lambertz, & Mehler, Cognition, 105(3), 577-614, 2007; Endress, Nespor, & Mehler, Trends in Cognitive Sciences, 13(8), 348-353, 2009), suggesting that learners preferentially learn regularities that are more salient to them, and that the pattern of salience reflects the frequency of language features across languages. We contrast this view with previous artificial grammar learning research, which suggests that infants "choose" the regularities they learn based on rational, Bayesian criteria (Frank & Tenenbaum, Cognition, 120(3), 360-371, 2013; Gerken, Cognition, 98(3)B67-B74, 2006, Cognition, 115(2), 362-366, 2010). In our experiments, adult participants listened to syllable strings starting with a syllable reduplication and always ending with the same "affix" syllable, or to syllable strings starting with this "affix" syllable and ending with the "reduplication". Both affixation and reduplication are frequently used for morphological marking across languages. We find three crucial results. First, participants learned both regularities simultaneously. Second, affixation regularities seemed easier to learn than reduplication regularities. Third, regularities in sequence offsets were easier to learn than regularities at sequence onsets. We show that these results are inconsistent with previous Bayesian rule learning models, but mesh well with the perceptual or memory primitives view. Further, we show that the pattern of salience revealed in our experiments reflects the distribution of regularities across languages. Ease of acquisition might thus be one determinant of the frequency of regularities across languages.

A Programming Environment Evaluation Methodology for Object-Oriented Systems. Ph.D Thesis Final Report, 1 Jul. 1985 - 31 Dec. 1987

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Moreau, Dennis R.

1987-01-01

The object-oriented design strategy as both a problem decomposition and system development paradigm has made impressive inroads into the various areas of the computing sciences. Substantial development productivity improvements have been demonstrated in areas ranging from artificial intelligence to user interface design. However, there has been very little progress in the formal characterization of these productivity improvements and in the identification of the underlying cognitive mechanisms. The development and validation of models and metrics of this sort require large amounts of systematically-gathered structural and productivity data. There has, however, been a notable lack of systematically-gathered information on these development environments. A large part of this problem is attributable to the lack of a systematic programming environment evaluation methodology that is appropriate to the evaluation of object-oriented systems.

Projective simulation for artificial intelligence

NASA Astrophysics Data System (ADS)

Briegel, Hans J.; de Las Cuevas, Gemma

2012-05-01

We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation.

Projective simulation for artificial intelligence

PubMed Central

Briegel, Hans J.; De las Cuevas, Gemma

2012-01-01

We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation. PMID:22590690

Cognitive and Neural Sciences Division 1990 Programs.

ERIC Educational Resources Information Center

Vaughan, Willard S., Jr., Ed.

Research and development efforts carried out under sponsorship of the Cognitive and Neural Sciences Division of the Office of Naval Research during fiscal year 1990 are described in this compilation of project description summaries. The Division's research is organized in three types of programs: (1) Cognitive Science (the human learner--cognitive…

An Exploration of Students' Science Learning Interest Related to Their Cognitive Anxiety, Cognitive Load, Self-Confidence and Learning Progress Using Inquiry-Based Learning with an iPad

ERIC Educational Resources Information Center

Hong, Jon-Chao; Hwang, Ming-Yueh; Tai, Kai-Hsin; Tsai, Chi-Ruei

2017-01-01

Based on the cognitive-affective theory, the present study designed a science inquiry learning model, "predict-observe-explain" (POE), and implemented it in an app called "WhyWhy" to examine the effectiveness of students' science inquiry learning practice. To understand how POE can affect the cognitive-affective learning…

Translation Meets Cognitive Science: The Imprint of Translation on Cognitive Processing

ERIC Educational Resources Information Center

Rojo, Ana

2015-01-01

Translation has long played a role in linguistic and literary studies research. More recently, the theoretical and methodological concerns of process research have given translation an additional role in cognitive science. The interest in the cognitive aspects of translation has led scholars to turn to disciplines such as cognitive linguistics,…

Anesthesia 2.0: internet-based information resources and Web 2.0 applications in anesthesia education.

PubMed

Chu, Larry F; Young, Chelsea; Zamora, Abby; Kurup, Viji; Macario, Alex

2010-04-01

Informatics is a broad field encompassing artificial intelligence, cognitive science, computer science, information science, and social science. The goal of this review is to illustrate how Web 2.0 information technologies could be used to improve anesthesia education. Educators in all specialties of medicine are increasingly studying Web 2.0 technologies to maximize postgraduate medical education of housestaff. These technologies include microblogging, blogs, really simple syndication (RSS) feeds, podcasts, wikis, and social bookmarking and networking. 'Anesthesia 2.0' reflects our expectation that these technologies will foster innovation and interactivity in anesthesia-related web resources which embraces the principles of openness, sharing, and interconnectedness that represent the Web 2.0 movement. Although several recent studies have shown benefits of implementing these systems into medical education, much more investigation is needed. Although direct practice and observation in the operating room are essential, Web 2.0 technologies hold great promise to innovate anesthesia education and clinical practice such that the resident learner need not be in a classroom for a didactic talk, or even in the operating room to see how an arterial line is properly placed. Thoughtful research to maximize implementation of these technologies should be a priority for development by academic anesthesiology departments. Web 2.0 and advanced informatics resources will be part of physician lifelong learning and clinical practice.

The architecture challenge: Future artificial-intelligence systems will require sophisticated architectures, and knowledge of the brain might guide their construction.

PubMed

Baldassarre, Gianluca; Santucci, Vieri Giuliano; Cartoni, Emilio; Caligiore, Daniele

2017-01-01

In this commentary, we highlight a crucial challenge posed by the proposal of Lake et al. to introduce key elements of human cognition into deep neural networks and future artificial-intelligence systems: the need to design effective sophisticated architectures. We propose that looking at the brain is an important means of facing this great challenge.

Pre-Service Science Teachers' Cognitive Structures Regarding Science, Technology, Engineering, Mathematics (STEM) and Science Education

ERIC Educational Resources Information Center

Hacioglu, Yasemin; Yamak, Havva; Kavak, Nusret

2016-01-01

The aim of this study is to reveal pre-service science teachers' cognitive structures regarding Science, Technology, Engineering, Mathematics (STEM) and science education. The study group of the study consisted of 192 pre-service science teachers. A Free Word Association Test (WAT) consisting of science, technology, engineering, mathematics and…

Dual PECCS: a cognitive system for conceptual representation and categorization

NASA Astrophysics Data System (ADS)

Lieto, Antonio; Radicioni, Daniele P.; Rho, Valentina

2017-03-01

In this article we present an advanced version of Dual-PECCS, a cognitively-inspired knowledge representation and reasoning system aimed at extending the capabilities of artificial systems in conceptual categorization tasks. It combines different sorts of common-sense categorization (prototypical and exemplars-based categorization) with standard monotonic categorization procedures. These different types of inferential procedures are reconciled according to the tenets coming from the dual process theory of reasoning. On the other hand, from a representational perspective, the system relies on the hypothesis of conceptual structures represented as heterogeneous proxytypes. Dual-PECCS has been experimentally assessed in a task of conceptual categorization where a target concept illustrated by a simple common-sense linguistic description had to be identified by resorting to a mix of categorization strategies, and its output has been compared to human responses. The obtained results suggest that our approach can be beneficial to improve the representational and reasoning conceptual capabilities of standard cognitive artificial systems, and - in addition - that it may be plausibly applied to different general computational models of cognition. The current version of the system, in fact, extends our previous work, in that Dual- PECCS is now integrated and tested into two cognitive architectures, ACT-R and CLARION, implementing different assumptions on the underlying invariant structures governing human cognition. Such integration allowed us to extend our previous evaluation.

Software Reviews.

ERIC Educational Resources Information Center

Wulfson, Stephen, Ed.

1988-01-01

Reviews seven instructional software packages covering a variety of topics. Includes: "Science Square-Off"; "The Desert"; "Science Courseware: Physical Science"; "Odell Lake"; "Safety First"; "An Experience in Artificial Intelligence"; and "Master Mapper." (TW)

New Types of Artificial Muscles for Large Stroke and High Force Applications

DTIC Science & Technology

2012-10-10

University of Texas at Dallas and include Aerogel Muscles, Torsional and Tensile Yarn Muscles, Artificial Muscles Based on Polypyrrole Laminates and...Stroke, Superelastic Carbon Nanotube Aerogel Muscles 3. Torsional and Tensile Carbon Nanotube Yarn Muscles 4. Artificial Muscles Based on...in numerous press releases and TV programs. As we reported in Science 2009, carbon nanotube aerogel sheets are the sole component of new artificial

Intelligent Tutoring Systems

NASA Astrophysics Data System (ADS)

Anderson, John R.; Boyle, C. Franklin; Reiser, Brian J.

1985-04-01

Cognitive psychology, artificial intelligence, and computer technology have advanced to the point where it is feasible to build computer systems that are as effective as intelligent human tutors. Computer tutors based on a set of pedagogical principles derived from the ACT theory of cognition have been developed for teaching students to do proofs in geometry and to write computer programs in the language LISP.

Intelligent tutoring systems.

PubMed

Anderson, J R; Boyle, C F; Reiser, B J

1985-04-26

Cognitive psychology, artificial intelligence, and computer technology have advanced to the point where it is feasible to build computer systems that are as effective as intelligent human tutors. Computer tutors based on a set of pedagogical principles derived from the ACT theory of cognition have been developed for teaching students to do proofs in geometry and to write computer programs in the language LISP.

Review of Winograd and Flores'"Understanding Computers and Cognition": A Favorable Interpretation. ONR Technical Report #21.

ERIC Educational Resources Information Center

Clancey, William J.

Artificial Intelligence researchers and cognitive scientists commonly believe that thinking involves manipulating representations. Thinking involves search, inference, and making choices. This is how we model reasoning and what goes on in the brain is similar. Winograd and Flores present a radically different view, claiming that our knowledge is…

Investigating the Use of Vicarious and Mastery Experiences in Influencing Early Childhood Education Majors' Self-Efficacy Beliefs

NASA Astrophysics Data System (ADS)

Bautista, Nazan Uludag

2011-06-01

This study investigated the effectiveness of an Early Childhood Education science methods course that focused exclusively on providing various mastery (i.e., enactive, cognitive content, and cognitive pedagogical) and vicarious experiences (i.e., cognitive self-modeling, symbolic modeling, and simulated modeling) in increasing preservice elementary teachers' self-efficacy beliefs. Forty-four preservice elementary teachers participated in the study. Analysis of the quantitative (STEBI-b) and qualitative (informal surveys) data revealed that personal science teaching efficacy and science teaching outcome expectancy beliefs increased significantly over the semester. Enactive mastery, cognitive pedagogical mastery, symbolic modeling, and cognitive self-modeling were the major sources of self-efficacy. This list was followed by cognitive content mastery and simulated modeling. This study has implications for science teacher educators.

Connecting cognition and consumer choice.

PubMed

Bartels, Daniel M; Johnson, Eric J

2015-02-01

We describe what can be gained from connecting cognition and consumer choice by discussing two contexts ripe for interaction between the two fields. The first-context effects on choice-has already been addressed by cognitive science yielding insights about cognitive process but there is promise for more interaction. The second is learning and representation in choice where relevant theories in cognitive science could be informed by consumer choice, and in return, could pose and answer new questions. We conclude by discussing how these two fields of research stand to benefit from more interaction, citing examples of how interfaces of cognitive science with other fields have been illuminating for theories of cognition. Copyright © 2014 Elsevier B.V. All rights reserved.

Computer science, artificial intelligence, and cybernetics: Applied artificial intelligence in Japan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rubinger, B.

1988-01-01

This sourcebook provides information on the developments in artificial intelligence originating in Japan. Spanning such innovations as software productivity, natural language processing, CAD, and parallel inference machines, this volume lists leading organizations conducting research or implementing AI systems, describes AI applications being pursued, illustrates current results achieved, and highlights sources reporting progress.

Science Education for Women: Situated Cognition, Feminist Standpoint Theory, and the Status of Women in Science

NASA Astrophysics Data System (ADS)

Pinnick, Cassandra L.

2008-11-01

This paper examines the relation between situated cognition theory in science education, and feminist standpoint theory in philosophy of science. It shows that situated cognition is an idea borrowed from a long since discredited philosophy of science. It argues that feminist standpoint theory ought not be indulged as it is a failed challenge to traditional philosophy of science. Standpoint theory diverts attention away from the abiding educational and career needs of women in science. In the interest of women in science, and in the interest of science, science educators would do best for their constituencies by a return to feminist philosophy understood as the demand for equal access and a level playing field for women in science and society.

Building machines that learn and think like people.

PubMed

Lake, Brenden M; Ullman, Tomer D; Tenenbaum, Joshua B; Gershman, Samuel J

2017-01-01

Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn and how they learn it. Specifically, we argue that these machines should (1) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (2) ground learning in intuitive theories of physics and psychology to support and enrich the knowledge that is learned; and (3) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes toward these goals that can combine the strengths of recent neural network advances with more structured cognitive models.

Parallel Distributed Processing at 25: further explorations in the microstructure of cognition.

PubMed

Rogers, Timothy T; McClelland, James L

2014-08-01

This paper introduces a special issue of Cognitive Science initiated on the 25th anniversary of the publication of Parallel Distributed Processing (PDP), a two-volume work that introduced the use of neural network models as vehicles for understanding cognition. The collection surveys the core commitments of the PDP framework, the key issues the framework has addressed, and the debates the framework has spawned, and presents viewpoints on the current status of these issues. The articles focus on both historical roots and contemporary developments in learning, optimality theory, perception, memory, language, conceptual knowledge, cognitive control, and consciousness. Here we consider the approach more generally, reviewing the original motivations, the resulting framework, and the central tenets of the underlying theory. We then evaluate the impact of PDP both on the field at large and within specific subdomains of cognitive science and consider the current role of PDP models within the broader landscape of contemporary theoretical frameworks in cognitive science. Looking to the future, we consider the implications for cognitive science of the recent success of machine learning systems called "deep networks"-systems that build on key ideas presented in the PDP volumes. Copyright © 2014 Cognitive Science Society, Inc.

Economic development evaluation based on science and patents

NASA Astrophysics Data System (ADS)

Jokanović, Bojana; Lalic, Bojan; Milovančević, Miloš; Simeunović, Nenad; Marković, Dusan

2017-09-01

Economic development could be achieved through many factors. Science and technology factors could influence economic development drastically. Therefore the main aim in this study was to apply computational intelligence methodology, artificial neural network approach, for economic development estimation based on different science and technology factors. Since economic analyzing could be very challenging task because of high nonlinearity, in this study was applied computational intelligence methodology, artificial neural network approach, to estimate the economic development based on different science and technology factors. As economic development measure, gross domestic product (GDP) was used. As the science and technology factors, patents in different field were used. It was found that the patents in electrical engineering field have the highest influence on the economic development or the GDP.

JPRS Report Science & Technology Japan STA 1988 White Paper Part 2.

DTIC Science & Technology

1989-12-13

artificial insemination . In connection with the "Progress of Life Sciences and Their Harmony With Mankind and Society," a theme whose importance is pointed...Research Dept. The Weather Satellite Research Department has been reorganized into the Weather Satellite / Monitoring System Research Dept. The...research on undersea greening technology (creation of seaweed farms using artificial light), and 3) research on tech- nology for probing and breeding

Perspectives on modeling in cognitive science.

PubMed

Shiffrin, Richard M

2010-10-01

This commentary gives a personal perspective on modeling and modeling developments in cognitive science, starting in the 1950s, but focusing on the author's personal views of modeling since training in the late 1960s, and particularly focusing on advances since the official founding of the Cognitive Science Society. The range and variety of modeling approaches in use today are remarkable, and for many, bewildering. Yet to come to anything approaching adequate insights into the infinitely complex fields of mind, brain, and intelligent systems, an extremely wide array of modeling approaches is vital and necessary. Copyright © 2010 Cognitive Science Society, Inc.

Enquire within: cultural evolution and cognitive science.

PubMed

Heyes, Cecilia

2018-04-05

Cultural evolution and cognitive science need each other. Cultural evolution needs cognitive science to find out whether the conditions necessary for Darwinian evolution are met in the cultural domain. Cognitive science needs cultural evolution to explain the origins of distinctively human cognitive processes. Focusing on the first question, I argue that cultural evolutionists can get empirical traction on third-way cultural selection by rooting the distinction between replication and reconstruction, two modes of cultural inheritance, in the distinction between System 1 and System 2 cognitive processes. This move suggests that cultural epidemiologists are right in thinking that replication has higher fidelity than reconstruction, and replication processes are not genetic adaptations for culture, but wrong to assume that replication is rare. If replication is not rare, an important requirement for third-way cultural selection, one-shot fidelity , is likely to be met. However, there are other requirements, overlooked by dual-inheritance theorists when they conflate strong (Darwinian) and weak (choice) senses of 'cultural selection', including dumb choices and recurrent fidelity In a second excursion into cognitive science, I argue that these requirements can be met by metacognitive social learning strategies , and trace the origins of these distinctively human cognitive processes to cultural evolution. Like other forms of cultural learning, they are not cognitive instincts but cognitive gadgets.This article is part of the theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'. © 2018 The Author(s).

Could Intelligent Tutors Anticipate Successfully User Reactions?

NASA Astrophysics Data System (ADS)

Kalisz, Eugenia; Florea, Adina Magda

2006-06-01

Emotions have been shown to have an important impact on several human processes such as decision-making, planning, cognition, and learning. In an e-learning system, an artificial tutor capable of effectively understanding and anticipating the student emotions during learning will have a significantly enhanced role. The paper presents a model of an artificial tutor endowed with synthesized emotions according to the BDE model, previously developed by the authors. It also analyzes possible student reactions while interacting with the learning material and the way the artificial tutor could anticipate and should respond to these reactions, with adequate actions.

Science and Religious Education: A Deepening Conversation.

ERIC Educational Resources Information Center

Petersen, Rodney L.

1997-01-01

Argues that science and technology associated with research in artificial intelligence, the Human Genome Project, cosmology, and sociobiology raise questions that promote dialog between the worlds of science and religion. (DDR)

Can cognitive science create a cognitive economics?

PubMed

Chater, Nick

2015-02-01

Cognitive science can intersect with economics in at least three productive ways: by providing richer models of individual behaviour for use in economic analysis; by drawing from economic theory in order to model distributed cognition; and jointly to create more powerful 'rational' models of cognitive processes and social interaction. There is the prospect of moving from behavioural economics to a genuinely cognitive economics. Copyright © 2014. Published by Elsevier B.V.

Apple Fool! An Introduction to Artificial Flavors.

ERIC Educational Resources Information Center

Journal of Chemical Education, 2003

2003-01-01

Presents a science activity on consumer chemistry in which students explore artificial flavors that are commonly used in foods, such as isoamyl acetate and methyl salicylate. Includes instructor information and a student worksheet. (YDS)

A Non-Cognitive Formal Approach to Knowledge Representation in Artificial Intelligence.

DTIC Science & Technology

1986-06-01

example, Duda and others translated production rules into a partitioned semantic network (73). Representations were also translated into production...153. Berlin: Springer-Verlag, 1982. 38. Blikle, Andrzej . "Equational Languages," Information and Control, 21: 134-147 (September 1972). 285 39. Ezawa...Conference on Artificial Intelligence, IJCAI-75. 115-121. William Kaufmann, Inc., Los Altos CA, 1975. 73. Duda , Richard 0. and others. "Semantic

Computational Modeling of Cultural Dimensions in Adversary Organizations

DTIC Science & Technology

2010-01-01

Nodes”, In the Proceedings of the 9th Conference on Uncertainty in Artificial Intelli - gence, 1993. [8] Pearl, J. Probabilistic Reasoning in...the artificial life simulations; in con- trast, models with only a few agents typically employ quite sophisticated cognitive agents capa- ble of...Model Construction 45 cisions as to how to allocate scarce ISR assets (two Unmanned Air Systems, UAS ) among the two Red activities while at the same

Cognitive development in a secondary science setting

NASA Astrophysics Data System (ADS)

Endler, Lorna C.; Bond, Trevor

2000-12-01

Observations were made of the progressive change in the cognitive development of 141 students over the course of their secondary education in an Australian private school. Cognitive development was measured in years 8, 10 and 12 using Bond's Logical Orerations Test. Rasch analysis of each of the data sets provided ability estimates for students in the year groups of 1993 (year 8), 1995 (year 10) and 1997 (year 12). Twenty-nine students from the year group of 1993 were tested on all three occasions. We analysed data from these 29 students in order to investigate the children's cognitive development across years 8, 10 and 12. We also examined the influence of the Cognitive Acceleration through Science Education (CASE) Thinking Science program on the cognitive development and scholastic achievement of these students. We found increased mental growth between years 8 and 10 for most students in the Thinking Science cohort, which could not be predicted from their starting levels. There was a significant correlation between cognitive development and the scholastic achievement of these students. Although boys as a group were more advanced in cognitive development than girls in years 8 and 10, no difference was found in the rate of cognitive change based on sex up to year 10. However girls showed cognitive gains across years 10-12 which were not found in boys. The students who were new to the school also showed increased cognitive development in years 11 and 12. Students who had experienced the Thinking Science course were more cognitively developed than students who joined the school after the intervention had taken place. This study supports the claim of Adey and Shayer that there is a relationship between cognitive development and scholastic achievement, even though we used different measures of cognitive development and scholastic achievement.

Mutually Augmented Cognition

NASA Astrophysics Data System (ADS)

Friesdorf, Florian; Pangercic, Dejan; Bubb, Heiner; Beetz, Michael

In mac, an ergonomic dialog-system and algorithms will be developed that enable human experts and companions to be integrated into knowledge gathering and decision making processes of highly complex cognitive systems (e.g. Assistive Household as manifested further in the paper). In this event we propose to join algorithms and methodologies coming from Ergonomics and Artificial Intelligence that: a) make cognitive systems more congenial for non-expert humans, b) facilitate their comprehension by utilizing a high-level expandable control code for human experts and c) augment representation of such cognitive system into “deep representation” obtained through an interaction with human companions.

An Analysis of Cognitive Style Profiles and Related Science Achievement Among Secondary School Students.

ERIC Educational Resources Information Center

Ogden, William R.; Brewster, Patricia M.

The purpose of this study was to identify cognitive styles for successful and unsuccessful science students at the secondary level. Additional purposes were to identify common and unique elements in these composite cognitive styles and to substantiate the description of the groups of successful and unsuccessful science students according to the…

Cognitive Correlates of Performance in Algorithms in a Computer Science Course for High School

ERIC Educational Resources Information Center

Avancena, Aimee Theresa; Nishihara, Akinori

2014-01-01

Computer science for high school faces many challenging issues. One of these is whether the students possess the appropriate cognitive ability for learning the fundamentals of computer science. Online tests were created based on known cognitive factors and fundamental algorithms and were implemented among the second grade students in the…

How to Teach for Social Justice: Lessons from "Uncle Tom's Cabin" and Cognitive Science

ERIC Educational Resources Information Center

Bracher, Mark

2009-01-01

The author explains how principles of cognitive science can help teachers of literature use texts as a means of increasing students' commitment to social justice. Applying these principles to a particular work, Uncle Tom's Cabin, he calls particular attention to the relationship between cognitive science and literary schemes for building reader…

Normative and descriptive rationality: from nature to artifice and back

NASA Astrophysics Data System (ADS)

Besold, T. R.; Uckelman, S. L.

2018-03-01

Rationality plays a key role in both the study of human reasoning and Artificial Intelligence (AI). Certain notions of rationality have been adopted in AI as guides for the development of intelligent machines and these notions have been given a normative function. The notions of rationality in AI are often taken to be closely related to conceptions of rationality in human contexts. In this paper, we argue that the normative role of rationality differs in the human and artificial contexts. While rationality in human-focused fields of study is normative, prescribing how humans ought to reason, the normative conception in AI is built on a notion of human rationality which is descriptive, not normative, in the human context, as AI aims at building agents which reason as humans do. In order to make this point, we review prominent notions of rationality used in psychology, cognitive science, and (the history of) philosophy, as well as in AI, and discuss some factors that contributed to rationality being assigned the differing normative statuses in the differing fields of study. We argue that while 'rationality' is a normative notion in both AI and in human reasoning, the normativity of the AI conception of 'rationality' is grounded in a descriptive account of human rationality.

Learning and liking of melody and harmony: further studies in artificial grammar learning.

PubMed

Loui, Psyche

2012-10-01

Much of what we know and love about music is based on implicitly acquired mental representations of musical pitches and the relationships between them. While previous studies have shown that these mental representations of music can be acquired rapidly and can influence preference, it is still unclear which aspects of music influence learning and preference formation. This article reports two experiments that use an artificial musical system to examine two questions: (1) which aspects of music matter most for learning, and (2) which aspects of music matter most for preference formation. Two aspects of music are tested: melody and harmony. In Experiment 1 we tested the learning and liking of a new musical system that is manipulated melodically so that only some of the possible conditional probabilities between successive notes are presented. In Experiment 2 we administered the same tests for learning and liking, but we used a musical system that is manipulated harmonically to eliminate the property of harmonic whole-integer ratios between pitches. Results show that disrupting melody (Experiment 1) disabled the learning of music without disrupting preference formation, whereas disrupting harmony (Experiment 2) does not affect learning and memory but disrupts preference formation. Results point to a possible dissociation between learning and preference in musical knowledge. Copyright © 2012 Cognitive Science Society, Inc.

Towards Machine Learning of Motor Skills

NASA Astrophysics Data System (ADS)

Peters, Jan; Schaal, Stefan; Schölkopf, Bernhard

Autonomous robots that can adapt to novel situations has been a long standing vision of robotics, artificial intelligence, and cognitive sciences. Early approaches to this goal during the heydays of artificial intelligence research in the late 1980s, however, made it clear that an approach purely based on reasoning or human insights would not be able to model all the perceptuomotor tasks that a robot should fulfill. Instead, new hope was put in the growing wake of machine learning that promised fully adaptive control algorithms which learn both by observation and trial-and-error. However, to date, learning techniques have yet to fulfill this promise as only few methods manage to scale into the high-dimensional domains of manipulator robotics, or even the new upcoming trend of humanoid robotics, and usually scaling was only achieved in precisely pre-structured domains. In this paper, we investigate the ingredients for a general approach to motor skill learning in order to get one step closer towards human-like performance. For doing so, we study two major components for such an approach, i.e., firstly, a theoretically well-founded general approach to representing the required control structures for task representation and execution and, secondly, appropriate learning algorithms which can be applied in this setting.

Optical Inference Machines

DTIC Science & Technology

1988-06-27

de olf nessse end Id e ;-tl Sb ieeI smleo) ,Optical Artificial Intellegence ; Optical inference engines; Optical logic; Optical informationprocessing...common. They arise in areas such as expert systems and other artificial intelligence systems. In recent years, the computer science language PROLOG has...cal processors should in principle be well suited for : I artificial intelligence applications. In recent years, symbolic logic processing. , the

Science anxiety and social cognitive factors predicting STEM career aspirations of high school freshmen in general science class

NASA Astrophysics Data System (ADS)

Skells, Kristin Marie

Extant data was used to consider the association between science anxiety, social cognitive factors and STEM career aspirations of high school freshmen in general science classes. An adapted model based on social cognitive career theory (SCCT) was used to consider these relationships, with science anxiety functioning as a barrier in the model. The study assessed the following research questions: (1) Do social cognitive variables relate in the expected way to STEM career aspirations based on SCCT for ninth graders taking general science classes? (2) Is there an association between science anxiety and outcomes and processes identified in the SCCT model for ninth graders taking general science classes? (3) Does gender moderate these relationships? Results indicated that support was found for many of the central tenants of the SCCT model. Science anxiety was associated with prior achievement, self-efficacy, and science interest, although it did not relate directly to STEM career goals. Gender was found to moderate only the relationship between prior achievement and science self-efficacy.

The Implications of the Cognitive Sciences for the Relation Between Religion and Science Education: The Case of Evolutionary Theory

NASA Astrophysics Data System (ADS)

Blancke, Stefaan; De Smedt, Johan; De Cruz, Helen; Boudry, Maarten; Braeckman, Johan

2012-08-01

This paper discusses the relationship between religion and science education in the light of the cognitive sciences. We challenge the popular view that science and religion are compatible, a view that suggests that learning and understanding evolutionary theory has no effect on students' religious beliefs and vice versa. We develop a cognitive perspective on how students manage to reconcile evolutionary theory with their religious beliefs. We underwrite the claim developed by cognitive scientists and anthropologists that religion is natural because it taps into people's intuitive understanding of the natural world which is constrained by essentialist, teleological and intentional biases. After contrasting the naturalness of religion with the unnaturalness of science, we discuss the difficulties cognitive and developmental scientists have identified in learning and accepting evolutionary theory. We indicate how religious beliefs impede students' understanding and acceptance of evolutionary theory. We explore a number of options available to students for reconciling an informed understanding of evolutionary theory with their religious beliefs. To conclude, we discuss the implications of our account for science and biology teachers.

Sci-Fi Science.

ERIC Educational Resources Information Center

Freudenrich, Craig C.

2000-01-01

Recommends using science fiction television episodes, novels, and films for teaching science and motivating students. Studies Newton's Law of Motion, principles of relativity, journey to Mars, interplanetary trajectories, artificial gravity, and Martian geology. Discusses science fiction's ability to capture student interest and the advantages of…

"Vague and artificial": the historically elusive distinction between pure and applied science.

PubMed

Gooday, Graeme

2012-09-01

This essay argues for the historicity of applied science as a contested category within laissez-faire Victorian British science. This distinctively pre-twentieth-century notion of applied science as a self-sustaining, autonomous enterprise was thrown into relief from the 1880s by a campaign on the part of T. H. Huxley and his followers to promote instead the primacy of "pure" science. Their attempt to relegate applied science to secondary status involved radically reconfiguring it as the mere application of pre-existing pure science. This new notion of extrinsically funded pure science that would produce only contingently future social benefits as a mere by-product came under pressure during World War I, when military priorities focused attention once again on science for immediate utility. This threatened the Cambridge-based promoters of self-referential pure science who collectively published Science and the Nation in 1917. Yet most contributors to this work discussed forms of "applied" science that had no prior "pure" form. Even the U.K.'s leading government scientist, Lord Moulton, dismissed the book's provocative distinction between pure and applied science as unhelpfully "vague and artificial."

The Effects of Cognitive Conflict Management on Cognitive Development and Science Achievement

ERIC Educational Resources Information Center

Budiman, Zainol Badli; Halim, Lilia; Mohd Meerah, Subahan; Osman, Kamisah

2014-01-01

Three teaching methods were compared in this study, namely a Cognitive Conflict Management Module (CCM) that is infused into Cognitive Acceleration through Science Education (CASE), (Module A) CASE without CCM (Module B) and a conventional teaching method. This study employed a pre- and post-test quasi-experimental design using non-equivalent…

Knowledge and Regulation of Cognition in College Science Students

ERIC Educational Resources Information Center

Roshanaei, Mehrnaz

2014-01-01

The research focused on three issues in college science students: whether there was empirical support for the two factor (knowledge of cognition and regulation of cognition) view of metacognition, whether the two factors were related to each other, and whether either of the factors was related to empirical measures of cognitive and metacognitive…

What Cognitive Science May Learn from Instructional Design: A Case Study in Introductory Computer Programming.

ERIC Educational Resources Information Center

van Merrienboer, Jeroen J. G.

The contributions of instructional design to cognitive science are discussed. It is argued that both sciences have their own object of study, but share a common interest in human cognition and performance as part of instructional systems. From a case study based on experience in teaching introductory computer programming, it is concluded that both…

On the Science of Embodied Cognition in the 2010s: Research Questions, Appropriate Reductionism, and Testable Explanations

ERIC Educational Resources Information Center

Nunez, Rafael

2012-01-01

"The Journal of the Learning Sciences" has devoted this special issue to the study of embodied cognition (as it applies to mathematics), a topic that for several decades has gained attention in the cognitive sciences and in mathematics education, in particular. In this commentary, the author aims to address crucial questions in embodied…

Cognitive Science and Science Education.

ERIC Educational Resources Information Center

Carey, Susan

1986-01-01

The premise behind the cognitive approach to teaching is that understanding results when new learning is integrated with existing knowledge. But the goal of science instruction is to replace existing ideas with new theories. Current research in science education seeks to resolve these conflicting instructional approaches. (Author/VM)

Cognitive apprenticeship in health sciences education: a qualitative review.

PubMed

Lyons, Kayley; McLaughlin, Jacqueline E; Khanova, Julia; Roth, Mary T

2017-08-01

Cognitive apprenticeship theory emphasizes the process of making expert thinking "visible" to students and fostering the cognitive and meta-cognitive processes required for expertise. The purpose of this review was to evaluate the use of cognitive apprenticeship theory with the primary aim of understanding how and to what extent the theory has been applied to the design, implementation, and analysis of education in the health sciences. The initial search yielded 149 articles, with 45 excluded because they contained the term "cognitive apprenticeship" only in reference list. The remaining 104 articles were categorized using a theory talk coding scheme. An in depth qualitative synthesis and review was conducted for the 26 articles falling into the major theory talk category. Application of cognitive apprenticeship theory tended to focus on the methods dimension (e.g., coaching, mentoring, scaffolding), with some consideration for the content and sociology dimensions. Cognitive apprenticeship was applied in various disciplines (e.g., nursing, medicine, veterinary) and educational settings (e.g., clinical, simulations, online). Health sciences education researchers often used cognitive apprenticeship to inform instructional design and instrument development. Major recommendations from the literature included consideration for contextual influences, providing faculty development, and expanding application of the theory to improve instructional design and student outcomes. This body of research provides critical insight into cognitive apprenticeship theory and extends our understanding of how to develop expert thinking in health sciences students. New research directions should apply the theory into additional aspects of health sciences educational research, such as classroom learning and interprofessional education.

Artificial Intelligence, Machine Learning, Deep Learning, and Cognitive Computing: What Do These Terms Mean and How Will They Impact Health Care?

PubMed

Bini, Stefano A

2018-02-27

This article was presented at the 2017 annual meeting of the American Association of Hip and Knee Surgeons to introduce the members gathered as the audience to the concepts behind artificial intelligence (AI) and the applications that AI can have in the world of health care today. We discuss the origin of AI, progress to machine learning, and then discuss how the limits of machine learning lead data scientists to develop artificial neural networks and deep learning algorithms through biomimicry. We will place all these technologies in the context of practical clinical examples and show how AI can act as a tool to support and amplify human cognitive functions for physicians delivering care to increasingly complex patients. The aim of this article is to provide the reader with a basic understanding of the fundamentals of AI. Its purpose is to demystify this technology for practicing surgeons so they can better understand how and where to apply it. Copyright © 2018 Elsevier Inc. All rights reserved.

Technology as Teammate: Examining the Role of External Cognition in Support of Team Cognitive Processes

PubMed Central

Fiore, Stephen M.; Wiltshire, Travis J.

2016-01-01

In this paper we advance team theory by describing how cognition occurs across the distribution of members and the artifacts and technology that support their efforts. We draw from complementary theorizing coming out of cognitive engineering and cognitive science that views forms of cognition as external and extended and integrate this with theorizing on macrocognition in teams. Two frameworks are described that provide the groundwork for advancing theory and aid in the development of more precise measures for understanding team cognition via focus on artifacts and the technologies supporting their development and use. This includes distinctions between teamwork and taskwork and the notion of general and specific competencies from the organizational sciences along with the concepts of offloading and scaffolding from the cognitive sciences. This paper contributes to the team cognition literature along multiple lines. First, it aids theory development by synthesizing a broad set of perspectives on the varied forms of cognition emerging in complex collaborative contexts. Second, it supports research by providing diagnostic guidelines to study how artifacts are related to team cognition. Finally, it supports information systems designers by more precisely describing how to conceptualize team-supporting technology and artifacts. As such, it provides a means to more richly understand process and performance as it occurs within sociotechnical systems. Our overarching objective is to show how team cognition can both be more clearly conceptualized and more precisely measured by integrating theory from cognitive engineering and the cognitive and organizational sciences. PMID:27774074

Technology as Teammate: Examining the Role of External Cognition in Support of Team Cognitive Processes.

PubMed

Fiore, Stephen M; Wiltshire, Travis J

2016-01-01

In this paper we advance team theory by describing how cognition occurs across the distribution of members and the artifacts and technology that support their efforts. We draw from complementary theorizing coming out of cognitive engineering and cognitive science that views forms of cognition as external and extended and integrate this with theorizing on macrocognition in teams. Two frameworks are described that provide the groundwork for advancing theory and aid in the development of more precise measures for understanding team cognition via focus on artifacts and the technologies supporting their development and use. This includes distinctions between teamwork and taskwork and the notion of general and specific competencies from the organizational sciences along with the concepts of offloading and scaffolding from the cognitive sciences. This paper contributes to the team cognition literature along multiple lines. First, it aids theory development by synthesizing a broad set of perspectives on the varied forms of cognition emerging in complex collaborative contexts. Second, it supports research by providing diagnostic guidelines to study how artifacts are related to team cognition. Finally, it supports information systems designers by more precisely describing how to conceptualize team-supporting technology and artifacts. As such, it provides a means to more richly understand process and performance as it occurs within sociotechnical systems. Our overarching objective is to show how team cognition can both be more clearly conceptualized and more precisely measured by integrating theory from cognitive engineering and the cognitive and organizational sciences.

Effects of Web Based Inquiry Science Environment on Cognitive Outcomes in Biological Science in Correlation to Emotional Intelligence

ERIC Educational Resources Information Center

Manoj, T. I.; Devanathan, S.

2010-01-01

This research study is the report of an experiment conducted to find out the effects of web based inquiry science environment on cognitive outcomes in Biological science in correlation to Emotional intelligence. Web based inquiry science environment (WISE) provides a platform for creating inquiry-based science projects for students to work…

The Classification, Detection and Handling of Imperfect Theory Problems.

DTIC Science & Technology

1987-04-20

Explanation-Based Learning: Failure-Driven Schema Refinement." Proceedings of the Third IEEE Conference on Artificial Intelligence Applications . Orlando...A. Rajamoney. Gerald F. DeJong Artificial Intelligence Research Group " . Coordinated Science Laboratory " University of Illinois at Urbana-Champaign...Urbana. IL 61801 . April 1987 ABSTRACT This paper also appears in the Proceedings of the Tenth International Conference on Artificial Intelligence

Magnetoresistance in Permalloy Connected Brickwork Artificial Spin Ice

NASA Astrophysics Data System (ADS)

Park, Jungsik; Le, Brian; Chern, Gia-Wei; Watts, Justin; Leighton, Chris; Schiffer, Peter

Artificial spin ice refers to a two-dimensional array of elongated ferromagnetic elements in which frustrated lattice geometry induces novel magnetic behavior. Here we examine room-temperature magnetoresistance properties of connected permalloy (Ni81Fe19) brickwork artificial spin ice. Both the longitudinal and transverse magnetoresistance of the nanostructure demonstrate an angular sensitivity that has not been previously observed. The observed magnetoresistance behavior can be explained from micromagnetic modelling using an anisotropic magnetoresistance model (AMR). As part of this study, we find that the ground state of the connected brickwork artificial spin ice can be reproducibly created by a simple field sweep in a narrow range of angles, and manifests in the magnetotransport with a distinct signal. Supported by the US Department of Energy, Office of Basic Energy Sciences, Materials Sciences and Engineering Division under Grant Number DE-SC0010778. Work at the University of Minnesota was supported by the NSF MRSEC under award DMR-1420013, and DMR-1507048.

Simulation as an Engine of Physical Scene Understanding

DTIC Science & Technology

2013-11-05

critical to the origins of intelligence : Researchers in developmental psychology, language, animal cognition, and artificial intelligence (2–6) con- sider...implemented computationally in classic artificial intelligence systems (18–20). However, these systems have not attempted to engage with physical scene un...N00014-09-0124, N00014-07-1-0937, and 1015GNA126; by Qualcomm; and by Intelligence Advanced Research Project Activity Grant D10PC20023. 1. Marr D (1982

Inequity aversion and the evolution of cooperation

NASA Astrophysics Data System (ADS)

Ahmed, Asrar; Karlapalem, Kamalakar

2014-02-01

Evolution of cooperation is a widely studied problem in biology, social science, economics, and artificial intelligence. Most of the existing approaches that explain cooperation rely on some notion of direct or indirect reciprocity. These reciprocity based models assume agents recognize their partner and know their previous interactions, which requires advanced cognitive abilities. In this paper we are interested in developing a model that produces cooperation without requiring any explicit memory of previous game plays. Our model is based on the notion of inequity aversion, a concept introduced within behavioral economics, whereby individuals care about payoff equality in outcomes. Here we explore the effect of using income inequality to guide partner selection and interaction. We study our model by considering both the well-mixed and the spatially structured population and present the conditions under which cooperation becomes dominant. Our results support the hypothesis that inequity aversion promotes cooperative relationship among nonkin.

Inequity aversion and the evolution of cooperation.

PubMed

Ahmed, Asrar; Karlapalem, Kamalakar

2014-02-01

Evolution of cooperation is a widely studied problem in biology, social science, economics, and artificial intelligence. Most of the existing approaches that explain cooperation rely on some notion of direct or indirect reciprocity. These reciprocity based models assume agents recognize their partner and know their previous interactions, which requires advanced cognitive abilities. In this paper we are interested in developing a model that produces cooperation without requiring any explicit memory of previous game plays. Our model is based on the notion of inequity aversion, a concept introduced within behavioral economics, whereby individuals care about payoff equality in outcomes. Here we explore the effect of using income inequality to guide partner selection and interaction. We study our model by considering both the well-mixed and the spatially structured population and present the conditions under which cooperation becomes dominant. Our results support the hypothesis that inequity aversion promotes cooperative relationship among nonkin.

The Interaction of Language-Specific and Universal Factors During the Acquisition of Morphophonemic Alternations With Exceptions.

PubMed

Baer-Henney, Dinah; Kügler, Frank; van de Vijver, Ruben

2015-09-01

Using the artificial language paradigm, we studied the acquisition of morphophonemic alternations with exceptions by 160 German adult learners. We tested the acquisition of two types of alternations in two regularity conditions while additionally varying length of training. In the first alternation, a vowel harmony, backness of the stem vowel determines backness of the suffix. This process is grounded in substance (phonetic motivation), and this universal phonetic factor bolsters learning a generalization. In the second alternation, tenseness of the stem vowel determines backness of the suffix vowel. This process is not based in substance, but it reflects a phonotactic property of German and our participants benefit from this language-specific factor. We found that learners use both cues, while substantive bias surfaces mainly in the most unstable situation. We show that language-specific and universal factors interact in learning. Copyright © 2014 Cognitive Science Society, Inc.

Moral principles or consumer preferences? Alternative framings of the trolley problem.

PubMed

Rai, Tage S; Holyoak, Keith J

2010-03-01

We created paired moral dilemmas with minimal contrasts in wording, a research strategy that has been advocated as a way to empirically establish principles operative in a domain-specific moral psychology. However, the candidate "principles" we tested were not derived from work in moral philosophy, but rather from work in the areas of consumer choice and risk perception. Participants were paradoxically less likely to choose an action that sacrifices one life to save others when they were asked to provide more reasons for doing so (Experiment 1), and their willingness to sacrifice lives depended not only on how many lives would be saved, but on the number of lives at risk (Experiment 2). The latter effect was also found in a within-subjects design (Experiment 3). These findings suggest caution in the use of artificial dilemmas as a key testbed for revealing principled bases for moral judgment. Copyright © 2009 Cognitive Science Society, Inc.

Semantic Coherence Facilitates Distributional Learning.

PubMed

Ouyang, Long; Boroditsky, Lera; Frank, Michael C

2017-04-01

Computational models have shown that purely statistical knowledge about words' linguistic contexts is sufficient to learn many properties of words, including syntactic and semantic category. For example, models can infer that "postman" and "mailman" are semantically similar because they have quantitatively similar patterns of association with other words (e.g., they both tend to occur with words like "deliver," "truck," "package"). In contrast to these computational results, artificial language learning experiments suggest that distributional statistics alone do not facilitate learning of linguistic categories. However, experiments in this paradigm expose participants to entirely novel words, whereas real language learners encounter input that contains some known words that are semantically organized. In three experiments, we show that (a) the presence of familiar semantic reference points facilitates distributional learning and (b) this effect crucially depends both on the presence of known words and the adherence of these known words to some semantic organization. Copyright © 2016 Cognitive Science Society, Inc.

Multimodal communication in animals, humans and robots: an introduction to perspectives in brain-inspired informatics.

PubMed

Wermter, S; Page, M; Knowles, M; Gallese, V; Pulvermüller, F; Taylor, J

2009-03-01

Recent years have seen convergence in research on brain mechanisms and neurocomputational approaches, culminating in the creation of a new generation of robots whose artificial "brains" respect neuroscience principles and whose "cognitive" systems venture into higher cognitive domains such as planning and action sequencing, complex object and concept processing, and language. The present article gives an overview of selected projects in this general multidisciplinary field. The work reviewed centres on research funded by the EU in the context of the New and Emergent Science and Technology, NEST, funding scheme highlighting the topic "What it means to be human". Examples of such projects include learning by imitation (Edici project), examining the origin of human rule-based reasoning (Far), studying the neural origins of language (Neurocom), exploring the evolutionary origins of the human mind (Pkb140404), researching into verbal and non-verbal communication (Refcom), using and interpreting signs (Sedsu), characterising human language by structural complexity (Chlasc), and representing abstract concepts (Abstract). Each of the communication-centred research projects revealed individual insights; however, there had been little overall analysis of results and hypotheses. In the Specific Support Action Nestcom, we proposed to analyse some NEST projects focusing on the central question "What it means to communicate" and to review, understand and integrate the results of previous communication-related research, in order to develop and communicate multimodal experimental hypotheses for investigation by future projects. The present special issue includes a range of papers on the interplay between neuroinformatics, brain science and robotics in the general area of higher cognitive functions and multimodal communication. These papers extend talks given at the NESTCOM workshops, at ICANN (http://www.his.sunderland.ac.uk/nestcom/workshop/icann.html) in Porto and at the first meeting of the Federation of the European Societies of Neuropsychology in Edinburgh in 2008 (http://www.his.sunderland.ac.uk/nestcom/workshop/esn.html). We hope that the collection will give a vivid insight into current trends in the field.

An Exploration of Students' Science Learning Interest Related to Their Cognitive Anxiety, Cognitive Load, Self-Confidence and Learning Progress Using Inquiry-Based Learning With an iPad

NASA Astrophysics Data System (ADS)

Hong, Jon-Chao; Hwang, Ming-Yueh; Tai, Kai-Hsin; Tsai, Chi-Ruei

2017-12-01

Based on the cognitive-affective theory, the present study designed a science inquiry learning model, predict-observe-explain (POE), and implemented it in an app called "WhyWhy" to examine the effectiveness of students' science inquiry learning practice. To understand how POE can affect the cognitive-affective learning process, as well as the learning progress, a pretest and a posttest were given to 152 grade 5 elementary school students. The students practiced WhyWhy during six sessions over 6 weeks, and data related to interest in learning science (ILS), cognitive anxiety (CA), and extraneous cognitive load (ECL) were collected and analyzed through confirmatory factor analysis with structure equation modeling. The results showed that students with high ILS have low CA and ECL. In addition, the results also indicated that students with a high level of self-confidence enhancement showed significant improvement in the posttest. The implications of this study suggest that by using technology-enhanced science learning, the POE model is a practical approach to motivate students to learn.

Bridging views in cinema: a review of the art and science of view integration.

PubMed

Levin, Daniel T; Baker, Lewis J

2017-09-01

Recently, there has been a surge of interest in the relationship between film and cognitive science. This is reflected in a new science of cinema that can help us both to understand this art form, and to produce new insights about cognition and perception. In this review, we begin by describing how the initial development of cinema involved close observation of audience response. This allowed filmmakers to develop an informal theory of visual cognition that helped them to isolate and creatively recombine fundamental elements of visual experience. We review research exploring naturalistic forms of visual perception and cognition that have opened the door to a productive convergence between the dynamic visual art of cinema and science of visual cognition that can enrich both. In particular, we discuss how parallel understandings of view integration in cinema and in cognitive science have been converging to support a new understanding of meaningful visual experience. WIREs Cogn Sci 2017, 8:e1436. doi: 10.1002/wcs.1436 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

Visual analytics as a translational cognitive science.

PubMed

Fisher, Brian; Green, Tera Marie; Arias-Hernández, Richard

2011-07-01

Visual analytics is a new interdisciplinary field of study that calls for a more structured scientific approach to understanding the effects of interaction with complex graphical displays on human cognitive processes. Its primary goal is to support the design and evaluation of graphical information systems that better support cognitive processes in areas as diverse as scientific research and emergency management. The methodologies that make up this new field are as yet ill defined. This paper proposes a pathway for development of visual analytics as a translational cognitive science that bridges fundamental research in human/computer cognitive systems and design and evaluation of information systems in situ. Achieving this goal will require the development of enhanced field methods for conceptual decomposition of human/computer cognitive systems that maps onto laboratory studies, and improved methods for conducting laboratory investigations that might better map onto real-world cognitive processes in technology-rich environments. Copyright © 2011 Cognitive Science Society, Inc.

Problem representation and variation in the forecasts of ’political experts’

DTIC Science & Technology

2001-06-01

artificial intelligence classification of the themes that were used by the Presidential Commission on Women in Combat. Psychological constraints to...In contrast, controls for expert-novice differences is standard practice in psychology . Cognitive psychologists who have studied how experts and...participant=s Athink aloud@ analysis from Alevel of verbosity.@ By summarizing verbatim statements associated with free-hand cognitive diagrams it

Multilayer Networks of Self-Interested Adaptive Units.

DTIC Science & Technology

1987-07-01

T. J. Sejnowski. A learning algorithm for Boltzmann machines. Cognitive Science, 9:147-169, 1985. 121 S. Amarel. Problems of Representation in...Barto and C. W. Anderson. Structural learning in connectionist sys- tems. In Proceedings of the Seventh Annual Conference of the Cognitive Science...E. Hinton and T. J. Sejnowski. Analyzing cooperative computation. In Proceedings of the Fifth Annual Conference of the Cognitive Science Society

Mathematical Idea Analysis: What Embodied Cognitive Science Can Say about the Human Nature of Mathematics.

ERIC Educational Resources Information Center

Nunez, Rafael E.

This paper gives a brief introduction to a discipline called the cognitive science of mathematics. The theoretical background of the arguments is based on embodied cognition and findings in cognitive linguistics. It discusses Mathematical Idea Analysis, a set of techniques for studying implicit structures in mathematics. Particular attention is…

Who Chooses STEM Careers? Using A Relative Cognitive Strength and Interest Model to Predict Careers in Science, Technology, Engineering, and Mathematics.

PubMed

Wang, Ming-Te; Ye, Feifei; Degol, Jessica Lauren

2017-08-01

Career aspirations in science, technology, engineering, and mathematics (STEM) are formulated in adolescence, making the high school years a critical time period for identifying the cognitive and motivational factors that increase the likelihood of future STEM employment. While past research has mainly focused on absolute cognitive ability levels in math and verbal domains, the current study tested whether relative cognitive strengths and interests in math, science, and verbal domains in high school were more accurate predictors of STEM career decisions. Data were drawn from a national longitudinal study in the United States (N = 1762; 48 % female; the first wave during ninth grade and the last wave at age 33). Results revealed that in the high-verbal/high-math/high-science ability group, individuals with higher science task values and lower orientation toward altruism were more likely to select STEM occupations. In the low-verbal/moderate-math/moderate-science ability group, individuals with higher math ability and higher math task values were more likely to select STEM occupations. The findings suggest that youth with asymmetrical cognitive ability profiles are more likely to select careers that utilize their cognitive strengths rather than their weaknesses, while symmetrical cognitive ability profiles may grant youth more flexibility in their options, allowing their interests and values to guide their career decisions.

Interactions between Classroom Discourse, Teacher Questioning, and Student Cognitive Engagement in Middle School Science

ERIC Educational Resources Information Center

Smart, Julie B.; Marshall, Jeff C.

2013-01-01

Classroom discourse can affect various aspects of student learning in science. The present study examines interactions between classroom discourse, specifically teacher questioning, and related student cognitive engagement in middle school science. Observations were conducted throughout the school year in 10 middle school science classrooms using…

On the Need for Artificial Intelligence and Advanced Test and Evaluation Methods for Space Exploration

NASA Astrophysics Data System (ADS)

Scheidt, D. H.; Hibbitts, C. A.; Chen, M. H.; Paxton, L. J.; Bekker, D. L.

2017-02-01

Implementing mature artificial intelligence would create the ability to significantly increase the science return from a mission, while potentially saving costs in mission and instrument operations, and solving currently intractable problems.

Cognitive abilities of health and art college students a pilot study.

PubMed

AlAbdulwahab, Sami S; Kachanathu, Shaji John; AlKhamees, Abdullah K

2016-05-01

[Purpose] The selection of a college major is a struggle that high school students undergo every year; however, there is a dearth of studies examining the role of cognitive ability tests as a tool for determining the aptitude of prospective students. Hence, the purpose of this study was to assess cognitive ability differences among students. [Subjects and Methods] A convenience sample of 60 college students (30 health science and 30 art students) with a mean age of 19 ± 1.6 years, voluntarily participated in this study. Cognitive ability was assessed using the self-administered Cognitive Assessment of Minnesota (CAM) scale under the supervision of a researcher. [Results] The findings indicated that there was a significant cognitive ability difference between health science and art students, especially in the cognitive components of knowledge, calculation, and thinking. However, the difference in the social cognitive component of both the health science and art students was not significant. [Conclusion] The results indicate that the health science students' cognitive abilities were better than those of the art students. This finding implies that it is important for high school graduates to undertake a cognitive ability assessment prior to choosing a subject major. Hence, it is recommended that cognitive scales should be included as an aptitude assessment tool for the decision-makers and prospective students to determine an appropriate career, since it might reduce the percentage of university drop-out ratio.

A medical prescription for a mind

NASA Astrophysics Data System (ADS)

Simões da Fonseca, J.

1999-03-01

The author who is an expert in clinical psychiatry deals with the problem of modeling human Mind the way physicians implicitly use when their profession renders necessary to intervene to help or even cure patients. If physicists, mathematicians or cognitive science specialists and engineers may propose artificial designs for a mind, psychiatrists and psychologists have developed reliable diagnostic systems for the classification of normal or else psychopathological states. Usually in Psychiatry it is not made any use of an algorithmic approach to describe and characterize psychological processes during cognitive, perceptual, emotional, motivational processes or else anticipatory processes, distinct types of memory, learning processes, etc. Differently from what is mentioned in Neuropsychological literature the author and his group were able to find a significant and consistent relationship between the level of ostensive expression of symptoms and competence in interpretation of information carried by verbal communication during the simulation of social interactions by restrict groups of experimenters. Furthermore it is shown how dendro-dendritic models of neural processing are adequate to represent symbolic processes performed by local operators in the Cortex, as well as the usefulness of models of chemical reactors either batch reactors or else flow plug reactors to represent virtual neural networks capable of clarifying some aspects of cognition and of the structure of the Self. Finally many episodes of the life of the late Warren Sturgis McCulloch are recalled as attribute of gratitude of the author who was his before the last student.

The Effects of Item Format and Cognitive Domain on Students' Science Performance in TIMSS 2011

NASA Astrophysics Data System (ADS)

Liou, Pey-Yan; Bulut, Okan

2017-12-01

The purpose of this study was to examine eighth-grade students' science performance in terms of two test design components, item format, and cognitive domain. The portion of Taiwanese data came from the 2011 administration of the Trends in International Mathematics and Science Study (TIMSS), one of the major international large-scale assessments in science. The item difficulty analysis was initially applied to show the proportion of correct items. A regression-based cumulative link mixed modeling (CLMM) approach was further utilized to estimate the impact of item format, cognitive domain, and their interaction on the students' science scores. The results of the proportion-correct statistics showed that constructed-response items were more difficult than multiple-choice items, and that the reasoning cognitive domain items were more difficult compared to the items in the applying and knowing domains. In terms of the CLMM results, students tended to obtain higher scores when answering constructed-response items as well as items in the applying cognitive domain. When the two predictors and the interaction term were included together, the directions and magnitudes of the predictors on student science performance changed substantially. Plausible explanations for the complex nature of the effects of the two test-design predictors on student science performance are discussed. The results provide practical, empirical-based evidence for test developers, teachers, and stakeholders to be aware of the differential function of item format, cognitive domain, and their interaction in students' science performance.

Motor cognition-motor semantics: action perception theory of cognition and communication.

PubMed

Pulvermüller, Friedemann; Moseley, Rachel L; Egorova, Natalia; Shebani, Zubaida; Boulenger, Véronique

2014-03-01

A new perspective on cognition views cortical cell assemblies linking together knowledge about actions and perceptions not only as the vehicles of integrated action and perception processing but, furthermore, as a brain basis for a wide range of higher cortical functions, including attention, meaning and concepts, sequences, goals and intentions, and even communicative social interaction. This article explains mechanisms relevant to mechanistic action perception theory, points to concrete neuronal circuits in brains along with artificial neuronal network simulations, and summarizes recent brain imaging and other experimental data documenting the role of action perception circuits in cognition, language and communication. © 2013 Published by Elsevier Ltd.

Artificial Muscles Based on Electroactive Polymers as an Enabling Tool in Biomimetics

NASA Technical Reports Server (NTRS)

Bar-Cohen, Y.

2007-01-01

Evolution has resolved many of nature's challenges leading to working and lasting solutions that employ principles of physics, chemistry, mechanical engineering, materials science, and many other fields of science and engineering. Nature's inventions have always inspired human achievements leading to effective materials, structures, tools, mechanisms, processes, algorithms, methods, systems, and many other benefits. Some of the technologies that have emerged include artificial intelligence, artificial vision, and artificial muscles, where the latter is the moniker for electroactive polymers (EAPs). To take advantage of these materials and make them practical actuators, efforts are made worldwide to develop capabilities that are critical to the field infrastructure. Researchers are developing analytical model and comprehensive understanding of EAP materials response mechanism as well as effective processing and characterization techniques. The field is still in its emerging state and robust materials are still not readily available; however, in recent years, significant progress has been made and commercial products have already started to appear. In the current paper, the state-of-the-art and challenges to artificial muscles as well as their potential application to biomimetic mechanisms and devices are described and discussed.

The Interdisciplinarity of Collaborations in Cognitive Science.

PubMed

Bergmann, Till; Dale, Rick; Sattari, Negin; Heit, Evan; Bhat, Harish S

2017-07-01

We introduce a new metric for interdisciplinarity, based on co-author publication history. A published article that has co-authors with quite different publication histories can be deemed relatively "interdisciplinary," in that the article reflects a convergence of previous research in distinct sets of publication outlets. In recent work, we have shown that this interdisciplinarity metric can predict citations. Here, we show that the journal Cognitive Science tends to contain collaborations that are relatively high on this interdisciplinarity metric, at about the 80th percentile of all journals across both social and natural sciences. Following on Goldstone and Leydesdorff (2006), we describe how scientometric tools provide a valuable means of assessing the role of cognitive science in broader scientific work, and also as a tool to investigate teamwork and distributed cognition. We describe how data-driven metrics of this kind may facilitate this exploration without relying upon rapidly changing discipline and topic keywords associated with publications. Copyright © 2016 Cognitive Science Society, Inc.

Using a multilevel mediation model to examine the effects of National Board Certified Teachers on high school science students' cognitive engagement

NASA Astrophysics Data System (ADS)

Zaleski, Diana Janet

2011-12-01

The National Board for Professional Teaching Standards claims to identify effective educators through their certification process. However, research concerning National Board Certified Teachers (NBCT) is inconclusive. The purpose of this study was to examine the direct and indirect effects of NBCT on the cognitive engagement of high school science students. Multilevel mediation modeling was used to examine the direct and indirect effects of teacher certification on students' cognitive engagement in science and whether students' expectancies for success and perceptions of task value mediate these effects. Students of NBCT were found to be more cognitively engaged in science than students of non-NBCT; however, students' expectancies for success and perceptions of task value did not mediate this relationship. In addition, students with more positive expectancies for success and perceptions of task value were more cognitively engaged in science. These findings support the proposition that the National Board certification process at least identifies effective educators.

The cognitive science of visual-spatial displays: implications for design.

PubMed

Hegarty, Mary

2011-07-01

This paper reviews cognitive science perspectives on the design of visual-spatial displays and introduces the other papers in this topic. It begins by classifying different types of visual-spatial displays, followed by a discussion of ways in which visual-spatial displays augment cognition and an overview of the perceptual and cognitive processes involved in using displays. The paper then argues for the importance of cognitive science methods to the design of visual displays and reviews some of the main principles of display design that have emerged from these approaches to date. Cognitive scientists have had good success in characterizing the performance of well-defined tasks with relatively simple visual displays, but many challenges remain in understanding the use of complex displays for ill-defined tasks. Current research exemplified by the papers in this topic extends empirical approaches to new displays and domains, informs the development of general principles of graphic design, and addresses current challenges in display design raised by the recent explosion in availability of complex data sets and new technologies for visualizing and interacting with these data. Copyright © 2011 Cognitive Science Society, Inc.

A Framework for Relating Cognitive to Neural Systems. Cognitive Science Program, Technical Report No. 84-2.

ERIC Educational Resources Information Center

Posner, Michael I.

This paper reviews the aspects of cognitive science that relate best to using electrical and magnetic recording to understand the function of brain systems. It outlines a framework for relating cognitive activities of daily life (typing, reading) to underlying neural systems. The framework uses five levels of analysis: task, elementary operations,…

The Implications of the Cognitive Sciences for the Relation between Religion and Science Education: The Case of Evolutionary Theory

ERIC Educational Resources Information Center

Blancke, Stefaan; De Smedt, Johan; De Cruz, Helen; Boudry, Maarten; Braeckman, Johan

2012-01-01

This paper discusses the relationship between religion and science education in the light of the cognitive sciences. We challenge the popular view that science and religion are compatible, a view that suggests that learning and understanding evolutionary theory has no effect on students' religious beliefs and vice versa. We develop a cognitive…

77 FR 38630 - Open Internet Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-28

... Computer Science and Co-Founder of the Berkman Center for Internet and Society, Harvard University, is... of Technology Computer Science and Artificial Intelligence Laboratory, is appointed vice-chairperson... Jennifer Rexford, Professor of Computer Science, Princeton University Dennis Roberson, Vice Provost...

Embodied Cognition and Curriculum Construction

ERIC Educational Resources Information Center

Wang, Mei-qian; Zheng, Xu-dong

2018-01-01

The disembodiment of cognitive science has resulted in curricula with disembodied concepts and practice. The emergence of the embodied cognitive science provoked public reflections on the nature of the curriculum. This has elevated the body from the "peripheral" position to the "central" position, acting as the subject in…

Online webcam-based eye tracking in cognitive science: A first look.

PubMed

Semmelmann, Kilian; Weigelt, Sarah

2018-04-01

Online experimentation is emerging in many areas of cognitive psychology as a viable alternative or supplement to classical in-lab experimentation. While performance- and reaction-time-based paradigms are covered in recent studies, one instrument of cognitive psychology has not received much attention up to now: eye tracking. In this study, we used JavaScript-based eye tracking algorithms recently made available by Papoutsaki et al. (International Joint Conference on Artificial Intelligence, 2016) together with consumer-grade webcams to investigate the potential of online eye tracking to benefit from the common advantages of online data conduction. We compared three in-lab conducted tasks (fixation, pursuit, and free viewing) with online-acquired data to analyze the spatial precision in the first two, and replicability of well-known gazing patterns in the third task. Our results indicate that in-lab data exhibit an offset of about 172 px (15% of screen size, 3.94° visual angle) in the fixation task, while online data is slightly less accurate (18% of screen size, 207 px), and shows higher variance. The same results were found for the pursuit task with a constant offset during the stimulus movement (211 px in-lab, 216 px online). In the free-viewing task, we were able to replicate the high attention attribution to eyes (28.25%) compared to other key regions like the nose (9.71%) and mouth (4.00%). Overall, we found web technology-based eye tracking to be suitable for all three tasks and are confident that the required hard- and software will be improved continuously for even more sophisticated experimental paradigms in all of cognitive psychology.

Conceptual Metaphor and Embodied Cognition in Science Learning: Introduction to Special Issue

ERIC Educational Resources Information Center

Amin, Tamer G.; Jeppsson, Fredrik; Haglund, Jesper

2015-01-01

This special issue of "International Journal of Science Education" is based on the theme "Conceptual Metaphor and Embodied Cognition in Science Learning." The idea for this issue grew out of a symposium organized on this topic at the conference of the European Science Education Research Association (ESERA) in September 2013.…

Mathematical representations in science: a cognitive-historical case history.

PubMed

Tweney, Ryan D

2009-10-01

The important role of mathematical representations in scientific thinking has received little attention from cognitive scientists. This study argues that neglect of this issue is unwarranted, given existing cognitive theories and laws, together with promising results from the cognitive historical analysis of several important scientists. In particular, while the mathematical wizardry of James Clerk Maxwell differed dramatically from the experimental approaches favored by Michael Faraday, Maxwell himself recognized Faraday as "in reality a mathematician of a very high order," and his own work as in some respects a re-representation of Faraday's field theory in analytic terms. The implications of the similarities and differences between the two figures open new perspectives on the cognitive role of mathematics as a learned mode of representation in science. Copyright © 2009 Cognitive Science Society, Inc.

Spiking Phineas Gage: a neurocomputational theory of cognitive-affective integration in decision making.

PubMed

Wagar, Brandon M; Thagard, Paul

2004-01-01

The authors present a neurological theory of how cognitive information and emotional information are integrated in the nucleus accumbens during effective decision making. They describe how the nucleus accumbens acts as a gateway to integrate cognitive information from the ventromedial prefrontal cortex and the hippocampus with emotional information from the amygdala. The authors have modeled this integration by a network of spiking artificial neurons organized into separate areas and used this computational model to simulate 2 kinds of cognitive-affective integration. The model simulates successful performance by people with normal cognitive-affective integration. The model also simulates the historical case of Phineas Gage as well as subsequent patients whose ability to make decisions became impeded by damage to the ventromedial prefrontal cortex.

Hoping for more: How cognitive science has and hasn't been helpful to the OCD clinician.

PubMed

Ouimet, Allison J; Ashbaugh, Andrea R; Radomsky, Adam S

2018-04-12

Cognitive-behavioural models of obsessive-compulsive disorder (OCD) stemmed from knowledge acquired from cognitive science. Researchers continue to apply basic cognitive-affective science methods to understanding OCD, with the overarching goal of improving and refining evidence-based treatments. However, the degree to which such research has contributed to this goal is unclear. We reviewed OCD research in the general areas that comprise basic cognitive science, and evaluated the degree to which it has contributed to our understanding of the development, maintenance, and treatment of OCD. We focused on studies that either compared people with and without OCD and/or used experimental psychopathology methods with human participants, and attempted to resolve some of the conflicting theories related to the importance of cognitive deficits vs. cognitive biases. Overall, we observed equivocal findings for deficits in perception, attention, memory, and executive functioning. Moreover, many so-called deficits were moderated and/or explained by OCD-relevant beliefs, highlighting the role of confidence in cognitive processes as integral to our understanding of OCD. We discussed these findings in terms of cognitive measurement, cognitive-behavioural models, and clinical applicability, and made recommendations for future research that may offer innovation and insight helpful to clinicians working to improve the symptoms and lives of people with OCD. Copyright © 2018 Elsevier Ltd. All rights reserved.

Plus or Minus 30 Years in the Language Sciences

PubMed Central

Newport, Elissa L.

2010-01-01

The language sciences – Linguistics, Psycholinguistics, and Computational Linguistics – have not been broadly represented at the Cognitive Science Society meetings of the past 30 years, but they are an important part of the heart of cognitive science. This article discusses several major themes that have dominated the controversies and consensus in the study of language and suggests the most pressing issues of the future. These themes include differences among the language science disciplines in their view of numbers and symbols and of modular and distributed cognition; and the need for an increasing prominence of questions concerning language and the brain. PMID:20730034

Artificial selection on relative brain size in the guppy reveals costs and benefits of evolving a larger brain.

PubMed

Kotrschal, Alexander; Rogell, Björn; Bundsen, Andreas; Svensson, Beatrice; Zajitschek, Susanne; Brännström, Ioana; Immler, Simone; Maklakov, Alexei A; Kolm, Niclas

2013-01-21

The large variation in brain size that exists in the animal kingdom has been suggested to have evolved through the balance between selective advantages of greater cognitive ability and the prohibitively high energy demands of a larger brain (the "expensive-tissue hypothesis"). Despite over a century of research on the evolution of brain size, empirical support for the trade-off between cognitive ability and energetic costs is based exclusively on correlative evidence, and the theory remains controversial. Here we provide experimental evidence for costs and benefits of increased brain size. We used artificial selection for large and small brain size relative to body size in a live-bearing fish, the guppy (Poecilia reticulata), and found that relative brain size evolved rapidly in response to divergent selection in both sexes. Large-brained females outperformed small-brained females in a numerical learning assay designed to test cognitive ability. Moreover, large-brained lines, especially males, developed smaller guts, as predicted by the expensive-tissue hypothesis, and produced fewer offspring. We propose that the evolution of brain size is mediated by a functional trade-off between increased cognitive ability and reproductive performance and discuss the implications of these findings for vertebrate brain evolution. Copyright © 2013 Elsevier Ltd. All rights reserved.

Cognitive and Social Values.

ERIC Educational Resources Information Center

Machamer, Peter; Douglas, Heather

1999-01-01

Criticizes Hugh Lacey's separation of cognitive values and social values in discussions of the nature of science. Claims that attempting to distinguish between cognitive and social ignores crucial complexities in the development and use of knowledge. Proposes that the proper distinction be between legitimate and illegitimate reasons in science as…

Penicillin for Education: How Cognitive Science Can Contribute to Education.

ERIC Educational Resources Information Center

Bruer, John T.

1995-01-01

Education can benefit from knowledge derived from cognitive and developmental psychology. Family demographics have actually improved between 1970 and 90 and so have NAEP scores. Three innovative programs demonstrating cognitive science applications include the Teaching Number Sense elementary math program, reciprocal teaching (reading strategy),…

The potential of using quantum theory to build models of cognition.

PubMed

Wang, Zheng; Busemeyer, Jerome R; Atmanspacher, Harald; Pothos, Emmanuel M

2013-10-01

Quantum cognition research applies abstract, mathematical principles of quantum theory to inquiries in cognitive science. It differs fundamentally from alternative speculations about quantum brain processes. This topic presents new developments within this research program. In the introduction to this topic, we try to answer three questions: Why apply quantum concepts to human cognition? How is quantum cognitive modeling different from traditional cognitive modeling? What cognitive processes have been modeled using a quantum account? In addition, a brief introduction to quantum probability theory and a concrete example is provided to illustrate how a quantum cognitive model can be developed to explain paradoxical empirical findings in psychological literature. © 2013 Cognitive Science Society, Inc.

Mill and mental phenomena: critical contributions to a science of cognition.

PubMed

Bistricky, Steven L

2013-06-01

Attempts to define cognition preceded John Stuart Mill's life and continue to this day. John Stuart Mill envisioned a science of mental phenomena informed by associationism, empirical introspection, and neurophysiology, and he advanced specific ideas that still influence modern conceptions of cognition. The present article briefly reviews Mill's personal history and the times in which he lived, and it traces the evolution of ideas that have run through him to contemporary cognitive concepts. The article also highlights contemporary problems in defining cognition and supports specific criteria regarding what constitutes cognition.

Artificial Intelligence and Expert Systems.

ERIC Educational Resources Information Center

Lawlor, Joseph

Artificial intelligence (AI) is the field of scientific inquiry concerned with designing machine systems that can simulate human mental processes. The field draws upon theoretical constructs from a wide variety of disciplines, including mathematics, psychology, linguistics, neurophysiology, computer science, and electronic engineering. Some of the…

Cognitive architectures: choreographing the dance of mental operations with the task environment.

PubMed

Gray, Wayne D

2008-06-01

In this article, I present the ideas and trends that have given rise to the use of cognitive architectures in human factors and provide a cognitive engineering-oriented taxonomy of these architectures and a snapshot of their use for cognitive engineering. Architectures of cognition have had a long history in human factors but a brief past. The long history entails a 50-year preamble, whereas the explosion of work in the current decade reflects the brief past. Understanding this history is key to understanding the current and future prospects for applying cognitive science theory to human factors practice. The review defines three formative eras in cognitive engineering research: the 1950s, 1980s, and now. In the first era, the fledging fields of cognitive science and human factors emphasized characteristics of the dancer the limited capacity or bounded rationality view of the mind, and the ballroom, the task environment. The second era emphasized the dance (i.e., the dynamic interaction between mental operations and task environment). The third era has seen the rise of cognitive architectures as tools for choreographing the dance of mental operations within the complex environments posed by human factors practice. Hybrid architectures present the best vector for introducing cognitive science theories into a renewed engineering-based human factors. The taxonomy provided in this article may provide guidance on when and whether to apply a cognitive science or a hybrid architecture to a human factors issue.

Active Ambiguity Reduction: An Experiment Design Approach to Tractable Qualitative Reasoning.

DTIC Science & Technology

1987-04-20

Approach to Tractable Qualitative Reasoning Shankar A. Rajamoney t [ For Gerald F. DeJong Artificial Intelligence Research Group Coordinated Science...Representations of Knowledge in a Mechanics Problem- Solver." Proceedings of the Fifth International Joint Conference on Artificial Intelligence. Cambridge. MIA...International Joint Conference on Artificial Intelligence. Tokyo. Japan. 1979. [de Kleer84] J. de Kleer and J. S. Brown. "A Qualitative Physics Based on

The Mediating Roles of Generative Cognition and Organizational Culture between Personality Traits and Student Imagination

ERIC Educational Resources Information Center

Liu, Yi-Lin; Liang, Chaoyun

2014-01-01

Using science majors as an example, we analyzed how generative cognition, organizational culture, and personality traits affect student imagination, and examined the mediating effects of generative cognition and organizational culture. A total of 473 undergraduates enrolled in physical, chemical, mathematical, and biological science programs…

The Relation between Cognitive and Metacognitive Strategic Processing during a Science Simulation

ERIC Educational Resources Information Center

Dinsmore, Daniel L.; Zoellner, Brian P.

2018-01-01

Background: This investigation was designed to uncover the relations between students' cognitive and metacognitive strategies used during a complex climate simulation. While cognitive strategy use during science inquiry has been studied, the factors related to this strategy use, such as concurrent metacognition, prior knowledge, and prior…

The Construction of a Questionnaire to Evaluate the Science Orientedness of Students' Identities as Learners from a Cognitive Perspective

ERIC Educational Resources Information Center

Taconis, Ruurd; de Putter-Smits, Lesley G. M.; Henry, Steven; den Brok, Perry J.; Beijaard, Douwe

2010-01-01

Forming a science-oriented identity is considered a process underlying both interest and achievement in science education. A questionnaire is developed for describing "identities as learners" and evaluating their science orientedness. The instrument (k = 65) focuses on cognitive aspects. An internal coherence of .88 was found. Five…

Social Cognitive Predictors of Mexican American High School Students' Math/Science Career Goals

ERIC Educational Resources Information Center

Garriott, Patton O.; Raque-Bogdan, Trisha L.; Zoma, Lorrine; Mackie-Hernandez, Dylan; Lavin, Kelly

2017-01-01

This study tested a social cognitive model of math/science career goals in a sample (N = 258) of Mexican American high school students. Familism and proximal family supports for math/science careers were examined as predictors of math/science: performance accomplishments, self-efficacy, interests, and goals. Results showed that the hypothesized…

A canonical theory of dynamic decision-making.

PubMed

Fox, John; Cooper, Richard P; Glasspool, David W

2013-01-01

Decision-making behavior is studied in many very different fields, from medicine and economics to psychology and neuroscience, with major contributions from mathematics and statistics, computer science, AI, and other technical disciplines. However the conceptualization of what decision-making is and methods for studying it vary greatly and this has resulted in fragmentation of the field. A theory that can accommodate various perspectives may facilitate interdisciplinary working. We present such a theory in which decision-making is articulated as a set of canonical functions that are sufficiently general to accommodate diverse viewpoints, yet sufficiently precise that they can be instantiated in different ways for specific theoretical or practical purposes. The canons cover the whole decision cycle, from the framing of a decision based on the goals, beliefs, and background knowledge of the decision-maker to the formulation of decision options, establishing preferences over them, and making commitments. Commitments can lead to the initiation of new decisions and any step in the cycle can incorporate reasoning about previous decisions and the rationales for them, and lead to revising or abandoning existing commitments. The theory situates decision-making with respect to other high-level cognitive capabilities like problem solving, planning, and collaborative decision-making. The canonical approach is assessed in three domains: cognitive and neuropsychology, artificial intelligence, and decision engineering.

A Canonical Theory of Dynamic Decision-Making

PubMed Central

Fox, John; Cooper, Richard P.; Glasspool, David W.

2012-01-01

Decision-making behavior is studied in many very different fields, from medicine and economics to psychology and neuroscience, with major contributions from mathematics and statistics, computer science, AI, and other technical disciplines. However the conceptualization of what decision-making is and methods for studying it vary greatly and this has resulted in fragmentation of the field. A theory that can accommodate various perspectives may facilitate interdisciplinary working. We present such a theory in which decision-making is articulated as a set of canonical functions that are sufficiently general to accommodate diverse viewpoints, yet sufficiently precise that they can be instantiated in different ways for specific theoretical or practical purposes. The canons cover the whole decision cycle, from the framing of a decision based on the goals, beliefs, and background knowledge of the decision-maker to the formulation of decision options, establishing preferences over them, and making commitments. Commitments can lead to the initiation of new decisions and any step in the cycle can incorporate reasoning about previous decisions and the rationales for them, and lead to revising or abandoning existing commitments. The theory situates decision-making with respect to other high-level cognitive capabilities like problem solving, planning, and collaborative decision-making. The canonical approach is assessed in three domains: cognitive and neuropsychology, artificial intelligence, and decision engineering. PMID:23565100

Bug Distribution and Statistical Pattern Classification.

ERIC Educational Resources Information Center

Tatsuoka, Kikumi K.; Tatsuoka, Maurice M.

1987-01-01

The rule space model permits measurement of cognitive skill acquisition and error diagnosis. Further discussion introduces Bayesian hypothesis testing and bug distribution. An illustration involves an artificial intelligence approach to testing fractions and arithmetic. (Author/GDC)

The Art of Artificial Intelligence. 1. Themes and Case Studies of Knowledge Engineering

DTIC Science & Technology

1977-08-01

in scientific and medical inference illuminate the art of knowledge engineering and its parent science , Artificial Intelligence....The knowledge engineer practices the art of bringing the principles and tools of AI research to bear on difficult applications problems requiring

Systems in Science: Modeling Using Three Artificial Intelligence Concepts.

ERIC Educational Resources Information Center

Sunal, Cynthia Szymanski; Karr, Charles L.; Smith, Coralee; Sunal, Dennis W.

2003-01-01

Describes an interdisciplinary course focusing on modeling scientific systems. Investigates elementary education majors' applications of three artificial intelligence concepts used in modeling scientific systems before and after the course. Reveals a great increase in understanding of concepts presented but inconsistent application. (Author/KHR)

Artificial multilayers and nanomagnetic materials.

PubMed

Shinjo, Teruya

2013-01-01

The author has been actively engaged in research on nanomagnetic materials for about 50 years. Nanomagnetic materials are comprised of ferromagnetic systems for which the size and shape are controlled on a nanometer scale. Typical examples are ultrafine particles, ultrathin films, multilayered films and nano-patterned films. In this article, the following four areas of the author's studies are described.(1) Mössbauer spectroscopic studies of nanomagnetic materials and interface magnetism.(2) Preparation and characterization of metallic multilayers with artificial superstructures.(3) Giant magnetoresistance (GMR) effect in magnetic multilayers.(4) Novel properties of nanostructured ferromagnetic thin films (dots and wires).A subject of particular interest in the author's research was the artificially prepared multilayers consisting of metallic elements. The motivation to initiate the multilayer investigation is described and the physical properties observed in the artificial multilayers are introduced. The author's research was initially in the field of pure physical science and gradually extended into applied science. His achievements are highly regarded not only from the fundamental point of view but also from the technological viewpoint.

An Ankle-Foot Orthosis Powered by Artificial Pneumatic Muscles

PubMed Central

Ferris, Daniel P.; Czerniecki, Joseph M.; Hannaford, Blake

2005-01-01

We developed a pneumatically powered orthosis for the human ankle joint. The orthosis consisted of a carbon fiber shell, hinge joint, and two artificial pneumatic muscles. One artificial pneumatic muscle provided plantar flexion torque and the second one provided dorsiflexion torque. Computer software adjusted air pressure in each artificial muscle independently so that artificial muscle force was proportional to rectified low-pass-filtered electromyography (EMG) amplitude (i.e., proportional myoelectric control). Tibialis anterior EMG activated the artificial dorsiflexor and soleus EMG activated the artificial plantar flexor. We collected joint kinematic and artificial muscle force data as one healthy participant walked on a treadmill with the orthosis. Peak plantar flexor torque provided by the orthosis was 70 Nm, and peak dorsiflexor torque provided by the orthosis was 38 Nm. The orthosis could be useful for basic science studies on human locomotion or possibly for gait rehabilitation after neurological injury. PMID:16082019

Artificial Neural Network approach to develop unique Classification and Raga identification tools for Pattern Recognition in Carnatic Music

NASA Astrophysics Data System (ADS)

Srimani, P. K.; Parimala, Y. G.

2011-12-01

A unique approach has been developed to study patterns in ragas of Carnatic Classical music based on artificial neural networks. Ragas in Carnatic music which have found their roots in the Vedic period, have grown on a Scientific foundation over thousands of years. However owing to its vastness and complexities it has always been a challenge for scientists and musicologists to give an all encompassing perspective both qualitatively and quantitatively. Cognition, comprehension and perception of ragas in Indian classical music have always been the subject of intensive research, highly intriguing and many facets of these are hitherto not unravelled. This paper is an attempt to view the melakartha ragas with a cognitive perspective using artificial neural network based approach which has given raise to very interesting results. The 72 ragas of the melakartha system were defined through the combination of frequencies occurring in each of them. The data sets were trained using several neural networks. 100% accurate pattern recognition and classification was obtained using linear regression, TLRN, MLP and RBF networks. Performance of the different network topologies, by varying various network parameters, were compared. Linear regression was found to be the best performing network.

Biologically inspired intelligent robots

NASA Astrophysics Data System (ADS)

Bar-Cohen, Yoseph; Breazeal, Cynthia

2003-07-01

Humans throughout history have always sought to mimic the appearance, mobility, functionality, intelligent operation, and thinking process of biological creatures. This field of biologically inspired technology, having the moniker biomimetics, has evolved from making static copies of human and animals in the form of statues to the emergence of robots that operate with realistic behavior. Imagine a person walking towards you where suddenly you notice something weird about him--he is not real but rather he is a robot. Your reaction would probably be "I can't believe it but this robot looks very real" just as you would react to an artificial flower that is a good imitation. You may even proceed and touch the robot to check if your assessment is correct but, as oppose to the flower case, the robot may be programmed to respond physical and verbally. This science fiction scenario could become a reality as the current trend continues in developing biologically inspired technologies. Technology evolution led to such fields as artificial muscles, artificial intelligence, and artificial vision as well as biomimetic capabilities in materials science, mechanics, electronics, computing science, information technology and many others. This paper will review the state of the art and challenges to biologically-inspired technologies and the role that EAP is expected to play as the technology evolves.

Development of Online Cognitive and Algorithm Tests as Assessment Tools in Introductory Computer Science Courses

ERIC Educational Resources Information Center

Avancena, Aimee Theresa; Nishihara, Akinori; Vergara, John Paul

2012-01-01

This paper presents the online cognitive and algorithm tests, which were developed in order to determine if certain cognitive factors and fundamental algorithms correlate with the performance of students in their introductory computer science course. The tests were implemented among Management Information Systems majors from the Philippines and…

From Universal Laws of Cognition to Specific Cognitive Models

ERIC Educational Resources Information Center

Chater, Nick; Brown, Gordon D. A.

2008-01-01

The remarkable successes of the physical sciences have been built on highly general quantitative laws, which serve as the basis for understanding an enormous variety of specific physical systems. How far is it possible to construct universal principles in the cognitive sciences, in terms of which specific aspects of perception, memory, or decision…

Cognitive Research and Elementary Science Instruction: From the Laboratory, to the Classroom, and Back

ERIC Educational Resources Information Center

Klahr, David; Li, Junlei

2005-01-01

Can cognitive research generate usable knowledge for elementary science instruction? Can issues raised by classroom practice drive the agenda of laboratory cognitive research? Answering yes to both questions, we advocate building a reciprocal interface between basic and applied research. We discuss five studies of the teaching, learning, and…

Science Teaching Based on Cognitive Load Theory: Engaged Students, but Cognitive Deficiencies

ERIC Educational Resources Information Center

Meissner, Barbara; Bogner, Franz X.

2012-01-01

To improve science learning under demanding conditions, we designed an out-of-school lesson in compliance with cognitive load theory (CLT). We extracted student clusters based on individual effectiveness, and compared instructional efficiency, mental effort, and persistence of learning. The present study analyses students' engagement. 50.0% of our…

The Status of Cognitive Psychology Journals: An Impact Factor Approach

ERIC Educational Resources Information Center

Togia, Aspasia

2013-01-01

The purpose of this study was to examine the impact factor of cognitive psychology journals indexed in the Science and Social Sciences edition of "Journal Citation Reports" ("JCR") database over a period of 10 consecutive years. Cognitive psychology journals were indexed in 11 different subject categories of the database. Their mean impact factor…

At the Root of Embodied Cognition: Cognitive Science Meets Neurophysiology

ERIC Educational Resources Information Center

Garbarini, Francesca; Adenzato, Mauro

2004-01-01

Recent experimental research in the field of neurophysiology has led to the discovery of two classes of visuomotor neurons: canonical neurons and mirror neurons. In light of these studies, we propose here an overview of two classical themes in the cognitive science panorama: James Gibson's theory of affordances and Eleanor Rosch's principles of…

Cognitive Science and Military Training.

ERIC Educational Resources Information Center

Halff, Henry M.; And Others

1986-01-01

Four new military training systems offer the opportunity for the application of cognitive science. They are the following: (1) a family of memorization games; (2) a simulator with a graphic, schematic student interface; (3) a system for solving problems of relative motion; and (4) a method of building cognitive skills for air-intercept control.…

Effects of a Modified Thinking Science Program for Year 8 Students of Various Abilities

ERIC Educational Resources Information Center

Mobbs, Ellen

2016-01-01

The aim of this research was to identify whether students of various academic abilities would achieve positive gains in cognitive ability after completing a modified cognitive acceleration program based on the Cognitive Acceleration through Science Education (CASE) program. This research was quasi-experimental in design, with small samples of…

The Challenges of Scientific Literacy: From the Viewpoint of Second-Generation Cognitive Science

ERIC Educational Resources Information Center

Klein, Perry D.

2006-01-01

Recent trends in cognitive science have not made scientific literacy easier to attain, but they have made the practices through which educators meet its challenges more interpretable. Traditionally, cognitive scientists viewed knowledge as a set of propositions comprised of classical concepts, thought as logical inference and language as a literal…

Mill and Mental Phenomena: Critical Contributions to a Science of Cognition

PubMed Central

Bistricky, Steven L.

2013-01-01

Attempts to define cognition preceded John Stuart Mill’s life and continue to this day. John Stuart Mill envisioned a science of mental phenomena informed by associationism, empirical introspection, and neurophysiology, and he advanced specific ideas that still influence modern conceptions of cognition. The present article briefly reviews Mill’s personal history and the times in which he lived, and it traces the evolution of ideas that have run through him to contemporary cognitive concepts. The article also highlights contemporary problems in defining cognition and supports specific criteria regarding what constitutes cognition. PMID:25379235

Low-Level Cognitive Modeling of Aircrew Function Using the Soar Artificial Intelligence Architecture

DTIC Science & Technology

1998-04-01

Neisser , U . (1976). Cognition and reality. New York: Freeman. • Newell, A. (1990). Unified theories of cognition. Cambridge, MA: Harvard Uni...Figures 8 and 9, identification distance had an element of chance associ- ated with both the RTIC and baseline behaviors. 14 30 T 25 0) o P 20 u O...Condition. 16 14 1 12 c o 3 Ü U O m SI E 3 10 8- o o o First Identification Distribution o o o CM co o o o co CO o o o CO o o o in

Construction of Optimal-Path Maps for Homogeneous-Cost-Region Path-Planning Problems

DTIC Science & Technology

1989-09-01

of Artificial Inteligence , 9%,4. 24. Kirkpatrick, S., Gelatt Jr., C. D., and Vecchi, M. P., "Optinization by Sinmulated Ani- nealing", Science, Vol...studied in depth by researchers in such fields as artificial intelligence, robot;cs, and computa- tional geometry. Most methods require homogeneous...the results of the research. 10 U. L SLEVANT RESEARCH A. APPLICABLE CONCEPTS FROM ARTIFICIAL INTELLIGENCE 1. Search Methods One of the central

The image recognition based on neural network and Bayesian decision

NASA Astrophysics Data System (ADS)

Wang, Chugege

2018-04-01

The artificial neural network began in 1940, which is an important part of artificial intelligence. At present, it has become a hot topic in the fields of neuroscience, computer science, brain science, mathematics, and psychology. Thomas Bayes firstly reported the Bayesian theory in 1763. After the development in the twentieth century, it has been widespread in all areas of statistics. In recent years, due to the solution of the problem of high-dimensional integral calculation, Bayesian Statistics has been improved theoretically, which solved many problems that cannot be solved by classical statistics and is also applied to the interdisciplinary fields. In this paper, the related concepts and principles of the artificial neural network are introduced. It also summarizes the basic content and principle of Bayesian Statistics, and combines the artificial neural network technology and Bayesian decision theory and implement them in all aspects of image recognition, such as enhanced face detection method based on neural network and Bayesian decision, as well as the image classification based on the Bayesian decision. It can be seen that the combination of artificial intelligence and statistical algorithms has always been the hot research topic.

Artificial Intelligence and Expert Systems Research and Their Possible Impact on Information Science.

ERIC Educational Resources Information Center

Borko, Harold

1985-01-01

Defines artificial intelligence (AI) and expert systems; describes library applications utilizing AI to automate creation of document representations, request formulations, and design and modify search strategies for information retrieval systems; discusses expert system development for information services; and reviews impact of these…

Relational Integration as a Predictor of Academic Achievement

ERIC Educational Resources Information Center

Krumm, Stefan; Lipnevich, Anastasiya A.; Schmidt-Atzert, Lothar; Buhner, Markus

2012-01-01

The current study aimed at applying a broad model of cognitive functions to predict performance in science and language courses at school as well as performance in a science course at university. We hypothesized that performance in science courses was predominantly related to the cognitive function known as relational integration, whereas…

The Relationship of Mentoring on Middle School Girls' Science-Related Attitudes

ERIC Educational Resources Information Center

Clark, Lynette M.

2013-01-01

This quantitative study examined the science-related attitudes of middle school girls who attended a science-focused mentoring program and those of middle school girls who attended a traditional mentoring program. Theories related to this study include social cognitive theory, cognitive development theory, and possible selves' theory. These…

Teaching School Science within the Cognitive and Affective Domains

ERIC Educational Resources Information Center

Tan, Kok Siang; Heng, Chong Yong; Tan, Shuhui

2013-01-01

In classrooms, science is usually taught within the cognitive domain while the psychomotor learning domain is achieved through performing science experiments in the laboratory. Although students attend civic and moral education and pastoral care classes where values and life skills are often taught directly, learning experiences in most school…

Social Cognitive Predictors of Interest in Environmental Science: Recommendations for Environmental Educators

ERIC Educational Resources Information Center

Quimby, Julie L.; Seyala, Nazar D.; Wolfson, Jane L.

2007-01-01

The authors examined the influence of social cognitive variables on students' interest in environmental science careers and investigated differences between White and ethnic minority students on several career-related variables. The sample consisted of 161 undergraduate science majors (124 White students, 37 ethnic minority students). Results of…

Dynamic mechanistic explanation: computational modeling of circadian rhythms as an exemplar for cognitive science.

PubMed

Bechtel, William; Abrahamsen, Adele

2010-09-01

We consider computational modeling in two fields: chronobiology and cognitive science. In circadian rhythm models, variables generally correspond to properties of parts and operations of the responsible mechanism. A computational model of this complex mechanism is grounded in empirical discoveries and contributes a more refined understanding of the dynamics of its behavior. In cognitive science, on the other hand, computational modelers typically advance de novo proposals for mechanisms to account for behavior. They offer indirect evidence that a proposed mechanism is adequate to produce particular behavioral data, but typically there is no direct empirical evidence for the hypothesized parts and operations. Models in these two fields differ in the extent of their empirical grounding, but they share the goal of achieving dynamic mechanistic explanation. That is, they augment a proposed mechanistic explanation with a computational model that enables exploration of the mechanism's dynamics. Using exemplars from circadian rhythm research, we extract six specific contributions provided by computational models. We then examine cognitive science models to determine how well they make the same types of contributions. We suggest that the modeling approach used in circadian research may prove useful in cognitive science as researchers develop procedures for experimentally decomposing cognitive mechanisms into parts and operations and begin to understand their nonlinear interactions.

Magnetic Charge Organization and Screening in Thermalized Artificial Spin Ice

NASA Astrophysics Data System (ADS)

Gilbert, Ian

2014-03-01

Artificial spin ice is a material-by-design in which interacting single-domain ferromagnetic nanoislands are used to model Ising spins in frustrated spin systems. Artificial spin ice has proved a useful system in which to directly probe the physics of geometrical frustration, allowing us to better understand materials such as spin ice. Recently, several new experimental techniques have been developed that allow effective thermalization of artificial spin ice. Given the intense interest in magnetic monopole excitations in spin ice materials and artificial spin ice's success in modeling these materials, it should not come as a surprise that interesting monopole physics emerges here as well. The first experimental investigation of thermalized artificial square spin ice determined that the system's monopole-like excitations obeyed a Boltzmann distribution and also found evidence for monopole-antimonopole interactions. Further experiments have implicated these monopole excitations in the growth of ground state domains. Our recent study of artificial kagome spin ice, whose odd-coordinated vertices always possess a net magnetic charge, has revealed a theoretically-predicted magnetic charge ordering transition which has not been previously observed experimentally. We have also investigated the details of magnetic charge interactions in lattices of mixed coordination number. This work was done in collaboration with Sheng Zhang, Cristiano Nisoli, Gia-Wei Chern, Michael Erickson, Liam O'Brien, Chris Leighton, Paul Lammert, Vincent Crespi, and Peter Schiffer. This work was primarily funded by the US Department of Energy, Office of Basic Energy Sciences, Materials Science and Engineering Division, grant no. DE-SC0005313.

A social-cognitive framework of multidisciplinary team innovation.

PubMed

Paletz, Susannah B F; Schunn, Christian D

2010-01-01

The psychology of science typically lacks integration between cognitive and social variables. We present a new framework of team innovation in multidisciplinary science and engineering groups that ties factors from both literatures together. We focus on the effects of a particularly challenging social factor, knowledge diversity, which has a history of mixed effects on creativity, most likely because those effects are mediated and moderated by cognitive and additional social variables. In addition, we highlight the distinction between team innovative processes that are primarily divergent versus convergent; we propose that the social and cognitive implications are different for each, providing a possible explanation for knowledge diversity's mixed results on team outcomes. Social variables mapped out include formal roles, communication norms, sufficient participation and information sharing, and task conflict; cognitive variables include analogy, information search, and evaluation. This framework provides a roadmap for research that aims to harness the power of multidisciplinary teams. Copyright © 2009 Cognitive Science Society, Inc.

Functional research and cognitive-process research in behavioural science: An unequal but firmly connected pair.

PubMed

Fiedler, Klaus

2016-02-01

Drawing on illustrative examples of the functional and cognitive psychology in contemporary research, the present article emphasizes the primacy of functional relationships, which provide the fundament for all attempts to uncover invisible cognitive processes. Cognitive research is not only inherently more difficult and much more ambitious than functional research. It also suffers from several home-made problems, such as unwarranted inferences from model fitting, the mediation-analysis cult and the failure to take environmental influences into account. However, despite the primacy of functional psychology and the problems associated with the ambitious goals of cognitive research, the two partners in this unequal pair are firmly connected and jointly responsible for the most impressive examples of progress in behavioural science. © 2015 International Union of Psychological Science.

Artificial Gravity as a Multi-System Countermeasure: Effects on Cognitive Function

NASA Technical Reports Server (NTRS)

Sipes, Walter E.; Seaton, Kim; Slack, Kellely; Bowie, Kendra

2007-01-01

The Space Flight Cognitive Assessment Tool for Windows (WinSCAT) is a medical requirement on the International Space Station, and its purpose is to evaluate cognitive functioning after physical insult (e.g., head trauma, decompression sickness, exposure to toxic gases, medication side effects). The current objective is to assess cognitive functioning in a long duration space mission analog environment where Artificial Gravity is being applied as a countermeasure in a Bed Rest study. Methods: Fifteen male subjects (8 treatment and 7 control) who participated in 21 days of -6 degree head-down bed rest were assessed. Three practice and three baseline WinSCAT test sessions were administered during the pre-bed rest phase of study participation. During the bed rest phase, the WinSCAT test was scheduled every other day, following the centrifuge, for a total of 10 test sessions. (The treatment group received 60 minutes of centrifugation each day during the 21 days of bed rest. The control subjects were strapped to the centrifuge for the same length of time as the treatment group but were not spun.) During the post-bed rest (reconditioning) phase, the test was administered 4 times. Results: Individual differences were found both within and between the treatment and control groups. After controlling for the number of subjects in each group, the treatment group accounted for more off-nominal WinSCAT scores than the control group. Conclusions:There is some preliminary evidence that centrifuge spinning might negatively impact cognitive functioning. However, due to sample size limitations, it cannot be ascertained whether there were significant differences in cognitive performance between the treatment and control groups. If centrifugation had a negative effect on cognitive functioning, consistent decrements would be expected to be found with all treatment subjects across time. Individual differences in underlying cognitive ability and motivation level are other possible explanations for the results found in this study.

Future Tense: Science Fiction Confronts the New Science.

ERIC Educational Resources Information Center

Antczak, Janice

1990-01-01

Describes 10 science fiction stories for young readers whose contents address recent developments on the frontiers of scientific research, including genetic engineering, artificial intelligence, and robotics. The use of these materials to inform young readers about the issues and dangers involved in scientific developments is discussed. (CLB)

Department-Level Representations: A New Approach to the Study of Science Teacher Cognition

ERIC Educational Resources Information Center

Hutner, Todd L.; Markman, Arthur B.

2016-01-01

Research on science teacher cognition is important as findings from this research can be used to improve teacher training, leading to improved classroom practice. Previous research has often relied on two underlying assumptions: Cognition is an individual process, and these processes are detailed and introspective. In this paper, we put forth a…

Parental Loss and Eating-Related Cognitions and Behaviors in College-Age Women

ERIC Educational Resources Information Center

Beam, Minna R.; Servaty-Seib, Heather L.; Mathews, Laura

2004-01-01

To examine the eating-related cognitions and behaviors of college-age women who had experienced parental death, parental divorce, or neither loss condition, we recruited 48 women from science and social science departments at a state university in the Southeast. All participants completed the Mizes Anorectic Cognitions Scale (MAC) and the Bulimia…

Towards Cognitive Load Theory as Guideline for Instructional Design in Science Education

ERIC Educational Resources Information Center

Meissner, Barbara; Bogner, Franz X.

2013-01-01

We applied cognitive load theory in an heuristic out-of-school science lesson. The lesson comprises experiments concerning major attributes of NaCl and was designed for 5th to 8th grade students. Our interest focused on whether cognitive load theory provides sufficient guidelines for instructional design in the field of heuristic science…

An Investigation of Some Cognitive Style Variables and Their Relationships to Science Achievement.

ERIC Educational Resources Information Center

Zambotti, Geno; Fazio, Frank

This study was designed to survey the cognitive style preferences of college students. Two instruments were used in obtaining data for this inquiry. The Cognitive Preference Survey for Physical Science, developed by the authors, gave three preference scores: Memory, a preference for simple content facts; Principle, for a concept or theoretical…

Learning with Multiple Representations: Infographics as Cognitive Tools for Authentic Learning in Science Literacy

ERIC Educational Resources Information Center

Gebre, Engida

2018-01-01

This paper presents a descriptive case study where infographics--visual representation of data and ideas--have been used as cognitive tools to facilitate learning with multiple representations in the context of secondary school students' science news reporting. Despite the complementary nature of the two research foci, studies on cognitive tools…

Human Behavior Modeling in Network Science

DTIC Science & Technology

2010-03-01

in Network Science bringing three distinct research areas together, communication networks, information networks, and social /cognitive networks. The...researchers. A critical part of the social /cognitive network effort is the modeling of human behavior. The modeling efforts range from organizational...behavior to social cognitive trust to explore and refine the theoretical and applied network relationships between and among the human

The coming of age of artificial intelligence in medicine.

PubMed

Patel, Vimla L; Shortliffe, Edward H; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R; Bellazzi, Riccardo; Abu-Hanna, Ameen

2009-05-01

This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its "adolescence" (Shortliffe EH. The adolescence of AI in medicine: will the field come of age in the '90s? Artificial Intelligence in Medicine 1993;5:93-106). In this article, the discussants reflect on medical AI research during the subsequent years and characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision-making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems.

An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part A: The core ingredients

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1983-01-01

Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. The goal of Artificial Intelligence is focused on developing computational approaches to intelligent behavior. This goal is so broad - covering virtually all aspects of human cognitive activity - that substantial confusion has arisen as to the actual nature of AI, its current status and its future capability. This volume, the first in a series of NBS/NASA reports on the subject, attempts to address these concerns. Thus, this report endeavors to clarify what AI is, the foundations on which it rests, the techniques utilized, applications, the participants and, finally, AI's state-of-the-art and future trends. It is anticipated that this report will prove useful to government and private engineering and research managers, potential users, and others who will be affected by this field as it unfolds.

The Coming of Age of Artificial Intelligence in Medicine*

PubMed Central

Patel, Vimla L.; Shortliffe, Edward H.; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R.; Bellazzi, Riccardo; Abu-Hanna, Ameen

2009-01-01

Summary This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its “adolescence” (Shortliffe EH. The adolescence of AI in medicine: Will the field come of age in the ‘90s? Artificial Intelligence in Medicine 1993; 5:93–106). In this article, the discussants reflect on medical AI research during the subsequent years and attempt to characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems. PMID:18790621

Artificial Intelligence in Business: Technocrat Jargon or Quantum Leap?

ERIC Educational Resources Information Center

Burford, Anna M.; Wilson, Harold O.

This paper addresses the characteristics and applications of artificial intelligence (AI) as a subsection of computer science, and briefly describes the most common types of AI programs: expert systems, natural language, and neural networks. Following a brief presentation of the historical background, the discussion turns to an explanation of how…

Mapping and correcting the influence of gaze position on pupil size measurements

PubMed Central

Petrov, Alexander A.

2015-01-01

Pupil size is correlated with a wide variety of important cognitive variables and is increasingly being used by cognitive scientists. Pupil data can be recorded inexpensively and non-invasively by many commonly used video-based eye-tracking cameras. Despite the relative ease of data collection and increasing prevalence of pupil data in the cognitive literature, researchers often underestimate the methodological challenges associated with controlling for confounds that can result in misinterpretation of their data. One serious confound that is often not properly controlled is pupil foreshortening error (PFE)—the foreshortening of the pupil image as the eye rotates away from the camera. Here we systematically map PFE using an artificial eye model and then apply a geometric model correction. Three artificial eyes with different fixed pupil sizes were used to systematically measure changes in pupil size as a function of gaze position with a desktop EyeLink 1000 tracker. A grid-based map of pupil measurements was recorded with each artificial eye across three experimental layouts of the eye-tracking camera and display. Large, systematic deviations in pupil size were observed across all nine maps. The measured PFE was corrected by a geometric model that expressed the foreshortening of the pupil area as a function of the cosine of the angle between the eye-to-camera axis and the eye-to-stimulus axis. The model reduced the root mean squared error of pupil measurements by 82.5 % when the model parameters were pre-set to the physical layout dimensions, and by 97.5 % when they were optimized to fit the empirical error surface. PMID:25953668

Biologically inspired technologies using artificial muscles

NASA Astrophysics Data System (ADS)

Bar-Cohen, Yoseph

2005-01-01

After billions of years of evolution, nature developed inventions that work, which are appropriate for the intended tasks and that last. The evolution of nature led to the introduction of highly effective and power efficient biological mechanisms that are scalable from micron to many meters in size. Imitating these mechanisms offers enormous potentials for the improvement of our life and the tools we use. Humans have always made efforts to imitate nature and we are increasingly reaching levels of advancement where it becomes significantly easier to imitate, copy, and adapt biological methods, processes and systems. Some of the biomimetic technologies that have emerged include artificial muscles, artificial intelligence, and artificial vision to which significant advances in materials science, mechanics, electronics, and computer science have contributed greatly. One of the newest fields of biomimetics is the electroactive polymers (EAP) that are also known as artificial muscles. To take advantage of these materials, efforts are made worldwide to establish a strong infrastructure addressing the need for comprehensive analytical modeling of their operation mechanism and develop effective processing and characterization techniques. The field is still in its emerging state and robust materials are not readily available however in recent years significant progress has been made and commercial products have already started to appear. This paper covers the state-of-the-art and challenges to making artificial muscles and their potential biomimetic applications.

Précis of bayesian rationality: The probabilistic approach to human reasoning.

PubMed

Oaksford, Mike; Chater, Nick

2009-02-01

According to Aristotle, humans are the rational animal. The borderline between rationality and irrationality is fundamental to many aspects of human life including the law, mental health, and language interpretation. But what is it to be rational? One answer, deeply embedded in the Western intellectual tradition since ancient Greece, is that rationality concerns reasoning according to the rules of logic--the formal theory that specifies the inferential connections that hold with certainty between propositions. Piaget viewed logical reasoning as defining the end-point of cognitive development; and contemporary psychology of reasoning has focussed on comparing human reasoning against logical standards. Bayesian Rationality argues that rationality is defined instead by the ability to reason about uncertainty. Although people are typically poor at numerical reasoning about probability, human thought is sensitive to subtle patterns of qualitative Bayesian, probabilistic reasoning. In Chapters 1-4 of Bayesian Rationality (Oaksford & Chater 2007), the case is made that cognition in general, and human everyday reasoning in particular, is best viewed as solving probabilistic, rather than logical, inference problems. In Chapters 5-7 the psychology of "deductive" reasoning is tackled head-on: It is argued that purportedly "logical" reasoning problems, revealing apparently irrational behaviour, are better understood from a probabilistic point of view. Data from conditional reasoning, Wason's selection task, and syllogistic inference are captured by recasting these problems probabilistically. The probabilistic approach makes a variety of novel predictions which have been experimentally confirmed. The book considers the implications of this work, and the wider "probabilistic turn" in cognitive science and artificial intelligence, for understanding human rationality.

A Microworld Approach to the Formalization of Musical Knowledge.

ERIC Educational Resources Information Center

Honing, Henkjan

1993-01-01

Discusses the importance of applying computational modeling and artificial intelligence techniques to music cognition and computer music research. Recommends three uses of microworlds to trim computational theories to their bare minimum, allowing for better and easier comparison. (CFR)

Knowledge Engineering and Education.

ERIC Educational Resources Information Center

Lopez, Antonio M., Jr.; Donlon, James

2001-01-01

Discusses knowledge engineering, computer software, and possible applications in the field of education. Highlights include the distinctions between data, information, and knowledge; knowledge engineering as a subfield of artificial intelligence; knowledge acquisition; data mining; ontology development for subject terms; cognitive apprentices; and…

AFFECTIVE GUIDANCE OF INTELLIGENT AGENTS: How Emotion Controls Cognition1

PubMed Central

Clore, Gerald L.; Palmer, Janet E.

2008-01-01

Emotions and moods color cognition. In this article, we outline how emotions affect judgments and cognitive performance of human agents. We argue that affective influences are due, not to the affective reactions themselves, but to the information they carry about value, a potentially useful finding for creators of artificial agents. The kind of influence that occurs depends on the focus of the agent at the time. When making evaluative judgments, for example, agents may experience positive affect as a positive attitude toward a person or object. But when an agent focuses on a cognitive task, positive affect may act like performance feedback, with positive affect giving a green light to cognitive, relational processes. By contrast, negative affect tends to inhibit relational processing, resulting in a more perceptual, stimulus-specific processing. One result is that many textbook phenomena from cognitive psychology occur readily in happy moods, but are inhibited in sad moods. PMID:19255620

Analyzing Hierarchical Relationships among Modes of Cognitive Reasoning and Integrated Science Process Skills.

ERIC Educational Resources Information Center

Yeany, Russell H.; And Others

This study attempted to search for a learning hierarchy among the skills comprising formal operations and the integrated science processes. Data were obtained from two instruments administered to 741 high school science students. The Group Assessment of Logical Thinking (GALT) measured performance on six Piagetian cognitive modes: controlling…

Biomedical Engineering and Cognitive Science Secondary Science Curriculum Development: A Three Year Study

ERIC Educational Resources Information Center

Klein, Stacy S.; Sherwood, Robert D.

2005-01-01

This study reports on a multi-year effort to create and evaluate cognitive-based curricular materials for secondary school science classrooms. A team of secondary teachers, educational researchers, and academic biomedical engineers developed a series of curriculum units that are based in biomedical engineering for secondary level students in…

Science Adjustment, Parental and Teacher Autonomy Support and the Cognitive Orientation of Science Students

ERIC Educational Resources Information Center

Jungert, Tomas; Koestner, Richard

2015-01-01

Research has shown that autonomy support has positive effects on academic development, but no study has examined how systemising cognitive orientation is related to important outcomes for science students, and how it may interact with autonomy support. This prospective investigation considered how systemising and support from teachers and parents…

Linguistics, Cognitive Science and the Undergraduate Curriculum. Linguistics in the Undergraduate Curriculum, Appendix 4-I.

ERIC Educational Resources Information Center

Feinstein, Mark; Stillings, Neil

Cognitive science has recently emerged as a new interdisciplinary field incorporating parts of psychology, computer science, philosophy, neuroscience, and linguistics. Its goal is to bring the theoretical and methodological resources of the contributing disciplines to bear on an integrated investigation of thought, meaning, language, perception,…

Systemizing: A Cross-Cultural Constant for Motivation to Learn Science

ERIC Educational Resources Information Center

Zeyer, Albert; Çetin-Dindar, Ayla; Md Zain, Ahmad Nurulazam; Juriševic, Mojca; Devetak, Iztok; Odermatt, Freia

2013-01-01

The present study is based on the empathizing-systemizing (E-S) theory of cognitive science. It was hypothesized that the influence of students' gender on their motivation to learn science is often overestimated in the research literature and that cognitive style is more important for motivation than students' gender. By using structural equation…

The Effect of Executive Function on Science Achievement Among Normally Developing 10-Year Olds

NASA Astrophysics Data System (ADS)

Lederman, Sheri G.

Executive function (EF) is an umbrella term used to identify a set of discrete but interrelated cognitive abilities that enable individuals to engage in goal-directed, future-oriented action in response to a novel context. Developmental studies indicate that EF is predictive of reading and math achievement in middle childhood. The purpose of this study was to identify the association between EF and science achievement among normally developing 10 year olds. A sample of fifth grade students from a Northeastern suburban community participated in tests of EF, science, and intelligence. Consistent with adult models of EF, principal components analysis identified a three-factor model of EF organization in middle childhood, including cognitive flexibility, working memory, and inhibition. Multiple regression analyses revealed that executive function processes of cognitive flexibility, working memory, and inhibition were all predictive of science performance. Post hoc analyses revealed that high-performing science students differed significantly from low-performing students in both cognitive flexibility and working memory. These findings suggest that complex academic demands specific to science achievement rely on the emergence and maturation of EF components.

Cognitive science speaks to the "common-sense" of chronic illness management.

PubMed

Leventhal, Howard; Leventhal, Elaine A; Breland, Jessica Y

2011-04-01

We describe the parallels between findings from cognitive science and neuroscience and Common-Sense Models in four areas: (1) Activation of illness representations by the automatic linkage of symptoms and functional changes with concepts (an integration of declarative and perceptual and procedural knowledge); (2) Action plans for the management of symptoms and disease; (3) Cognitive and behavioral heuristics (executive functions parallel to recent findings in cognitive science) involved in monitoring and modifying automatic control processes; (4) Perceiving and communicating to "other minds" during medical visits to address the declarative and non-declarative (perceptual and procedural) knowledge that comprise a patient's representations of illness and treatment (the transparency of other minds).

Introduction to cognition in science and technology.

PubMed

Gorman, Michael E

2009-10-01

Cognitive studies of science and technology have had a long history of largely independent research projects that have appeared in multiple outlets, but rarely together. The emergence of a new International Society for Psychology of Science and Technology suggests that this is a good time to put some of the latest work in this area into topiCS in a way that will both acquaint readers with the cutting edge in this domain and also give them a hint of its history. One core theme includes how scientists, inventors, and engineers represent and solve problems; another, related theme is the extent to which they distribute and share cognition. Methodologies include fine-grained studies of historical records, protocols of working scientists, observations and comparisons of engineering science laboratories, and computational simulations designed both to serve as research tools and also to improve scientific problem-solving. The series of articles will conclude with the Associate Editor's suggestions for future research. Copyright © 2009 Cognitive Science Society, Inc.

A DDC Bibliography on Computers in Information Sciences. Volume II. Information Sciences Series.

ERIC Educational Resources Information Center

Defense Documentation Center, Alexandria, VA.

The unclassified and unlimited bibliography compiles references dealing specifically with the role of computers in information sciences. The volume contains 239 annotated references grouped under three major headings: Artificial and Programming Languages, Computer Processing of Analog Data, and Computer Processing of Digital Data. The references…

Knowledge Engineering: The Interplay between Information and Historical Sciences in the Study of Change.

ERIC Educational Resources Information Center

McCrank, Lawrence J.

1992-01-01

Discusses trends in the fields of knowledge engineering and historical sciences to speculate about possibilities of converging interests and applications. Topics addressed include artificial intelligence and expert systems; the history of information science; history as a related field; historians as information scientists; multidisciplinary…

Teaching Science Out-of-School with Special Reference to Biology.

ERIC Educational Resources Information Center

Meyer, G. Rex, Ed.; Rao, A. N., Ed.

This book contains a selection of previously unpublished papers from an international Asian symposium on out-of-school science activities. These papers include: "Educational and Social Values of Out-of-School Science" (Peter Kelly); "School Versus Out-of-School: An Artificial Dichotomy" (William Mayer); "Biology of…

Classification of a Driver's cognitive workload levels using artificial neural network on ECG signals.

PubMed

Tjolleng, Amir; Jung, Kihyo; Hong, Wongi; Lee, Wonsup; Lee, Baekhee; You, Heecheon; Son, Joonwoo; Park, Seikwon

2017-03-01

An artificial neural network (ANN) model was developed in the present study to classify the level of a driver's cognitive workload based on electrocardiography (ECG). ECG signals were measured on 15 male participants while they performed a simulated driving task as a primary task with/without an N-back task as a secondary task. Three time-domain ECG measures (mean inter-beat interval (IBI), standard deviation of IBIs, and root mean squared difference of adjacent IBIs) and three frequencydomain ECG measures (power in low frequency, power in high frequency, and ratio of power in low and high frequencies) were calculated. To compensate for individual differences in heart response during the driving tasks, a three-step data processing procedure was performed to ECG signals of each participant: (1) selection of two most sensitive ECG measures, (2) definition of three (low, medium, and high) cognitive workload levels, and (3) normalization of the selected ECG measures. An ANN model was constructed using a feed-forward network and scaled conjugate gradient as a back-propagation learning rule. The accuracy of the ANN classification model was found satisfactory for learning data (95%) and testing data (82%). Copyright © 2016 Elsevier Ltd. All rights reserved.

[Neurophenomenology: Project for a Science of Past Experiences].

PubMed

Segovia-Cuellar, Andrés

2012-09-01

Since the middle of 20(th) Century, cognitive science has been recognized as the genuine convergence field for all scientific advances in human mind studies with the mechanisms enabling knowledge. Since then, it has become a multidisciplinary area where several research disciplines and actors have acquired citizenship, allowing new expectations on the scientific study of human uniqueness. Critical assessment of the discussion that the discourse of theoretical biology has been assuming regarding the study of the cognitive phenomenon with special attention to the enactive project and, extensively, to the neuro-phenomenology of Francisco J. Varela. Starting with a brief and synthesized history of cognitive science, we will establish the key principles for understanding the emergence of the enactive paradigm and the "embodied" turn influenced by continental phenomenology in the cognitive science, as well as the general guidelines of Neurophenomenology. The "hard problem" of consciousness still faces several types of reductionism relegating the cognitive issue to a kind of merely rational, individual, abstract and disembodied mechanism, thus strengthening the functionalist paradigm in mind philosophy. A solution to classic dichotomies in mind sciences must start rejecting such assumptions. Copyright © 2012 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Potential consequences of clinical application of artificial gametes: a systematic review of stakeholder views.

PubMed

Hendriks, Saskia; Dondorp, Wybo; de Wert, Guido; Hamer, Geert; Repping, Sjoerd; Dancet, Eline A F

2015-01-01

Recent progress in the formation of artificial gametes, i.e. gametes generated from progenitors or somatic cells, has led to scientific and societal discussion about their use in medically assisted reproduction. In animals, live births have already been achieved using artificial gametes of varying (cell type) sources and biological research seems to be progressing steadily toward clinical application in humans. Artificial gametes could potentially help not only infertile heterosexual couples of reproductive age of which one or both partners lacks functional gametes, but also post-menopausal women and same-sex couples, to conceive a child who will be genetically related to them. But as clinical application of these new technologies may have wider societal consequences, a proactive consideration of the possible impact seems timely and important. This review aims to contribute to this by providing a systematic overview of the potential consequences of clinical application of artificial gametes anticipated by different stakeholders. The electronic database 'Medline/Pubmed' was systematically searched with medical subject heading terms (MesH) for articles published in English between January 1970 and December 2013. Articles were selected based on eligibility and reference lists of eligible studies were hand searched. The reported potential consequences of clinical application of artificial gametes were extracted from the articles and were grouped into categories by content analysis. Per category, we noted which stakeholders referred to which potential consequences, based on author affiliations and, if applicable, study participants. The systematic search yielded 2424 articles, and 84 studies were included after screening. Nine positive consequences, 21 specific consequences requiring consideration and 22 recommendations referring to clinical application of artificial gametes were documented. All positive consequences, consequences requiring consideration and recommendations could be categorized under the following eight objectives to be safeguarded during clinical application of artificial gametes: (i) timing the implementation of new treatments correctly, (ii) meeting 'plausible demands of patients', (iii) improving and safeguarding public health, (iv) promoting the progress of medical science in the interest of future patients, (v) providing treatments that are morally acceptable for the general public, (vi) controlling medical practice, (vii) offering treatments that allow acquisition of informed consent and (viii) funding treatments fairly. Professionals specialized in biomedical science, science journalists and professionals specialized in ethics all addressed these eight objectives on artificial gametes, whereas professionals specialized in law or political science addressed seven objectives. Although one study reported on the perspective of parents of under-aged patients on three objectives, the perspectives of patients themselves were not reported by the reviewed literature. Of course, clinical introduction of artificial gametes should only be considered on the basis of reassuring outcomes of appropriate preclinical effectiveness and safety studies. In addition, potential users' views on the desirability and acceptability of artificial gametes should be studied before clinical introduction. A societal debate including all stakeholders is needed to determine the relative importance of all arguments in favor of and against the introduction of artificial gametes into clinical practice. More broadly, establishing pre-implementation processes for new medical techniques is relevant for all fields of medicine. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Learning through Intermediate Problems in Creating Cognitive Models

ERIC Educational Resources Information Center

Miwa, Kazuhisa; Morita, Junya; Nakaike, Ryuichi; Terai, Hitoshi

2014-01-01

Cognitive modelling is one of the representative research methods in cognitive science. It is believed that creating cognitive models promotes learners' meta-cognitive activities such as self-monitoring and reflecting on their own cognitive processing. Preceding studies have confirmed that such meta-cognitive activities actually promote learning…

An organizing model for recent cognitive science work on the self.

PubMed

Pageler, Ben

2016-10-01

An organizing model of 'the self' emerges from applying various kinds of brain injury to recent cognitive science and philosophical work on 'the self'. This model unifies various contents and mechanisms central to current notions of the self. The article then highlights several criteria and aspects of this notion of self. Qualities of the right type and level of psychological significance delineate 'the self' as an organizing concept useful for recent philosophical work and cognitive science research. Copyright © 2016 Elsevier Inc. All rights reserved.

[Philosophy within the context of neurosciences].

PubMed

Estany, Anna

2013-03-16

Based on the interrelation between science and philosophy, this article addresses the impact of neurosciences on the philosophical issues posed by today's society, especially those related with epistemology and the philosophy of science. To do so, the different approaches in the cognitive sciences are taken into account, with special attention paid to those that have to do with social, embodied and situated cognition versus a more individual, rational and abstract cognition. This initial framework is taken as the starting point with which to analyse the ways of representing knowledge and the characteristics of the cognoscente agent.

Alignment of Assessment Objectives with Instructional Objectives Using Revised Bloom's Taxonomy--The Case for Food Science and Technology Education

ERIC Educational Resources Information Center

Jideani, V. A.; Jideani, I. A.

2012-01-01

Nine food science and technology (FST) subjects were assessed for alignment between the learning outcomes and assessment using revised Bloom's taxonomy (RBT) of cognitive knowledge. Conjoint analysis was used to estimate the utilities of the levels of cognitive, knowledge, and the attribute importance (cognitive process and knowledge dimension)…

Investigation of Dynamic Algorithms for Pattern Recognition Identified in Cerebral Cortex

DTIC Science & Technology

1991-12-02

oscillatory and possibly chaotic activity forin the actual cortical substrate of the diverse sensory, motor, and cognitive operations now studied in...September Neural Information Processing Systems - Natural and Synthetic, Denver, Colo., November 1989 U.C. San Diego, Cognitive Science Dept...Baird. Biologically applied neural networks may foster the co-evolution of neurobiology and cognitive psychology. Brain and Behavioral Sciences, 37

The tractable cognition thesis.

PubMed

Van Rooij, Iris

2008-09-01

The recognition that human minds/brains are finite systems with limited resources for computation has led some researchers to advance the Tractable Cognition thesis: Human cognitive capacities are constrained by computational tractability. This thesis, if true, serves cognitive psychology by constraining the space of computational-level theories of cognition. To utilize this constraint, a precise and workable definition of "computational tractability" is needed. Following computer science tradition, many cognitive scientists and psychologists define computational tractability as polynomial-time computability, leading to the P-Cognition thesis. This article explains how and why the P-Cognition thesis may be overly restrictive, risking the exclusion of veridical computational-level theories from scientific investigation. An argument is made to replace the P-Cognition thesis by the FPT-Cognition thesis as an alternative formalization of the Tractable Cognition thesis (here, FPT stands for fixed-parameter tractable). Possible objections to the Tractable Cognition thesis, and its proposed formalization, are discussed, and existing misconceptions are clarified. 2008 Cognitive Science Society, Inc.

Role of cognitive assessment for high school graduates prior to choosing their college major.

PubMed

AlAbdulwahab, Sami S; Kachanathu, Shaji John; AlSaeed, Abdullah Saad

2018-02-01

[Purpose] Academic performance of college students can be impacted by the efficacy of students' ability and teaching methods. It is important to assess the progression of college students' cognitive abilities among different college majors and as they move from junior to senior levels. However, dearth of studies have been examined the role of cognitive ability tests as a tool to determine the aptitude of the perspective students. Therefore, this study assessed cognitive abilities of computer science and ART students. [Subjects and Methods] Participants were 130 college students (70 computer and 60 art students) in their first and final years of study at King Saud University. Cognitive ability was assessed using the Test of Nonverbal Intelligence, Third Edition. [Results] The cognitive ability of computer science students were statistically better than that of art students and were shown improvement from junior to senior levels, while the cognitive ability of art students did not. [Conclusion] The cognitive ability of computer science college students was superior compared to those in art, indicating the importance of cognitive ability assessment for high school graduates prior to choosing a college major. Cognitive scales should be included as an aptitude assessment tool for decision-makers and prospective students to determine an appropriate career, which might reduce the rate of university drop out.

Introduction: philosophy in and philosophy of cognitive science.

PubMed

Brook, Andrew

2009-04-01

Despite being there from the beginning, philosophical approaches have never had a settled place in cognitive research and few cognitive researchers not trained in philosophy have a clear sense of what its role has been or should be. We distinguish philosophy in cognitive research and philosophy of cognitive research. Concerning philosophy in cognitive research, after exploring some standard reactions to this work by nonphilosophers, we will pay particular attention to the methods that philosophers use. Being neither experimental nor computational, they can leave others bewildered. Thought experiments are the most striking example but not the only one. Concerning philosophy of cognitive research, we will pay particular attention to its power to generate and test normative claims, claims about what should and should not be done. Copyright © 2009 Cognitive Science Society, Inc.

Artificial Exo-Society Modeling: a New Tool for SETI Research

NASA Astrophysics Data System (ADS)

Gardner, James N.

2002-01-01

One of the newest fields of complexity research is artificial society modeling. Methodologically related to artificial life research, artificial society modeling utilizes agent-based computer simulation tools like SWARM and SUGARSCAPE developed by the Santa Fe Institute, Los Alamos National Laboratory and the Bookings Institution in an effort to introduce an unprecedented degree of rigor and quantitative sophistication into social science research. The broad aim of artificial society modeling is to begin the development of a more unified social science that embeds cultural evolutionary processes in a computational environment that simulates demographics, the transmission of culture, conflict, economics, disease, the emergence of groups and coadaptation with an environment in a bottom-up fashion. When an artificial society computer model is run, artificial societal patterns emerge from the interaction of autonomous software agents (the "inhabitants" of the artificial society). Artificial society modeling invites the interpretation of society as a distributed computational system and the interpretation of social dynamics as a specialized category of computation. Artificial society modeling techniques offer the potential of computational simulation of hypothetical alien societies in much the same way that artificial life modeling techniques offer the potential to model hypothetical exobiological phenomena. NASA recently announced its intention to begin exploring the possibility of including artificial life research within the broad portfolio of scientific fields comprised by the interdisciplinary astrobiology research endeavor. It may be appropriate for SETI researchers to likewise commence an exploration of the possible inclusion of artificial exo-society modeling within the SETI research endeavor. Artificial exo-society modeling might be particularly useful in a post-detection environment by (1) coherently organizing the set of data points derived from a detected ETI signal, (2) mapping trends in the data points over time (assuming receipt of an extended ETI signal), and (3) projecting such trends forward to derive alternative cultural evolutionary scenarios for the exo-society under analysis. The latter exercise might be particularly useful to compensate for the inevitable time lag between generation of an ETI signal and receipt of an ETI signal on Earth. For this reason, such an exercise might be a helpful adjunct to the decisional process contemplated by Paragraph 9 of the Declaration of Principles Concerning Activities Following the Detection of Extraterrestrial Intelligence.

Artificial intelligence in medicine.

PubMed Central

Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

2004-01-01

INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. RESULTS: The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. DISCUSSION: Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting. PMID:15333167

Artificial intelligence in medicine.

PubMed

Ramesh, A N; Kambhampati, C; Monson, J R T; Drew, P J

2004-09-01

Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting.

An assessment of non-stationarity in physiological cognitive state assessment using artificial neural networks.

PubMed

Estepp, Justin R; Klosterman, Samantha L; Christensen, James C

2011-01-01

With increased attention toward physiological cognitive state assessment as a component in the larger field of applied neuroscience, the need to develop methods for robust, stable assessment of cognitive state has been expressed as critical to designing effective augmented human-machine systems. The technique of cognitive state assessment, as well as its benefits, has been demonstrated by many research groups. In an effort to move closer toward a realized system, efforts must now be focused on critical issues that remain unsolved, namely instability of pattern classifiers over the course of hours and days. This work, as part of the Cognitive State Assessment Competition 2011, seeks to explore methods for 'learning' non-stationarity as a mitigation for more generalized patterns that are stable over time courses that are not widely discussed in the literature.

Does attainment of Piaget's formal operational level of cognitive development predict student understanding of scientific models?

NASA Astrophysics Data System (ADS)

Lahti, Richard Dennis, II

Knowledge of scientific models and their uses is a concept that has become a key benchmark in many of the science standards of the past 30 years, including the proposed Next Generation Science Standards. Knowledge of models is linked to other important nature of science concepts such as theory change which are also rising in prominence in newer standards. Effective methods of instruction will need to be developed to enable students to achieve these standards. The literature reveals an inconsistent history of success with modeling education. These same studies point to a possible cognitive development component which might explain why some students succeeded and others failed. An environmental science course, rich in modeling experiences, was used to test both the extent to which knowledge of models and modeling could be improved over the course of one semester, and more importantly, to identify if cognitive ability was related to this improvement. In addition, nature of science knowledge, particularly related to theories and theory change, was also examined. Pretest and posttest results on modeling (SUMS) and nature of science (SUSSI), as well as data from the modeling activities themselves, was collected. Cognitive ability was measured (CTSR) as a covariate. Students' gain in six of seven categories of modeling knowledge was at least medium (Cohen's d >.5) and moderately correlated to CTSR for two of seven categories. Nature of science gains were smaller, although more strongly correlated with CTSR. Student success at creating a model was related to CTSR, significantly in three of five sub-categories. These results suggest that explicit, reflective experience with models can increase student knowledge of models and modeling (although higher cognitive ability students may have more success), but successfully creating models may depend more heavily on cognitive ability. This finding in particular has implications in the grade placement of modeling standards and curriculum chosen to help these students, particularly those with low cognitive ability, to meet the standards.

The cognitive capabilities of farm animals: categorisation learning in dwarf goats (Capra hircus).

PubMed

Meyer, Susann; Nürnberg, Gerd; Puppe, Birger; Langbein, Jan

2012-07-01

The ability to establish categories enables organisms to classify stimuli, objects and events by assessing perceptual, associative or rational similarities and provides the basis for higher cognitive processing. The cognitive capabilities of farm animals are receiving increasing attention in applied ethology, a development driven primarily by scientifically based efforts to improve animal welfare. The present study investigated the learning of perceptual categories in Nigerian dwarf goats (Capra hircus) by using an automated learning device installed in the animals' pen. Thirteen group-housed goats were trained in a closed-economy approach to discriminate artificial two-dimensional symbols presented in a four-choice design. The symbols belonged to two categories: category I, black symbols with an open centre (rewarded) and category II, the same symbols but filled black (unrewarded). One symbol from category I and three different symbols from category II were used to define a discrimination problem. After the training of eight problems, the animals were presented with a transfer series containing the training problems interspersed with completely new problems made from new symbols belonging to the same categories. The results clearly demonstrate that dwarf goats are able to form categories based on similarities in the visual appearance of artificial symbols and to generalise across new symbols. However, the goats had difficulties in discriminating specific symbols. It is probable that perceptual problems caused these difficulties. Nevertheless, the present study suggests that goats housed under farming conditions have well-developed cognitive abilities, including learning of open-ended categories. This result could prove beneficial by facilitating animals' adaptation to housing environments that favour their cognitive capabilities.

Operationalizing Cognitive Science and Technologies' Research and Development; the "Brain and Cognition Study Group (BCSG)" Initiative from Shiraz, Iran.

PubMed

Ashjazadeh, Nahid; Boostani, Reza; Ekhtiari, Hamed; Emamghoreishi, Masoumeh; Farrokhi, Majidreza; Ghanizadeh, Ahmad; Hatam, Gholamreza; Hadianfard, Habib; Lotfi, Mehrzad; Mortazavi, Seyed Mohammad Javad; Mousavi, Maryam; Montakhab, Afshin; Nili, Majid; Razmkon, Ali; Salehi, Sina; Sodagar, Amir Mohammad; Setoodeh, Peiman; Taghipour, Mousa; Torabi-Nami, Mohammad; Vesal, Abdolkarim

2014-01-01

Recent advances in brain and cognitive science studies have revolutionized concepts in neural dynamics, regulating mechanisms, coding systems and information processing networks which govern our function and behavior. Hidden aspects of neurological and psychiatric diseases are being understood and hopes for their treatment are emerging. Although the two comprehensive mega-projects on brain mapping are in place in the United States and Europe; the proportion of science contributed by the developing countries should not be downsized. With the granted supports from the Cognitive Sciences and Technologies Council (CSTC), Iran can take its role in research on brain and cognition further. The idea of research and development in Cognitive Sciences and Technologies (CST) is being disseminated across the country by CSTC. Towards this goal, the first Shiraz interdisciplinary meeting on CST was held on 9 January 2014 in Namazi hospital, Shiraz. CST research priorities, infrastructure development, education and promotion were among the main topics discussed during this interactive meeting. The steering committee of the first CST meeting in Shiraz decided to frame future research works within the "Brain and Cognition Study Group-Shiraz" (BCSG-Shiraz). The study group comprises scientific leaders from various allied disciplines including neuroscience, neurosurgery, neurology, psychiatry, psychology, radiology, physiology, bioengineering, biophysics, applied physics and telecommunication. As the headquarter for CST in the southern Iran, BCSG-Shiraz is determined to advocate "brain and cognition" awareness, education and research in close collaboration with CSTC. Together with CSTC, Shiraz Neuroscience Research center (SNRC) will take the initiative to cross boundaries in interdisciplinary works and multi-centric research projects within the study group.

The Reference Encounter Model.

ERIC Educational Resources Information Center

White, Marilyn Domas

1983-01-01

Develops model of the reference interview which explicitly incorporates human information processing, particularly schema ideas presented by Marvin Minsky and other theorists in cognitive processing and artificial intelligence. Questions are raised concerning use of content analysis of transcribed verbal protocols as methodology for studying…

Les Sciences Physiques À L'école Maternelle: Un Cadre Sociocognitif Pour La Construction Des Connaissances ET/OU LE Développement Des Activités Didactiques

NASA Astrophysics Data System (ADS)

Ravanis, Konstantinos

2005-05-01

NATURAL SCIENCES IN KINDERGARTEN: A SOCIO-COGNITIVE FRAMEWORK FOR LEARNING AND TEACHING - The present study presents a socio-cognitive framework for the construction of the scientific knowledge of natural phenomena among pre-school children and for the development of science activities at kindergarten. It involves elements from theories of social interaction; social psychology of development and cognitive functioning; and research in natural-science teaching methods which acknowledge the importance and fundamental role of social interaction in the development of cognitive operations and learning. The study also presents some of the more significant results of the research carried out on different aspects of this topic. The discussion unfolded here supports the hypothesis that the construction of natural-scientific knowledge at the pre-school age and corresponding scholastic activities are necessary and effective.

Applying the Science of Learning to the Learning of Science: Newton's Second Law of Motion

ERIC Educational Resources Information Center

Lemmer, Miriam

2018-01-01

Science teaching and learning require knowledge about how learning takes place (cognition) and how learners interact with their surroundings (affective and sociocultural factors). The study reported on focussed on learning for understanding of Newton's second law of motion from a cognitive perspective that takes social factors into account. A…

The Science of Numbers: Does Language Help or Hinder?

ERIC Educational Resources Information Center

Calude, Andreea S.

2011-01-01

This paper examines Roy Harris' discussion of number and the language of science in his book "History, Science and the Limits of Language" in light of recent work in cognitive linguistics. While many of his points are valid, linguistic theory has since addressed some of these concerns by formulating usage-based, cognitive frameworks to explore and…

Pre-Service Science Teachers' Cognitive Structure about Some Epidermal Structure in Plant

ERIC Educational Resources Information Center

Yener, Yesim

2017-01-01

The main focus of this study is to determine pre-service science teachers' cognitive structure about trichome and stoma through two alternative assessment techniques: metaphor and word association test. The study was conducted with 35 pre-service science teachers. Word association test given stoma and trichome as stimulant words was applied. Also…

Food Science Education and the Cognitive Science of Learning

ERIC Educational Resources Information Center

Chew, Stephen L.

2014-01-01

In this essay, I argue that the traditional view of teaching, that the teacher's responsibility is to present information that students are solely responsible for learning, has been rendered untenable by cognitive science research in learning. The teacher can have a powerful effect on student learning by teaching not only content, but how to…

A cognitive operating system (COGNOSYS) for JPL's robot, phase 1 report

NASA Technical Reports Server (NTRS)

Mathur, F. P.

1972-01-01

The most important software requirement for any robot development is the COGNitive Operating SYStem (COGNOSYS). This report describes the Stanford University Artificial Intelligence Laboratory's hand eye software system from the point of view of developing a cognitive operating system for JPL's robot. In this, the Phase 1 of the JPL robot COGNOSYS task the installation of a SAIL compiler and a FAIL assembler on Caltech's PDP-10 have been accomplished and guidelines have been prepared for the implementation of a Stanford University type hand eye software system on JPL-Caltech's computing facility. The alternatives offered by using RAND-USC's PDP-10 Tenex operating sytem are also considered.

Design-Based Intervention Research as the Science of the Doubly Artificial

ERIC Educational Resources Information Center

Cole, Michael; Packer, Martin

2016-01-01

This article uses a variety of principles of cultural-historical activity theory to extend Herbert Simon's (1996) insight into the inherent linkage between the creation of artifacts and design. We argue that design research must grapple with the doubly artificial, as the classrooms in which many educational designs are implemented are themselves…

Artificial multilayers and nanomagnetic materials

PubMed Central

SHINJO, Teruya

2013-01-01

The author has been actively engaged in research on nanomagnetic materials for about 50 years. Nanomagnetic materials are comprised of ferromagnetic systems for which the size and shape are controlled on a nanometer scale. Typical examples are ultrafine particles, ultrathin films, multilayered films and nano-patterned films. In this article, the following four areas of the author’s studies are described. (1) Mössbauer spectroscopic studies of nanomagnetic materials and interface magnetism. (2) Preparation and characterization of metallic multilayers with artificial superstructures. (3) Giant magnetoresistance (GMR) effect in magnetic multilayers. (4) Novel properties of nanostructured ferromagnetic thin films (dots and wires). A subject of particular interest in the author’s research was the artificially prepared multilayers consisting of metallic elements. The motivation to initiate the multilayer investigation is described and the physical properties observed in the artificial multilayers are introduced. The author’s research was initially in the field of pure physical science and gradually extended into applied science. His achievements are highly regarded not only from the fundamental point of view but also from the technological viewpoint. PMID:23391605

Challenges and promises of integrating knowledge engineering and qualitative methods

NASA Astrophysics Data System (ADS)

Lundberg, C. Gustav; Holm, Gunilla

Our goal is to expose some of the close ties that exist between knowledge engineering (KE) and qualitative methodology (QM). Many key concepts of qualitative research, for example meaning, commonsense, understanding, and everyday life, overlap with central research concerns in artificial intelligence. These shared interests constitute a largely unexplored avenue for interdisciplinary cooperation. We compare and take some steps toward integrating two historically diverse methodologies by exploring the commonalities of KE and QM both from a substantive and a methodological/technical perspective. In the second part of this essay, we address knowledge acquisition problems and procedures. Knowledge acquisition within KE has been based primarily on cognitive psychology/science foundations, whereas knowledge acquisition within QM has a broader foundation in phenomenology, symbolic interactionism, and ethnomethodology. Our discussion and examples are interdisciplinary in nature. We do not suggest that there is a clash between the KE and QM frameworks, but rather that the lack of communication potentially may limit each framework's future development.

Robots Learn to Recognize Individuals from Imitative Encounters with People and Avatars

NASA Astrophysics Data System (ADS)

Boucenna, Sofiane; Cohen, David; Meltzoff, Andrew N.; Gaussier, Philippe; Chetouani, Mohamed

2016-02-01

Prior to language, human infants are prolific imitators. Developmental science grounds infant imitation in the neural coding of actions, and highlights the use of imitation for learning from and about people. Here, we used computational modeling and a robot implementation to explore the functional value of action imitation. We report 3 experiments using a mutual imitation task between robots, adults, typically developing children, and children with Autism Spectrum Disorder. We show that a particular learning architecture - specifically one combining artificial neural nets for (i) extraction of visual features, (ii) the robot’s motor internal state, (iii) posture recognition, and (iv) novelty detection - is able to learn from an interactive experience involving mutual imitation. This mutual imitation experience allowed the robot to recognize the interactive agent in a subsequent encounter. These experiments using robots as tools for modeling human cognitive development, based on developmental theory, confirm the promise of developmental robotics. Additionally, findings illustrate how person recognition may emerge through imitative experience, intercorporeal mapping, and statistical learning.

Intelligent Learning System using cognitive science theory and artificial intelligence methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cristensen, D.L.

1986-01-01

This dissertation is a presentation of a theoretical model of an intelligent Learning System (ILS). The approach view intelligent computer-based instruction on a curricular-level and educational-theory base, instead of the conventional instructional-only level. The ILS is divided into two components: (1) macro-level, curricular; and (2) micro-level (MAIS), instructional. The primary purpose of the ILS macro level is to establish the initial conditions of learning by considering individual difference variables within specification of the curriculum content domain. Second, the ILS macro-level will iteratively update the conditions of learning as the individual student progresses through the given curriculum. The term dynamic ismore » used to describe the expert tutor that establishes and monitors the conditions of instruction between the ILS macro level and the micro level. As the student progresses through the instruction, appropriate information is sent back continuously to the macro level to constantly improve decision making for succeeding conditions of instruction.« less

Planning, Anticipatory Systems, and Kinds of Actors

NASA Astrophysics Data System (ADS)

Jorna, René; van Wezel, Wout

2002-09-01

Anticipation and planning have much in common. Anticipation means being ahead of things. Planning means not only anticipating on things to come, but also trying to determine a course of action to reach a goal. Planning is investigated in many domains, for example, in economy, biology, and in the cognitive sciences. Each of these domains uses its own research methodologies, languages, ontologies, and models. Although there are many differences between the various approaches and models, there must of course also be similarities, since they all deal with establishing a future course of actions to reach a goal. We will compare several planning approaches on a number of aspects, e.g., the kind of entity that makes the plan (natural or artificial), whether the plan is executed by the planner or by another entity, representational issues, and the domain that the plan is executed in. Our article focuses on analytical dimensions in the extended field of planning. We do not discuss empirical results.

Robots Learn to Recognize Individuals from Imitative Encounters with People and Avatars

PubMed Central

Boucenna, Sofiane; Cohen, David; Meltzoff, Andrew N.; Gaussier, Philippe; Chetouani, Mohamed

2016-01-01

Prior to language, human infants are prolific imitators. Developmental science grounds infant imitation in the neural coding of actions, and highlights the use of imitation for learning from and about people. Here, we used computational modeling and a robot implementation to explore the functional value of action imitation. We report 3 experiments using a mutual imitation task between robots, adults, typically developing children, and children with Autism Spectrum Disorder. We show that a particular learning architecture - specifically one combining artificial neural nets for (i) extraction of visual features, (ii) the robot’s motor internal state, (iii) posture recognition, and (iv) novelty detection - is able to learn from an interactive experience involving mutual imitation. This mutual imitation experience allowed the robot to recognize the interactive agent in a subsequent encounter. These experiments using robots as tools for modeling human cognitive development, based on developmental theory, confirm the promise of developmental robotics. Additionally, findings illustrate how person recognition may emerge through imitative experience, intercorporeal mapping, and statistical learning. PMID:26844862

The roles of consistency and exclusivity in perceiving body ownership and agency.

PubMed

Ma, Ke; Hommel, Bernhard; Chen, Hong

2018-01-23

Previous rubber/virtual hand illusion studies have established important constraints for the illusion that an artificial effector becomes part of one's own body (perceived ownership), and that its actions are being caused by oneself (perceived agency). We can take these observed constraints to establish two of three Wegner's (Trends Cogn Sci 7:65-69; Wegner, Trends in Cognitive Sciences 7:65-69, 2003) criteria for the perception of personal agency: priority and consistency, but not Wegner's third criterion-exclusivity. In this study we tested with virtual hand illusion, whether exclusivity (participant is certain who was controlling the virtual effector) can also be established. We manipulated two factors: exclusivity and consistency. Our results show that on both ownership and agency judgments, consistency and exclusivity produced main effects, and the two effects interacted in an underadditive fashion. Taken together, these findings provide support for our suggestion to extend Wegner's agency theory to explain perceived body ownership, which in turn provides an integrative framework for interpreting constraints on ownership and agency illusions.

Visual Similarity of Words Alone Can Modulate Hemispheric Lateralization in Visual Word Recognition: Evidence From Modeling Chinese Character Recognition.

PubMed

Hsiao, Janet H; Cheung, Kit

2016-03-01

In Chinese orthography, the most common character structure consists of a semantic radical on the left and a phonetic radical on the right (SP characters); the minority, opposite arrangement also exists (PS characters). Recent studies showed that SP character processing is more left hemisphere (LH) lateralized than PS character processing. Nevertheless, it remains unclear whether this is due to phonetic radical position or character type frequency. Through computational modeling with artificial lexicons, in which we implement a theory of hemispheric asymmetry in perception but do not assume phonological processing being LH lateralized, we show that the difference in character type frequency alone is sufficient to exhibit the effect that the dominant type has a stronger LH lateralization than the minority type. This effect is due to higher visual similarity among characters in the dominant type than the minority type, demonstrating the modulation of visual similarity of words on hemispheric lateralization. Copyright © 2015 Cognitive Science Society, Inc.

Design of cognitive engine for cognitive radio based on the rough sets and radial basis function neural network

NASA Astrophysics Data System (ADS)

Yang, Yanchao; Jiang, Hong; Liu, Congbin; Lan, Zhongli

2013-03-01

Cognitive radio (CR) is an intelligent wireless communication system which can dynamically adjust the parameters to improve system performance depending on the environmental change and quality of service. The core technology for CR is the design of cognitive engine, which introduces reasoning and learning methods in the field of artificial intelligence, to achieve the perception, adaptation and learning capability. Considering the dynamical wireless environment and demands, this paper proposes a design of cognitive engine based on the rough sets (RS) and radial basis function neural network (RBF_NN). The method uses experienced knowledge and environment information processed by RS module to train the RBF_NN, and then the learning model is used to reconfigure communication parameters to allocate resources rationally and improve system performance. After training learning model, the performance is evaluated according to two benchmark functions. The simulation results demonstrate the effectiveness of the model and the proposed cognitive engine can effectively achieve the goal of learning and reconfiguration in cognitive radio.

Information processing, computation, and cognition.

PubMed

Piccinini, Gualtiero; Scarantino, Andrea

2011-01-01

Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both - although others disagree vehemently. Yet different cognitive scientists use 'computation' and 'information processing' to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In this paper, we address this unsatisfactory state of affairs by presenting a general and theory-neutral account of computation and information processing. We also apply our framework by analyzing the relations between computation and information processing on one hand and classicism, connectionism, and computational neuroscience on the other. We defend the relevance to cognitive science of both computation, at least in a generic sense, and information processing, in three important senses of the term. Our account advances several foundational debates in cognitive science by untangling some of their conceptual knots in a theory-neutral way. By leveling the playing field, we pave the way for the future resolution of the debates' empirical aspects.

Investigating surety methodologies for cognitive systems.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caudell, Thomas P.; Peercy, David Eugene; Mills, Kristy

2006-11-01

Advances in cognitive science provide a foundation for new tools that promise to advance human capabilities with significant positive impacts. As with any new technology breakthrough, associated technical and non-technical risks are involved. Sandia has mitigated both technical and non-technical risks by applying advanced surety methodologies in such areas as nuclear weapons, nuclear reactor safety, nuclear materials transport, and energy systems. In order to apply surety to the development of cognitive systems, we must understand the concepts and principles that characterize the certainty of a system's operation as well as the risk areas of cognitive sciences. This SAND report documentsmore » a preliminary spectrum of risks involved with cognitive sciences, and identifies some surety methodologies that can be applied to potentially mitigate such risks. Some potential areas for further study are recommended. In particular, a recommendation is made to develop a cognitive systems epistemology framework for more detailed study of these risk areas and applications of surety methods and techniques.« less

Using Educational Neuroscience and Psychology to Teach Science. Part 1: A Case Study Review of Cognitive Load Theory (CLT) and Cognitive Acceleration through Science Education (CASE)

ERIC Educational Resources Information Center

Jenkins, Rebecca Torrance

2017-01-01

This article is the first of a two-part series that explores science teachers' and their pupils' experiences of using different pedagogical approaches based on understandings of how brains learn. For this case-study research, nine science teachers were interviewed and four teachers self-selected to trial a pedagogical approach, new to them, from…

Conceptual metaphors and mathematical practice: on cognitive studies of historical developments in mathematics.

PubMed

Schlimm, Dirk

2013-04-01

This article looks at recent work in cognitive science on mathematical cognition from the perspective of history and philosophy of mathematical practice. The discussion is focused on the work of Lakoff and Núñez, because this is the first comprehensive account of mathematical cognition that also addresses advanced mathematics and its history. Building on a distinction between mathematics as it is presented in textbooks and as it presents itself to the researcher, it is argued that the focus of cognitive analyses of historical developments of mathematics has been primarily on the former, even if they claim to be about the latter. Copyright © 2013 Cognitive Science Society, Inc.

Artificial selection on male genitalia length alters female brain size.

PubMed

Buechel, Séverine D; Booksmythe, Isobel; Kotrschal, Alexander; Jennions, Michael D; Kolm, Niclas

2016-11-30

Male harassment is a classic example of how sexual conflict over mating leads to sex-specific behavioural adaptations. Females often suffer significant costs from males attempting forced copulations, and the sexes can be in an arms race over male coercion. Yet, despite recent recognition that divergent sex-specific interests in reproduction can affect brain evolution, sexual conflict has not been addressed in this context. Here, we investigate whether artificial selection on a correlate of male success at coercion, genital length, affects brain anatomy in males and females. We analysed the brains of eastern mosquitofish (Gambusia holbrooki), which had been artificially selected for long or short gonopodium, thereby mimicking selection arising from differing levels of male harassment. By analogy to how prey species often have relatively larger brains than their predators, we found that female, but not male, brain size was greater following selection for a longer gonopodium. Brain subregion volumes remained unchanged. These results suggest that there is a positive genetic correlation between male gonopodium length and female brain size, which is possibly linked to increased female cognitive ability to avoid male coercion. We propose that sexual conflict is an important factor in the evolution of brain anatomy and cognitive ability. © 2016 The Author(s).

Northeast Artificial Intelligence Consortium (NAIC). Volume 9. A Planner System for the Application of Indications and Warning

DTIC Science & Technology

1990-12-01

personality of other cognitive entities in the world. POPLAR is a step towards an AI system whose behavior is psychologically justified and can provide the...natural language capability (i.e. the ver- bal behavior of 1) and 5) are not addressed). Nor do we tackle in any complete ard principled manner the...human cognitive behavior . This property makes POPLAR 1.3 personality-oriented, i.e. provision is made in the present model for introducing personality

A Play on Words: Using Cognitive Computing as a Basis for AI Solvers in Word Puzzles

NASA Astrophysics Data System (ADS)

Manzini, Thomas; Ellis, Simon; Hendler, James

2015-12-01

In this paper we offer a model, drawing inspiration from human cognition and based upon the pipeline developed for IBM's Watson, which solves clues in a type of word puzzle called syllacrostics. We briefly discuss its situation with respect to the greater field of artificial general intelligence (AGI) and how this process and model might be applied to other types of word puzzles. We present an overview of a system that has been developed to solve syllacrostics.

Lecture Notes in Artificial Intelligence 689: Methodologies for Intelligent Systems: International Symposium, ISMIS 󈨡 (7th) Held at Trondheim (Norway) April 1993

DTIC Science & Technology

1993-06-18

expresses 171 From our earliest days we learn to perceive time as a result of two im- portant cognitive abilities : the awareness of change in the world...agent. - Learning and cognition are closely related. Between the levels of sensory percep- tion and abstract language there are several levels of...Kaufmann, Los Altos, California, 1988. Previously available as I Report PM-01-87, School of Mathematics , University of Bristol. [13] Y. Shoham

A surety engineering framework to reduce cognitive systems risks.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caudell, Thomas P.; Peercy, David Eugene; Caldera, Eva O.

Cognitive science research investigates the advancement of human cognition and neuroscience capabilities. Addressing risks associated with these advancements can counter potential program failures, legal and ethical issues, constraints to scientific research, and product vulnerabilities. Survey results, focus group discussions, cognitive science experts, and surety researchers concur technical risks exist that could impact cognitive science research in areas such as medicine, privacy, human enhancement, law and policy, military applications, and national security (SAND2006-6895). This SAND report documents a surety engineering framework and a process for identifying cognitive system technical, ethical, legal and societal risks and applying appropriate surety methods to reducemore » such risks. The framework consists of several models: Specification, Design, Evaluation, Risk, and Maturity. Two detailed case studies are included to illustrate the use of the process and framework. Several Appendices provide detailed information on existing cognitive system architectures; ethical, legal, and societal risk research; surety methods and technologies; and educing information research with a case study vignette. The process and framework provide a model for how cognitive systems research and full-scale product development can apply surety engineering to reduce perceived and actual risks.« less

Using science digital storytelling to increase students’ cognitive ability

NASA Astrophysics Data System (ADS)

Dewi, N. R.; Savitri, E. N.; Taufiq, M.; Khusniati, M.

2018-04-01

The purpose of this research is to understand whether or not science digital storytelling can improve cognitive ability. The research design used in this study was one shoot case study. The population of the research was seventh-grade students of junior high school. The number of samples involved in this study was two classes with a total of 68 students. Data of students' cognitive ability were collected using a test. The data that has been collected were then analyzed using N-gain test. Results of data analysis showed that N-gain values of experimental groups are equal to 0.48 and 0.42 which are categorized into medium category. This finding indicates that science digital storytelling can improve students' cognitive ability.

Cognitive Science.

ERIC Educational Resources Information Center

Cocking, Rodney R.; Mestre, Jose P.

The focus of this paper is on cognitive science as a model for understanding the application of human skills toward effective problem-solving. Sections include: (1) "Introduction" (discussing information processing framework, expert-novice distinctions, schema theory, and learning process); (2) "Application: The Expert-Novice…

Putting Cognitive Science behind a Statistics Teacher's Intuition

ERIC Educational Resources Information Center

Jones, Karrie A.; Jones, Jennifer L.; Vermette, Paul J.

2011-01-01

Recent advances in cognitive science have led to an enriched understanding of how people learn. Using a framework presented by Willingham, this article examines instructional best practice from the perspective of conceptual understanding and its implications on statistics education.

Probability-Based Inference in a Domain of Proportional Reasoning Tasks

DTIC Science & Technology

1992-01-01

Embretson, S.E. (1985). Multicomponent latent trait models for test design. In SE. Embretson (Ed.), Test design: Developments in psychology and...J.C. Conoley, & J. Witt (Eds.), The influence of cognitive psychology on testing and measurement: The Buros-Nebraska Symposium on measurement and...Mislevy Educational Testing Service This research was sponsored in part by the Cognitive Science Program Cognitive and Neural Sciences Division Office of

Cognitive Model Exploration and Optimization: A New Challenge for Computational Science

DTIC Science & Technology

2010-01-01

Introduction Research in cognitive science often involves the generation and analysis of computational cognitive models to explain various...HPC) clusters and volunteer computing for large-scale computational resources. The majority of applications on the Department of Defense HPC... clusters focus on solving partial differential equations (Post, 2009). These tend to be lean, fast models with little noise. While we lack specific

Cognitive Works Aids for C2 Planning: Actionable Information to Support Operational Decision Making

DTIC Science & Technology

2005-06-01

Information to Support Operational Decision Making Topic: Decisionmaking and Cognitive Science Jeffrey Wampler†*, Randall Whitaker§, Emilie...channeled through this state-of- the- art mobility C2 hub. It is a global AOC with several hundred people planning and executing around 350 missions...2005 Topical Area: Decisionmaking and Cognitive Science CONFERENCE PRESENTATION BY: RANDALL WHITAKER, PH.D. NORTHROP GRUMMAN INFORMATION TECHNOLOGY

Citizen Science Provides Valuable Data for Monitoring Global Night Sky Luminance

PubMed Central

Kyba, Christopher C. M.; Wagner, Janna M.; Kuechly, Helga U.; Walker, Constance E.; Elvidge, Christopher D.; Falchi, Fabio; Ruhtz, Thomas; Fischer, Jürgen; Hölker, Franz

2013-01-01

The skyglow produced by artificial lights at night is one of the most dramatic anthropogenic modifications of Earth's biosphere. The GLOBE at Night citizen science project allows individual observers to quantify skyglow using star maps showing different levels of light pollution. We show that aggregated GLOBE at Night data depend strongly on artificial skyglow, and could be used to track lighting changes worldwide. Naked eye time series can be expected to be very stable, due to the slow pace of human eye evolution. The standard deviation of an individual GLOBE at Night observation is found to be 1.2 stellar magnitudes. Zenith skyglow estimates from the “First World Atlas of Artificial Night Sky Brightness” are tested using a subset of the GLOBE at Night data. Although we find the World Atlas overestimates sky brightness in the very center of large cities, its predictions for Milky Way visibility are accurate. PMID:23677222

[Conceptual Development in Cognitive Science. Part II].

PubMed

Fierro, Marco

2012-03-01

Cognitive science has become the most influential paradigm on mental health in the late 20(th) and the early 21(st) centuries. In few years, the concepts, problem approaches and solutions proper to this science have significantly changed. Introduction and discussion of the fundamental concepts of cognitive science divided in four stages: Start, Classic Cognitivism, Connectionism, and Embodying / Enacting. The 2(nd) Part of the paper discusses the above mentioned fourth stage and explores the clinical setting, especially in terms of cognitive psychotherapy. The embodying/enacting stage highlights the role of the body including a set of determined evolutionary movements which provide a way of thinking and exploring the world. The performance of cognitive tasks is considered as a process that uses environmental resources that enhances mental skills and deploys them beyond the domestic sphere of the brain. On the other hand, body and mind are embedded in the world, thus giving rise to cognition when interacting, a process known as enacting. There is a close connection between perception and action, hence the interest in real-time interactions with the world rather than abstract reasoning. Regarding clinics, specifically the cognitive therapy, there is little conceptual discussion maybe due to good results from practice that may led us to consider that theoretical foundations are firm and not problem-raising. Copyright © 2012 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

The poverty of embodied cognition.

PubMed

Goldinger, Stephen D; Papesh, Megan H; Barnhart, Anthony S; Hansen, Whitney A; Hout, Michael C

2016-08-01

In recent years, there has been rapidly growing interest in embodied cognition, a multifaceted theoretical proposition that (1) cognitive processes are influenced by the body, (2) cognition exists in the service of action, (3) cognition is situated in the environment, and (4) cognition may occur without internal representations. Many proponents view embodied cognition as the next great paradigm shift for cognitive science. In this article, we critically examine the core ideas from embodied cognition, taking a "thought exercise" approach. We first note that the basic principles from embodiment theory are either unacceptably vague (e.g., the premise that perception is influenced by the body) or they offer nothing new (e.g., cognition evolved to optimize survival, emotions affect cognition, perception-action couplings are important). We next suggest that, for the vast majority of classic findings in cognitive science, embodied cognition offers no scientifically valuable insight. In most cases, the theory has no logical connections to the phenomena, other than some trivially true ideas. Beyond classic laboratory findings, embodiment theory is also unable to adequately address the basic experiences of cognitive life.

The Poverty of Embodied Cognition

PubMed Central

Goldinger, Stephen D.; Papesh, Megan H.; Barnhart, Anthony S.; Hansen, Whitney A.; Hout, Michael C.

2016-01-01

In recent years, there has been rapidly growing interest in Embodied Cognition, a multifaceted theoretical proposition that (1) cognitive processes are influenced by the body, (2) cognition exists in the service of action, (3) cognition is situated in the environment, and (4) cognition may occur without internal representations. Many proponents view embodied cognition as the next great paradigm shift for cognitive science. In this article, we critically examine the core ideas from embodied cognition, taking a “thought exercise” approach. We first note that the basic principles from embodiment theory are either unacceptably vague (e.g., the premise that perception is influenced by the body) or they offer nothing new (e.g., cognition evolved to optimize survival, emotions affect cognition, perception-action couplings are important). We next suggest that, for the vast majority of classic findings in cognitive science, embodied cognition offers no scientifically valuable insight. In most cases, the theory has no logical connections to the phenomena, other than some trivially true ideas. Beyond classic laboratory findings, embodiment theory is also unable to adequately address the basic experiences of cognitive life. PMID:27282990

Expert Causal Reasoning and Explanation.

ERIC Educational Resources Information Center

Kuipers, Benjamin

The relationship between cognitive psychologists and researchers in artificial intelligence carries substantial benefits for both. An ongoing investigation in causal reasoning in medical problem solving systems illustrates this interaction. This paper traces a dialectic of sorts in which three different types of causal resaoning for medical…

Development of Elementary School Students' Cognitive Structures and Information Processing Strategies under Long-Term Constructivist-Oriented Science Instruction

ERIC Educational Resources Information Center

Wu, Ying-Tien; Tsai, Chin-Chung

2005-01-01

The main purpose of this study was to explore the effects of long-term constructivist-oriented science instruction on elementary school students' process of constructing cognitive structures. Furthermore, such effects on different science achievers were also investigated. The subjects of this study were 69 fifth graders in Taiwan, while they were…

The theoretical cognitive process of visualization for science education.

PubMed

Mnguni, Lindelani E

2014-01-01

The use of visual models such as pictures, diagrams and animations in science education is increasing. This is because of the complex nature associated with the concepts in the field. Students, especially entrant students, often report misconceptions and learning difficulties associated with various concepts especially those that exist at a microscopic level, such as DNA, the gene and meiosis as well as those that exist in relatively large time scales such as evolution. However the role of visual literacy in the construction of knowledge in science education has not been investigated much. This article explores the theoretical process of visualization answering the question "how can visual literacy be understood based on the theoretical cognitive process of visualization in order to inform the understanding, teaching and studying of visual literacy in science education?" Based on various theories on cognitive processes during learning for science and general education the author argues that the theoretical process of visualization consists of three stages, namely, Internalization of Visual Models, Conceptualization of Visual Models and Externalization of Visual Models. The application of this theoretical cognitive process of visualization and the stages of visualization in science education are discussed.

Cognitive accuracy and intelligent executive function in the brain and in business.

PubMed

Bailey, Charles E

2007-11-01

This article reviews research on cognition, language, organizational culture, brain, behavior, and evolution to posit the value of operating with a stable reference point based on cognitive accuracy and a rational bias. Drawing on rational-emotive behavioral science, social neuroscience, and cognitive organizational science on the one hand and a general model of brain and frontal lobe executive function on the other, I suggest implications for organizational success. Cognitive thought processes depend on specific brain structures functioning as effectively as possible under conditions of cognitive accuracy. However, typical cognitive processes in hierarchical business structures promote the adoption and application of subjective organizational beliefs and, thus, cognitive inaccuracies. Applying informed frontal lobe executive functioning to cognition, emotion, and organizational behavior helps minimize the negative effects of indiscriminate application of personal and cultural belief systems to business. Doing so enhances cognitive accuracy and improves communication and cooperation. Organizations operating with cognitive accuracy will tend to respond more nimbly to market pressures and achieve an overall higher level of performance and employee satisfaction.

Sandia National Laboratories: 100 Resilient Cities

Science.gov Websites

Materials Science Nanodevices & Microsystems Radiation Effects & High Energy Density Science front of monitors Emergency Response Cognitive testing Psychological/ Cognitive Effects The Rockefeller Body's Systems - 100 Resilient Cities Blog News Releases City resilience: Sandia analyzes effects of

Decision Making, Models of Mind, and the New Cognitive Science.

ERIC Educational Resources Information Center

Evers, Colin W.

1998-01-01

Explores implications for understanding educational decision making from a cognitive science perspective. Examines three models of mind providing the methodological framework for decision-making studies. The "absent mind" embodies the behaviorist research tradition. The "functionalist mind" underwrites traditional cognitivism…

Priming as a Motivating Factor in Sociophonetic Variation and Change.

PubMed

Clark, Lynn

2018-04-24

Understanding how and why pronunciations vary and change has been a dominant theme in variationist sociolinguistics (Labov, , ). Linguistic variability has also been an area of focus in psychology and cognitive science. Work from these two fields has shown that where variation exists in language, an alternative form, once used, persists in working memory and has a greater chance of reuse (Bock, ; Bock & Loebell, ; Branigan, Pickering, & Cleland, ). While there have been efforts to connect priming research with sociolinguistics at the level of grammar (Poplack, ; Travis, ), there has been less work which explicitly considers the potential role of priming as a motivating factor in accent variation and change. This paper explores the role of priming in a socially conditioned sound change. There are two main findings: (a) phonetic variants with the same voicing tend to cluster together in naturally occurring speech and (b) repetition of phonetic form interacts with widely attested sociolinguistic predictors of variation. I argue that there are benefits to both cognitive science and sociolinguistics from this synergy: Incorporating research from cognitive science into sociolinguistics provides us with a better understanding of the factors underpinning a sound change in progress; incorporating insights from sociolinguistics into cognitive science shows that priming does not always operate in the same way for all speakers. Copyright © 2018 Cognitive Science Society, Inc.

Space science experimentation automation and support

NASA Technical Reports Server (NTRS)

Frainier, Richard J.; Groleau, Nicolas; Shapiro, Jeff C.

1994-01-01

This paper outlines recent work done at the NASA Ames Artificial Intelligence Research Laboratory on automation and support of science experiments on the US Space Shuttle in low earth orbit. Three approaches to increasing the science return of these experiments using emerging automation technologies are described: remote control (telescience), science advisors for astronaut operators, and fully autonomous experiments. The capabilities and limitations of these approaches are reviewed.

Developing team cognition: A role for simulation

PubMed Central

Fernandez, Rosemarie; Shah, Sachita; Rosenman, Elizabeth D.; Kozlowski, Steve W. J.; Parker, Sarah Henrickson; Grand, James A.

2016-01-01

SUMMARY STATEMENT Simulation has had a major impact in the advancement of healthcare team training and assessment. To date, the majority of simulation-based training and assessment focuses on the teamwork behaviors that impact team performance, often ignoring critical cognitive, motivational, and affective team processes. Evidence from team science research demonstrates a strong relationship between team cognition and team performance and suggests a role for simulation in the development of this team-level construct. In this article we synthesize research from the broader team science literature to provide foundational knowledge regarding team cognition and highlight best practices for using simulation to target team cognition. PMID:28704287

The evolution and extinction of science fiction.

PubMed

Hrotic, Steven

2014-11-01

Science fiction literature reflects our constantly evolving attitudes towards science and technological innovations, and the kinds of societal impacts believed possible. The newly popular subgenre 'steampunk' shows that these attitudes have significantly shifted. Examined from a cognitive anthropological perspective, science fiction reveals the cultural evolution of the genre as intelligently designed, and implies a cognitive mechanism of group membership reliant on implicit memory. However, such an analysis also suggests that genre science fiction as it was in the 20th century may no longer exist. © The Author(s) 2013.

[Artificial organs].

PubMed

Raguin, Thibaut; Dupret-Bories, Agnès; Debry, Christian

2017-01-01

Research has been fighting against organ failure and shortage of donations by supplying artificial organs for many years. With the raise of new technologies, tissue engineering and regenerative medicine, many organs can benefit of an artificial equivalent: thanks to retinal implants some blind people can visualize stimuli, an artificial heart can be proposed in case of cardiac failure while awaiting for a heart transplant, artificial larynx enables laryngectomy patients to an almost normal life, while the diabetic can get a glycemic self-regulation controlled by smartphones with an artificial device. Dialysis devices become portable, as well as the oxygenation systems for terminal respiratory failure. Bright prospects are being explored or might emerge in a near future. However, the retrospective assessment of putative side effects is not yet sufficient. Finally, the cost of these new devices is significant even if the advent of three dimensional printers may reduce it. © 2017 médecine/sciences – Inserm.

Learning Evolution and the Nature of Science Using Evolutionary Computing and Artificial Life

ERIC Educational Resources Information Center

Pennock, Robert T.

2007-01-01

Because evolution in natural systems happens so slowly, it is difficult to design inquiry-based labs where students can experiment and observe evolution in the way they can when studying other phenomena. New research in evolutionary computation and artificial life provides a solution to this problem. This paper describes a new A-Life software…

Data mining: sophisticated forms of managed care modeling through artificial intelligence.

PubMed

Borok, L S

1997-01-01

Data mining is a recent development in computer science that combines artificial intelligence algorithms and relational databases to discover patterns automatically, without the use of traditional statistical methods. Work with data mining tools in health care is in a developmental stage that holds great promise, given the combination of demographic and diagnostic information.

The Seeds of Artificial Intelligence. SUMEX-AIM.

ERIC Educational Resources Information Center

Research Resources Information Center, Rockville, MD.

Written to provide an understanding of the broad base of information on which the artificial intelligence (AI) branch of computer science rests, this publication presents a general view of AI, the concepts from which it evolved, its current abilities, and its promise for research. The focus is on a community of projects that use the SUMEX-AIM…

Issues or Identity? Cognitive Foundations of Voter Choice

PubMed Central

Jenke, Libby; Huettel, Scott A.

2016-01-01

Voter choice is one of the most important problems in political science. The most common models assume that voting is a rational choice based on policy positions (e.g., key issues) and non-policy information (e.g., social identity, personality). Though such models explain macroscopic features of elections, they also reveal important anomalies that have been resistant to explanation. We argue for a new approach that builds upon recent research in cognitive science and neuroscience; specifically, we contend that policy positions and social identities do not combine in merely an additive manner, but compete to determine voter preferences. This model not only explains several key anomalies in voter choice, but also suggests new directions for research in both political science and cognitive science. PMID:27769726

Literacy Strategies in the Science Classroom The Influence of Teacher Cognitive Resources on Implementation

NASA Astrophysics Data System (ADS)

Mawyer, Kirsten Kamaile Noelani

Scientific literacy is at the heart of science reform (AAAS, 1989; 1993: NRC, 1996). These initiatives advocate inquiry-based science education reform that promotes scientific literacy as the prerequisite ability to both understand and apply fundamental scientific ideas to real-world problems and issues involving science, technology, society and the environment. It has been argued that literacy, the very ability to read and write, is foundational to western science and is essential for the attainment of scientific literacy and the reform of science education in this country (Norris & Phillips, 2004). With this wave of reform comes the need to study initiatives that seek to support science teachers, as they take on the task of becoming teachers of literacy in the secondary science classroom. This qualitative research examines one such initiative that supports and guides teachers implementing literacy strategies designed to help students develop reading skills that will allow them to read closely, effectively, and with greater comprehension of texts in the context of science. The goal of this study is to gather data as teachers learn about literacy strategies through supports built into curricular materials, professional development, and implementation in the classroom. In particular, this research follows four secondary science teachers implementing literacy strategies as they enact a yearlong earth and environmental science course comprised of two different reform science curricula. The findings of this research suggest teacher's development of teacher cognitive resources bearing on Teaching & Design can be dynamic or static. They also suggest that the development of pedagogical design capacity (PDC) can be either underdeveloped or emergent. This study contributes to current understandings of the participatory relationship between curricular resources and teacher cognitive resources that reflects the design decision of teachers. In particular, it introduces a Cognitive Resources Framework, a tool researchers can use to identify the cognitive resources of teachers, and adds to the characterization of PDC. The data emerging from this study will inform the future design and refinement of curricular and professional development materials to better support teachers as they learn, use and adapt literacy strategies in the science classroom.

Embodied experiences for science learning: A cognitive linguistics exploration of middle school students' language in learning about water

NASA Astrophysics Data System (ADS)

Salinas Barrios, Ivan Eduardo

I investigated linguistic patterns in middle school students' writing to understand their relevant embodied experiences for learning science. Embodied experiences are those limited by the perceptual and motor constraints of the human body. Recent research indicates student understanding of science needs embodied experiences. Recent emphases of science education researchers in the practices of science suggest that students' understanding of systems and their structure, scale, size, representations, and causality are crosscutting concepts that unify all scientific disciplinary areas. To discern the relationship between linguistic patterns and embodied experiences, I relied on Cognitive Linguistics, a field within cognitive sciences that pays attention to language organization and use assuming that language reflects the human cognitive system. Particularly, I investigated the embodied experiences that 268 middle school students learning about water brought to understanding: i) systems and system structure; ii) scale, size and representations; and iii) causality. Using content analysis, I explored students' language in search of patterns regarding linguistic phenomena described within cognitive linguistics: image schemas, conceptual metaphors, event schemas, semantical roles, and force-dynamics. I found several common embodied experiences organizing students' understanding of crosscutting concepts. Perception of boundaries and change in location and perception of spatial organization in the vertical axis are relevant embodied experiences for students' understanding of systems and system structure. Direct object manipulation and perception of size with and without locomotion are relevant for understanding scale, size and representations. Direct applications of force and consequential perception of movement or change in form are relevant for understanding of causality. I discuss implications of these findings for research and science teaching.

Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science.

PubMed

Mocanu, Decebal Constantin; Mocanu, Elena; Stone, Peter; Nguyen, Phuong H; Gibescu, Madeleine; Liotta, Antonio

2018-06-19

Through the success of deep learning in various domains, artificial neural networks are currently among the most used artificial intelligence methods. Taking inspiration from the network properties of biological neural networks (e.g. sparsity, scale-freeness), we argue that (contrary to general practice) artificial neural networks, too, should not have fully-connected layers. Here we propose sparse evolutionary training of artificial neural networks, an algorithm which evolves an initial sparse topology (Erdős-Rényi random graph) of two consecutive layers of neurons into a scale-free topology, during learning. Our method replaces artificial neural networks fully-connected layers with sparse ones before training, reducing quadratically the number of parameters, with no decrease in accuracy. We demonstrate our claims on restricted Boltzmann machines, multi-layer perceptrons, and convolutional neural networks for unsupervised and supervised learning on 15 datasets. Our approach has the potential to enable artificial neural networks to scale up beyond what is currently possible.

Cognitive science and the cultural nature of music.

PubMed

Cross, Ian

2012-10-01

The vast majority of experimental studies of music to date have explored music in terms of the processes involved in the perception and cognition of complex sonic patterns that can elicit emotion. This paper argues that this conception of music is at odds both with recent Western musical scholarship and with ethnomusicological models, and that it presents a partial and culture-specific representation of what may be a generic human capacity. It argues that the cognitive sciences must actively engage with the problems of exploring music as manifested and conceived in the broad spectrum of world cultures, not only to elucidate the diversity of music in mind but also to identify potential commonalities that could illuminate the relationships between music and other domains of thought and behavior. Copyright © 2012 Cognitive Science Society, Inc.

A Framework for Re-thinking Learning in Science from Recent Cognitive Science Perspectives

NASA Astrophysics Data System (ADS)

Tytler, Russell; Prain, Vaughan

2010-10-01

Recent accounts by cognitive scientists of factors affecting cognition imply the need to reconsider current dominant conceptual theories about science learning. These new accounts emphasize the role of context, embodied practices, and narrative-based representation rather than learners' cognitive constructs. In this paper we analyse data from a longitudinal study of primary school children's learning to outline a framework based on these contemporary accounts and to delineate key points of difference from conceptual change perspectives. The findings suggest this framework provides strong theoretical and practical insights into how children learn and the key role of representational negotiation in this learning. We argue that the nature and process of conceptual change can be re-interpreted in terms of the development of students' representational resources.

Banknote recognition: investigating processing and cognition framework using competitive neural network.

PubMed

Oyedotun, Oyebade K; Khashman, Adnan

2017-02-01

Humans are apt at recognizing patterns and discovering even abstract features which are sometimes embedded therein. Our ability to use the banknotes in circulation for business transactions lies in the effortlessness with which we can recognize the different banknote denominations after seeing them over a period of time. More significant is that we can usually recognize these banknote denominations irrespective of what parts of the banknotes are exposed to us visually. Furthermore, our recognition ability is largely unaffected even when these banknotes are partially occluded. In a similar analogy, the robustness of intelligent systems to perform the task of banknote recognition should not collapse under some minimum level of partial occlusion. Artificial neural networks are intelligent systems which from inception have taken many important cues related to structure and learning rules from the human nervous/cognition processing system. Likewise, it has been shown that advances in artificial neural network simulations can help us understand the human nervous/cognition system even furthermore. In this paper, we investigate three cognition hypothetical frameworks to vision-based recognition of banknote denominations using competitive neural networks. In order to make the task more challenging and stress-test the investigated hypotheses, we also consider the recognition of occluded banknotes. The implemented hypothetical systems are tasked to perform fast recognition of banknotes with up to 75 % occlusion. The investigated hypothetical systems are trained on Nigeria's Naira banknotes and several experiments are performed to demonstrate the findings presented within this work.

Are there reasons to challenge a symbolic computationalist approach in explaining deductive reasoning?

PubMed

Faiciuc, Lucia E

2008-06-01

The majority of the existing theories explaining deductive reasoning could be included in a classic computationalist approach of the cognitive processes. In fact, deductive reasoning could be seen to be the pinnacle of the symbolic computationalism, its last fortress to be defended in the face of new, dynamic, and ecological perspectives over cognition. But are there weak points in that position regarding deductive reasoning? What would be the reasons for which new perspectives could gain in credibility? What could be their most important tenets? The answers given to those questions in the paper include two main points. The first one is that the present empirical data could not sustain unambiguously one view over the other, that they are obtained in artificial experimental conditions, and that there are data that are not easily explainable using the traditional computationalist paradigm. The second one is that approaching the deductive reasoning from dynamic and ecological perspectives could have significant advantages. The most obvious one is the possibility to integrate more easily the research regarding the deductive reasoning with the results obtained in other domains of the psychology (especially in what respects the lower cognitive processes), in artificial intelligence or in neurophysiology. The reasons for that would be that such perspectives, as they are sketched in the paper, would imply, essentially, processes of second-order pattern formation and recognition (as it is the case for perception), embodied cognition, and dynamic processes as the brain ones are.

Adaptive power allocation schemes based on IAFS algorithm for OFDM-based cognitive radio systems

NASA Astrophysics Data System (ADS)

Zhang, Shuying; Zhao, Xiaohui; Liang, Cong; Ding, Xu

2017-01-01

In cognitive radio (CR) systems, reasonable power allocation can increase transmission rate of CR users or secondary users (SUs) as much as possible and at the same time insure normal communication among primary users (PUs). This study proposes an optimal power allocation scheme for the OFDM-based CR system with one SU influenced by multiple PU interference constraints. This scheme is based on an improved artificial fish swarm (IAFS) algorithm in combination with the advantage of conventional artificial fish swarm (ASF) algorithm and particle swarm optimisation (PSO) algorithm. In performance comparison of IAFS algorithm with other intelligent algorithms by simulations, the superiority of the IAFS algorithm is illustrated; this superiority results in better performance of our proposed scheme than that of the power allocation algorithms proposed by the previous studies in the same scenario. Furthermore, our proposed scheme can obtain higher transmission data rate under the multiple PU interference constraints and the total power constraint of SU than that of the other mentioned works.

Infrastructural intelligence: Contemporary entanglements between neuroscience and AI.

PubMed

Bruder, Johannes

2017-01-01

In this chapter, I reflect on contemporary entanglements between artificial intelligence and the neurosciences by tracing the development of Google's recent DeepMind algorithms back to their roots in neuroscientific studies of episodic memory and imagination. Google promotes a new form of "infrastructural intelligence," which excels by constantly reassessing its cognitive architecture in exchange with a cloud of data that surrounds it, and exhibits putatively human capacities such as intuition. I argue that such (re)alignments of biological and artificial intelligence have been enabled by a paradigmatic infrastructuralization of the brain in contemporary neuroscience. This infrastructuralization is based in methodologies that epistemically liken the brain to complex systems of an entirely different scale (i.e., global logistics) and has given rise to diverse research efforts that target the neuronal infrastructures of higher cognitive functions such as empathy and creativity. What is at stake in this process is no less than the shape of brains to come and a revised understanding of the intelligent and creative social subject. © 2017 Elsevier B.V. All rights reserved.

Artificial neural networks identify the predictive values of risk factors on the conversion of amnestic mild cognitive impairment.

PubMed

Tabaton, Massimo; Odetti, Patrizio; Cammarata, Sergio; Borghi, Roberta; Monacelli, Fiammetta; Caltagirone, Carlo; Bossù, Paola; Buscema, Massimo; Grossi, Enzo

2010-01-01

The search for markers that are able to predict the conversion of amnestic mild cognitive impairment (aMCI) to Alzheimer's disease (AD) is crucial for early mechanistic therapies. Using artificial neural networks (ANNs), 22 variables that are known risk factors of AD were analyzed in 80 patients with aMCI, for a period spanning at least 2 years. The cases were chosen from 195 aMCI subjects recruited by four Italian Alzheimer's disease units. The parameters of glucose metabolism disorder, female gender, and apolipoprotein E epsilon3/epsilon4 genotype were found to be the biological variables with high relevance for predicting the conversion of aMCI. The scores of attention and short term memory tests also were predictors. Surprisingly, the plasma concentration of amyloid-beta (42) had a low predictive value. The results support the utility of ANN analysis as a new tool in the interpretation of data from heterogeneous and distinct sources.

Linguistics, Cognitive Science and Liberal Education. Linguistics in the Undergraduate Curriculum, Appendix 4-H.

ERIC Educational Resources Information Center

Heny, Frank

The goals of liberal education are to deepen the understanding of the nature of humankind and of the human condition. In the last half century, fundamental changes have occurred in perceptions of how the human species relates to the rest of the universe, due to developments in science and the creation of the cognitive sciences. There is now the…

Examination of Gender Differences on Cognitive and Motivational Factors That Influence 8th Graders' Science Achievement in Turkey

ERIC Educational Resources Information Center

Acar, Ömer; Türkmen, Lütfullah; Bilgin, Ahmet

2015-01-01

We examined the influence of several students' cognitive and motivational factors on 8th graders' science achievement and also gender differences on factors that significantly contribute to the science achievement model. A total of 99 girls and 83 boys responded all the instruments used in this study. Results showed that girls outperformed boys on…

The Effects of Cognitive Styles on Naïve Impetus Theory Application Degrees of Pre-Service Science Teachers

ERIC Educational Resources Information Center

Cataloglu, Erdat; Ates, Salih

2014-01-01

The purpose of this study was to determine whether there is a relationship between pre-service science teachers' Field Dependent or Field Independent (FD/FI) cognitive styles and the application of degrees of naive impetus theory. The sample consisted of 122 pre-service science teachers (97 females and 25 males) who were enrolled in the…

A Study on the Effectiveness of a Pilot Inquiry-Based Middle School Science Program on Non-Cognitive Outcomes and Academic Achievement

ERIC Educational Resources Information Center

Dionisio, Rui Meira

2017-01-01

The randomized research study assessed the effect of an inquiry-based science (IBS) program on non-cognitive outcomes and academic achievement. The study was the result of a grant that was awarded by Professional Resources in Science and Mathematics (PRISM), a program affiliated with Montclair State University in conjunction with Bristol-Myers…

Relationships among Prior Conceptual Knowledge, Metacognitive Awareness, Metacognitive Self-Management, Cognitive Style, Perception-Judgment Style, Attitude toward School Science, Self-Regulation, and Science Achievement in Grades 6-7 Students.

ERIC Educational Resources Information Center

Holden, Trudy G.; Yore, Larry D.

This study explores the learner dimension in learning biological science topics in five elementary school classrooms instructed by different teachers using a common course of study and outcome measures. Specifically, the study addressed the associations among conceptual, metacognitive, cognitive, stylistic, and affective characteristics and…

The Cultures of Contemporary Instructional Design Scholarship, Part One: Developments Based on Behavioral and Cognitive Science Foundations

ERIC Educational Resources Information Center

Willis, Jerry

2011-01-01

This is the first in a series of two articles examining the current status of instructional design (ID) scholarship and theory in four different cultures or traditions. In this article, the focus is on, first, ID models based on traditional behavioral theories of learning and, second, on models based on cognitive science and the learning sciences.…

Operationalizing Cognitive Science and Technologies’ Research and Development; the “Brain and Cognition Study Group (BCSG)” Initiative from Shiraz, Iran

PubMed Central

Ashjazadeh, Nahid; Boostani, Reza; Ekhtiari, Hamed; Emamghoreishi, Masoumeh; Farrokhi, Majidreza; Ghanizadeh, Ahmad; Hatam, Gholamreza; Hadianfard, Habib; Lotfi, Mehrzad; Mortazavi, Seyed Mohammad Javad; Mousavi, Maryam; Montakhab, Afshin; Nili, Majid; Razmkon, Ali; Salehi, Sina; Sodagar, Amir Mohammad; Setoodeh, Peiman; Taghipour, Mousa; Torabi-Nami, Mohammad; Vesal, Abdolkarim

2014-01-01

Recent advances in brain and cognitive science studies have revolutionized concepts in neural dynamics, regulating mechanisms, coding systems and information processing networks which govern our function and behavior. Hidden aspects of neurological and psychiatric diseases are being understood and hopes for their treatment are emerging. Although the two comprehensive mega-projects on brain mapping are in place in the United States and Europe; the proportion of science contributed by the developing countries should not be downsized. With the granted supports from the Cognitive Sciences and Technologies Council (CSTC), Iran can take its role in research on brain and cognition further. The idea of research and development in Cognitive Sciences and Technologies (CST) is being disseminated across the country by CSTC. Towards this goal, the first Shiraz interdisciplinary meeting on CST was held on 9 January 2014 in Namazi hospital, Shiraz. CST research priorities, infrastructure development, education and promotion were among the main topics discussed during this interactive meeting. The steering committee of the first CST meeting in Shiraz decided to frame future research works within the “Brain and Cognition Study Group-Shiraz” (BCSG-Shiraz). The study group comprises scientific leaders from various allied disciplines including neuroscience, neurosurgery, neurology, psychiatry, psychology, radiology, physiology, bioengineering, biophysics, applied physics and telecommunication. As the headquarter for CST in the southern Iran, BCSG-Shiraz is determined to advocate “brain and cognition” awareness, education and research in close collaboration with CSTC. Together with CSTC, Shiraz Neuroscience Research center (SNRC) will take the initiative to cross boundaries in interdisciplinary works and multi-centric research projects within the study group. PMID:25337368

Artificial consciousness and the consciousness-attention dissociation.

PubMed

Haladjian, Harry Haroutioun; Montemayor, Carlos

2016-10-01

Artificial Intelligence is at a turning point, with a substantial increase in projects aiming to implement sophisticated forms of human intelligence in machines. This research attempts to model specific forms of intelligence through brute-force search heuristics and also reproduce features of human perception and cognition, including emotions. Such goals have implications for artificial consciousness, with some arguing that it will be achievable once we overcome short-term engineering challenges. We believe, however, that phenomenal consciousness cannot be implemented in machines. This becomes clear when considering emotions and examining the dissociation between consciousness and attention in humans. While we may be able to program ethical behavior based on rules and machine learning, we will never be able to reproduce emotions or empathy by programming such control systems-these will be merely simulations. Arguments in favor of this claim include considerations about evolution, the neuropsychological aspects of emotions, and the dissociation between attention and consciousness found in humans. Ultimately, we are far from achieving artificial consciousness. Copyright © 2016 Elsevier Inc. All rights reserved.

Cognitive neuroimaging: cognitive science out of the armchair.

PubMed

de Zubicaray, Greig I

2006-04-01

Cognitive scientists were not quick to embrace the functional neuroimaging technologies that emerged during the late 20th century. In this new century, cognitive scientists continue to question, not unreasonably, the relevance of functional neuroimaging investigations that fail to address questions of interest to cognitive science. However, some ultra-cognitive scientists assert that these experiments can never be of relevance to the study of cognition. Their reasoning reflects an adherence to a functionalist philosophy that arbitrarily and purposefully distinguishes mental information-processing systems from brain or brain-like operations. This article addresses whether data from properly conducted functional neuroimaging studies can inform and subsequently constrain the assumptions of theoretical cognitive models. The article commences with a focus upon the functionalist philosophy espoused by the ultra-cognitive scientists, contrasting it with the materialist philosophy that motivates both cognitive neuroimaging investigations and connectionist modelling of cognitive systems. Connectionism and cognitive neuroimaging share many features, including an emphasis on unified cognitive and neural models of systems that combine localist and distributed representations. The utility of designing cognitive neuroimaging studies to test (primarily) connectionist models of cognitive phenomena is illustrated using data from functional magnetic resonance imaging (fMRI) investigations of language production and episodic memory.

Electron-Electron Interactions in Artificial Graphene

NASA Astrophysics Data System (ADS)

Räsänen, E.; Rozzi, C. A.; Pittalis, S.; Vignale, G.

2012-06-01

Recent advances in the creation and modulation of graphenelike systems are introducing a science of “designer Dirac materials”. In its original definition, artificial graphene is a man-made nanostructure that consists of identical potential wells (quantum dots) arranged in an adjustable honeycomb lattice in the two-dimensional electron gas. As our ability to control the quality of artificial graphene samples improves, so grows the need for an accurate theory of its electronic properties, including the effects of electron-electron interactions. Here we determine those effects on the band structure and on the emergence of Dirac points.

Leveraging Cognitive Science Underpinnings to Enhance NGSS Astronomy Concepts

NASA Astrophysics Data System (ADS)

Slater, Stephanie; Slater, Timothy F.

2014-06-01

National-scale science education reform efforts have been hampered by highly fragmented frameworks and standards that vary considerably from one state to the next. In an effort to improve the quality of science education across the nation’s K-12 schools, the 2013 Next Generation Science Standards (NGSS) have been designed to guide states in specifying the learning targets and performance expectations of all K-12 students. The NGSS is designed to reflect the 2011 Framework for K-12 Science Education developed by the National Research Council of the National Academy of Sciences. As teachers, curriculum developers, and assessment experts begin to implement the NGSS in specific geographical and socio-economic contexts, moving beyond an examination of common student misconceptions and reasoning difficulties to delineate the specific cognitive sources of those difficulties, and the specific interventions that can serve as countermeasures, should be a fruitful next step. While astronomy education researchers have already documented challenges in teaching system processes that operate with the space system, solar system, and interconnected Earth science systems, we are far from a thorough understanding of student thinking in astronomy. Many of these ideas can be better taught-and tested-by carefully examining the underlying cognitive science including learners’ difficulties with spatial thinking and the prescribed astronomy and space science concepts. The NGSS may prove to be useful as a framework for next steps in the cognitive science within astronomy, and this work may benefit from deliberate collaborations between education researchers, curriculum developers, and those who engage in teacher professional development.

What the cognitive neurosciences mean to me.

PubMed

Pereira, Alfredo

2007-01-01

Cognitive Neuroscience is an interdisciplinary area of research that combines measurement of brain activity (mostly by means of neuroimaging) with a simultaneous performance of cognitive tasks by human subjects. These investigations have been successful in the task of connecting the sciences of the brain (Neurosciences) and the sciences of the mind (Cognitive Sciences). Advances on this kind of research provide a map of localization of cognitive functions in the human brain. Do these results help us to understand how mind relates to the brain? In my view, the results obtained by the Cognitive Neurosciences lead to new investigations in the domain of Molecular Neurobiology, aimed at discovering biophysical mechanisms that generate the activity measured by neuroimaging instruments. In this context, I argue that the understanding of how ionic/molecular processes support cognition and consciousness cannot be made by means of the standard reductionist explanations. Knowledge of ionic/molecular mechanisms can contribute to our understanding of the human mind as long as we assume an alternative form of explanation, based on psycho-physical similarities, together with an ontological view of mentality and spirituality as embedded in physical nature (and not outside nature, as frequently assumed in western culture).

What The Cognitive Neurosciences Mean To Me

PubMed Central

Pereira, Alfredo

2007-01-01

Cognitive Neuroscience is an interdisciplinary area of research that combines measurement of brain activity (mostly by means of neuroimaging) with a simultaneous performance of cognitive tasks by human subjects. These investigations have been successful in the task of connecting the sciences of the brain (Neurosciences) and the sciences of the mind (Cognitive Sciences). Advances on this kind of research provide a map of localization of cognitive functions in the human brain. Do these results help us to understand how mind relates to the brain? In my view, the results obtained by the Cognitive Neurosciences lead to new investigations in the domain of Molecular Neurobiology, aimed at discovering biophysical mechanisms that generate the activity measured by neuroimaging instruments. In this context, I argue that the understanding of how ionic/molecular processes support cognition and consciousness cannot be made by means of the standard reductionist explanations. Knowledge of ionic/molecular mechanisms can contribute to our understanding of the human mind as long as we assume an alternative form of explanation, based on psycho-physical similarities, together with an ontological view of mentality and spirituality as embedded in physical nature (and not outside nature, as frequently assumed in western culture). PMID:22058629

Information processing, computation, and cognition

PubMed Central

Scarantino, Andrea

2010-01-01

Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both – although others disagree vehemently. Yet different cognitive scientists use ‘computation’ and ‘information processing’ to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In this paper, we address this unsatisfactory state of affairs by presenting a general and theory-neutral account of computation and information processing. We also apply our framework by analyzing the relations between computation and information processing on one hand and classicism, connectionism, and computational neuroscience on the other. We defend the relevance to cognitive science of both computation, at least in a generic sense, and information processing, in three important senses of the term. Our account advances several foundational debates in cognitive science by untangling some of their conceptual knots in a theory-neutral way. By leveling the playing field, we pave the way for the future resolution of the debates’ empirical aspects. PMID:22210958

Sex Differences in Cognitive Abilities. Third Edition.

ERIC Educational Resources Information Center

Halpern, Diane F.

This book examines the science and politics of cognitive sex differences, reflecting theories and research in the area over the past several years. Eight chapters discuss: (1) "Introduction and Overview" (e.g., theoretical approaches, values and science, and terminology); (2) "Searching for Sex Differences in Cognitive…

NCT and Culture-Conscious Developmental Science

ERIC Educational Resources Information Center

Downing-Wilson, Deborah; Pelaprat, Etienne; Rosero, Ivan; Vadeboncoeur, Jennifer; Packer, Martin; Cole, Michael

2013-01-01

The authors share the belief that there is great potential for developmental science in bringing the ideas of Niche Construction Theory (NCT), as developed in evolutionary biology, into conversation with Vygotskian-inspired theories such as cultural-historical and activity theories, distributed cognition, and embodied cognition, although from…

Relationships between Actualizing Concrete and Formal Science Teaching Intentions and the Levels of Cognitive Development among Some Prospective Teachers in Nigeria.

ERIC Educational Resources Information Center

Ehindero, Olusola J.

1980-01-01

Determines relationships between prospective secondary school science teachers' (N=60) level of cognitive development (i.e., Piaget's concrete operational or formal operational stage) and success in stating and actualizing teaching intentions. (CS)

Bringing CASE in from the Cold: the Teaching and Learning of Thinking

NASA Astrophysics Data System (ADS)

Oliver, Mary; Venville, Grady

2017-02-01

Thinking Science is a 2-year program of professional development for teachers and thinking lessons for students in junior high school science classes. This paper presents research on the effects of Thinking Science on students' levels of cognition in Australia. The research is timely, with a general capability focused on critical thinking in the newly implemented F-10 curriculum in Australia. The design of the research was a quasi-experiment with pre- and post-intervention cognitive tests conducted with participating students ( n = 655) from nine cohorts in seven high schools. Findings showed significant cognitive gains compared with an age-matched control group over the length of the program. Noteworthy is a correlation between baseline cognitive score and school Index of Community Socio-Educational Advantage (ICSEA). We argue that the teaching of thinking be brought into the mainstream arena of educational discourse and that the principles from evidence-based programs such as Thinking Science be universally adopted.

Prospects for direct social perception: a multi-theoretical integration to further the science of social cognition.

PubMed

Wiltshire, Travis J; Lobato, Emilio J C; McConnell, Daniel S; Fiore, Stephen M

2014-01-01

In this paper we suggest that differing approaches to the science of social cognition mirror the arguments between radical embodied and traditional approaches to cognition. We contrast the use in social cognition of theoretical inference and mental simulation mechanisms with approaches emphasizing a direct perception of others' mental states. We build from a recent integrative framework unifying these divergent perspectives through the use of dual-process theory and supporting social neuroscience research. Our elaboration considers two complementary notions of direct perception: one primarily stemming from ecological psychology and the other from enactive cognition theory. We use this as the foundation from which to offer an account of the informational basis for social information and assert a set of research propositions to further the science of social cognition. In doing so, we point out how perception of the minds of others can be supported in some cases by lawful information, supporting direct perception of social affordances and perhaps, mental states, and in other cases by cues that support indirect perceptual inference. Our goal is to extend accounts of social cognition by integrating advances across disciplines to provide a multi-level and multi-theoretic description that can advance this field and offer a means through which to reconcile radical embodied and traditional approaches to cognitive neuroscience.

Active vision in satellite scene analysis

NASA Technical Reports Server (NTRS)

Naillon, Martine

1994-01-01

In earth observation or planetary exploration it is necessary to have more and, more autonomous systems, able to adapt to unpredictable situations. This imposes the use, in artificial systems, of new concepts in cognition, based on the fact that perception should not be separated from recognition and decision making levels. This means that low level signal processing (perception level) should interact with symbolic and high level processing (decision level). This paper is going to describe the new concept of active vision, implemented in Distributed Artificial Intelligence by Dassault Aviation following a 'structuralist' principle. An application to spatial image interpretation is given, oriented toward flexible robotics.

Artificial humanoid for the elderly people.

PubMed

Simou, Panagiota; Alexiou, Athanasios; Tiligadis, Konstantinos

2015-01-01

While frailty and other multi-scale factors have to be correlated during a geriatric assessment, few prototype robots have already been developed in order to measure and provide real-time information, concerning elderly daily activities. Cognitive impairment and alterations on daily functions should be immediate recognized from caregivers, in order to be prevented and probably treated. In this chapter we recognize the necessity of artificial robots during the personal service of the elderly population, not only as a mobile laboratory-geriatrician, but mainly as a socialized digital humanoid able to develop social behavior and activate memories and emotions.

Children's Behaviour and Cognitions across Different Balance Tasks

ERIC Educational Resources Information Center

Messer, David J.; Pine, Karen J.; Butler, Cathal

2008-01-01

Children's understanding of the way objects balance has provided important insights about cognitive development [e.g., Karmiloff-Smith, A. (1992). "Beyond modularity: A developmental perspective on cognitive science." Cambridge, MA: MIT Press; Siegler, R. S. (1976). Three aspects of cognitive development. "Cognitive Psychology," 8, 481-520]. We…

Anticipation by multi-modal association through an artificial mental imagery process

NASA Astrophysics Data System (ADS)

Gaona, Wilmer; Escobar, Esaú; Hermosillo, Jorge; Lara, Bruno

2015-01-01

Mental imagery has become a central issue in research laboratories seeking to emulate basic cognitive abilities in artificial agents. In this work, we propose a computational model to produce an anticipatory behaviour by means of a multi-modal off-line hebbian association. Unlike the current state of the art, we propose to apply hebbian learning during an internal sensorimotor simulation, emulating a process of mental imagery. We associate visual and tactile stimuli re-enacted by a long-term predictive simulation chain motivated by covert actions. As a result, we obtain a neural network which provides a robot with a mechanism to produce a visually conditioned obstacle avoidance behaviour. We developed our system in a physical Pioneer 3-DX robot and realised two experiments. In the first experiment we test our model on one individual navigating in two different mazes. In the second experiment we assess the robustness of the model by testing in a single environment five individuals trained under different conditions. We believe that our work offers an underpinning mechanism in cognitive robotics for the study of motor control strategies based on internal simulations. These strategies can be seen analogous to the mental imagery process known in humans, opening thus interesting pathways to the construction of upper-level grounded cognitive abilities.

The Cognitive Advantages of Counting Specifically: A Representational Analysis of Verbal Numeration Systems in Oceanic Languages.

PubMed

Bender, Andrea; Schlimm, Dirk; Beller, Sieghard

2015-10-01

The domain of numbers provides a paradigmatic case for investigating interactions of culture, language, and cognition: Numerical competencies are considered a core domain of knowledge, and yet the development of specifically human abilities presupposes cultural and linguistic input by way of counting sequences. These sequences constitute systems with distinct structural properties, the cross-linguistic variability of which has implications for number representation and processing. Such representational effects are scrutinized for two types of verbal numeration systems-general and object-specific ones-that were in parallel use in several Oceanic languages (English with its general system is included for comparison). The analysis indicates that the object-specific systems outperform the general systems with respect to counting and mental arithmetic, largely due to their regular and more compact representation. What these findings reveal on cognitive diversity, how the conjectures involved speak to more general issues in cognitive science, and how the approach taken here might help to bridge the gap between anthropology and other cognitive sciences is discussed in the conclusion. Copyright © 2015 Cognitive Science Society, Inc.

Game-XP: Action Games as Experimental Paradigms for Cognitive Science.

PubMed

Gray, Wayne D

2017-04-01

Why games? How could anyone consider action games an experimental paradigm for Cognitive Science? In 1973, as one of three strategies he proposed for advancing Cognitive Science, Allen Newell exhorted us to "accept a single complex task and do all of it." More specifically, he told us that rather than taking an "experimental psychology as usual approach," we should "focus on a series of experimental and theoretical studies around a single complex task" so as to demonstrate that our theories of human cognition were powerful enough to explain "a genuine slab of human behavior" with the studies fitting into a detailed theoretical picture. Action games represent the type of experimental paradigm that Newell was advocating and the current state of programming expertise and laboratory equipment, along with the emergence of Big Data and naturally occurring datasets, provide the technologies and data needed to realize his vision. Action games enable us to escape from our field's regrettable focus on novice performance to develop theories that account for the full range of expertise through a twin focus on expertise sampling (across individuals) and longitudinal studies (within individuals) of simple and complex tasks. Copyright © 2017 Cognitive Science Society, Inc.

Computational modeling in cognitive science: a manifesto for change.

PubMed

Addyman, Caspar; French, Robert M

2012-07-01

Computational modeling has long been one of the traditional pillars of cognitive science. Unfortunately, the computer models of cognition being developed today have not kept up with the enormous changes that have taken place in computer technology and, especially, in human-computer interfaces.  For all intents and purposes, modeling is still done today as it was 25, or even 35, years ago. Everyone still programs in his or her own favorite programming language, source code is rarely made available, accessibility of models to non-programming researchers is essentially non-existent, and even for other modelers, the profusion of source code in a multitude of programming languages, written without programming guidelines, makes it almost impossible to access, check, explore, re-use, or continue to develop. It is high time to change this situation, especially since the tools are now readily available to do so. We propose that the modeling community adopt three simple guidelines that would ensure that computational models would be accessible to the broad range of researchers in cognitive science. We further emphasize the pivotal role that journal editors must play in making computational models accessible to readers of their journals. Copyright © 2012 Cognitive Science Society, Inc.

Six Suggestions for Research on Games in Cognitive Science.

PubMed

Chabris, Christopher F

2017-04-01

Games are more varied and occupy more of daily life than ever before. At the same time, the tools available to study game play and players are more powerful than ever, especially massive data sets from online platforms and computational engines that can accurately evaluate human decisions. This essay offers six suggestions for future cognitive science research on games: (1) Don't forget about chess, (2) Look beyond action games and chess, (3) Use (near)-optimal play to understand human play and players, (4) Investigate social phenomena, (5) Raise the standards for studies of games as treatments, (6) Talk to real experts. Copyright © 2017 Cognitive Science Society, Inc.

Different understanding: science through the eyes of visual thinkers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sesko, S.C.; Marchant, M.

1997-09-11

The objective of this emergent study was to follow the cognitive and creative processes demonstrated by five art student participants as they integrated a developing knowledge of big science, as practiced at the Department of Energy`s Lawrence Livermore National Laboratory, into a personal and idiosyncratic visual, graphical, or multimedia product. The non-scientist participants involved in this process attended design classes sponsored by the Laboratory at the Art Center College of Design in California. The learning experience itself, and how the students arrived at their product, were the focus of the class and the research. The study was emergent in thatmore » we found no applicable literature on the use of art to portray a cognitive understanding of science. This lack of literature led us to the foundation literature on creativity and to the corpus of literature on public understanding of science. We believe that this study contributes to the literature on science education, art education, cognitive change, and public understanding of science. 20 refs., 11 figs.« less

Utilizing the ISS Mission as a Testbed to Develop Cognitive Communications Systems

NASA Technical Reports Server (NTRS)

Jackson, Dan

2016-01-01

The ISS provides an excellent opportunity for pioneering artificial intelligence software to meet the challenges of real-time communications (comm) link management. This opportunity empowers the ISS Program to forge a testbed for developing cognitive communications systems for the benefit of the ISS mission, manned Low Earth Orbit (LEO) science programs and future planetary exploration programs. In November, 1998, the Flight Operations Directorate (FOD) started the ISS Antenna Manager (IAM) project to develop a single processor supporting multiple comm satellite tracking for two different antenna systems. Further, the processor was developed to be highly adaptable as it supported the ISS mission through all assembly stages. The ISS mission mandated communications specialists with complete knowledge of when the ISS was about to lose or gain comm link service. The current specialty mandated cognizance of large sun-tracking solar arrays and thermal management panels in addition to the highly-dynamic satellite service schedules and rise/set tables. This mission requirement makes the ISS the ideal communications management analogue for future LEO space station and long-duration planetary exploration missions. Future missions, with their precision-pointed, dynamic, laser-based comm links, require complete autonomy for managing high-data rate communications systems. Development of cognitive communications management systems that permit any crew member or payload science specialist, regardless of experience level, to control communications is one of the greater benefits the ISS can offer new space exploration programs. The IAM project met a new mission requirement never previously levied against US space-born communications systems management: process and display the orientation of large solar arrays and thermal control panels based on real-time joint angle telemetry. However, IAM leaves the actual communications availability assessment to human judgement, which introduces unwanted variability because each specialist has a different core of experience with comm link performance. Because the ISS utilizes two different frequency bands, dynamic structure can be occasionally translucent at one frequency while it can completely interdict service at the other frequency. The impact of articulating structure on the comm link can depend on its orientation at the time it impinges on the link. It can become easy for a human specialist to cross-associate experience at one frequency with experience at the other frequency. Additionally, the specialist's experience is incremental, occurring one nine-hour shift at a time. Only the IAM processor experiences the complete 24x7x365 communications link performance for both communications links but, it has no "learning capability." If the IAM processor could be endowed with a cognitive ability to remember past structure-induced comm link outages, based on its knowledge of the ISS position, attitude, communications gear, array joint angles and tracking accuracy, it could convey such experience to the human operator. It could also use its learned communications link behaviors to accurately convey the availability of future communications sessions. Further, the tool could remember how accurately or inaccurately it predicted availability and correct future predictions based on past performance. The IAM tool could learn frequency-specific impacts due to spacecraft structures and pass that information along as "experience." Such development would provide a single artificial intelligence processor that could provide two different experience bases. If it also "knew" the satellite service schedule, it could distinguish structure blockage from schedule or planet blockage and then quickly switch to another satellite. Alternatively, just as a human operator could judge, a cognizant comm system based on the IAM model could "know" that the blockage is not going to last very long and continue tracking a comm satellite, waiting for it to track away from structure. Ultimately, once this capability was fully developed and tested in the Mission Control Center, it could be transferred on-orbit to support development of operations concepts that include more advanced cognitive communications systems. Future applications of this capability are easily foreseen because even more dynamic satellite constellations with more nodes and greater capability are coming. Currently, the ISS fully employs its high-data-rate return link for harvesting payload science. In the coming months, it will double that data rate and is forecast to fully utilize that capability. Already there is talk of an upgrade that quadruples the current data rate allocated to ISS payload science before the end of its mission and laser comm links have already been tested from the ISS. Every data rate upgrade mandates more complicated and sensitive communications equipment which implies greater expertise invested in the human operator. Future on-orbit cognizant comm systems will be needed to meet greater performance demands aboard larger, far more complicated spacecraft. In the LEO environment, the old-style one-satellite-per-spacecraft operations concept will give way to a new concept of a single customer spacecraft simultaneously using multiple comm satellites. Much more highly-dynamic manned LEO missions with decades of crew members potentially increase the demand for communications link performance. A cognizant on-board communications system will meet advanced communications demands from future LEO missions and future planetary missions. The ISS has fledgling components of future exploration programs, both LEO and planetary. Further, the Flight Operations Directorate, through the IAM project, has already begun to develop a communications management system that attempts to solve advanced problems ideally represented by dynamic structure impacting scheduled satellite service. With an earnest project to integrate artificial intelligence into the IAM processor, the ISS Program could develop a cognizant communications system that could be adapted and transferred to future on-orbit avionics designs.

A Neuroscientific Perspective on Second Language Learning and Academic Achievement.

ERIC Educational Resources Information Center

Hawson, Anne

It is proposed that research on neurological organization, cognitive psychology, and artificial intelligence can contribute to understanding the relationship between second language learning processes and academic achievement. Relevant research in these areas and in the field of neurolinguistics is reviewed, with several themes or topics…

Discovery Systems.

DTIC Science & Technology

1986-04-01

independent regularities - called "concept germs" by Minsky [Min86] and mA 9 "cognitive cliches" by Chapman [ChaB3] - to which are attached batteries of...Dougls B. Lenat. Theory Formation by Heuristic Search. Artificial Intelligence, 21, 1983. [Mns6 Marvin insky. The Society of Mind. Simon and Schuster

Artificial Intelligence: An Analysis of the Technology for Training. Training and Development Research Center Project Number Fourteen.

ERIC Educational Resources Information Center

Sayre, Scott Alan

The ultimate goal of the science of artificial intelligence (AI) is to establish programs that will use algorithmic computer techniques to imitate the heuristic thought processes of humans. Most AI programs, especially expert systems, organize their knowledge into three specific areas: data storage, a rule set, and a control structure. Limitations…

Temporal Reasoning and Default Logics.

DTIC Science & Technology

1985-10-01

Aritificial Intelligence ", Computer Science Research Report, Yale University, forthcoming (1985). . 74 .-, A Axioms for Describing Persistences and Clipping...34Circumscription - A Form of Non-Monotonic Reasoning", Artificial Intelligence , vol. 13 (1980), pp. 27-39. [13] McCarthy, John, "Applications of...and P. J. Hayes, "Some philosophical problems from the standpoint of artificial intelligence ", in: B. Meltzer and D. Michie (eds.), Machine

Issues or Identity? Cognitive Foundations of Voter Choice.

PubMed

Jenke, Libby; Huettel, Scott A

2016-11-01

Voter choice is one of the most important problems in political science. The most common models assume that voting is a rational choice based on policy positions (e.g., key issues) and nonpolicy information (e.g., social identity, personality). Though such models explain macroscopic features of elections, they also reveal important anomalies that have been resistant to explanation. We argue for a new approach that builds upon recent research in cognitive science and neuroscience; specifically, we contend that policy positions and social identities do not combine in merely an additive manner, but compete to determine voter preferences. This model not only explains several key anomalies in voter choice, but also suggests new directions for research in both political science and cognitive science. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cognitive and Neural Sciences Division, 1991 Programs.

ERIC Educational Resources Information Center

Vaughan, Willard S., Ed.

This report documents research and development performed under the sponsorship of the Cognitive and Neural Sciences Division of the Office of Naval Research in fiscal year 1991. It provides abstracts (title, principal investigator, project code, objective, approach, progress, and related reports) of projects of three program divisions (cognitive…

Cognitive and Neural Sciences Division, 1988 Programs.

ERIC Educational Resources Information Center

Vaughan, Willard S., Ed.

The research and development efforts performed by principal investigators under sponsorship of the Office of Naval Research Cognitive and Neural Sciences Division during 1988 are documented. The title, name and affiliation of the principal investigator, project code, contract number, current end date, technical objective, approach, and progress of…

Monaural Speech Segregation by Integrating Primitive and Schema-Based Analysis

DTIC Science & Technology

2008-02-03

vol. 19, pp. 475-492. Wang D.L. and Chang P.S. (2008): An oscillatory correlation model of auditory streaming. Cognitive Neurodynamics , vol. 2, pp...Subcontracts DeLiang Wang (Principal Investigator) March 2008 Department of Computer Science & Engineering and Center for Cognitive Science The

Cognitive Apprenticeship in Health Sciences Education: A Qualitative Review

ERIC Educational Resources Information Center

Lyons, Kayley; McLaughlin, Jacqueline E.; Khanova, Julia; Roth, Mary T.

2017-01-01

Cognitive apprenticeship theory emphasizes the process of making expert thinking "visible" to students and fostering the cognitive and meta-cognitive processes required for expertise. The purpose of this review was to evaluate the use of cognitive apprenticeship theory with the primary aim of understanding how and to what extent the…

The development and validation of Science Learning Inventory (SLI): A conceptual change framework

NASA Astrophysics Data System (ADS)

Seyedmonir, Mehdi

2000-12-01

A multidimensional theoretical model, Conceptual Change Science Learning (CCSL), was developed based on Standard Model of Conceptual Change and Cognitive Reconstruction of Knowledge Model. The model addresses three main components of science learning, namely the learner's conceptual ecology, the message along with its social context, and the cognitive engagement. A learner's conceptual ecology is organized around three clusters, including epistemological beliefs, existing conceptions, and motivation. Learner's cognitive engagement is represented by a continuum from peripheral processing involving shallow cognitive engagement to central processing involving deep cognitive engagement. Through reciprocal, non-sequential interactions of such constructs, the learners' conceptual change is achieved. Using a quantitative empirical approach, three studies were conducted to investigate the theoretical constructs based on the CCSL Model. The first study reports the development and validation of the hypothesized and factor-analytic scales comprising the instrument, Science Learning Inventory (SLI) intended for college students. The self-report instrument was designed in two parts, SLI-A (conceptual ecology and cognitive engagement) with 48 initial items, and SLI-B (science epistemology) with 49 initial items. The items for SLI-B were based on the tenets of Nature of Science as reflected in the recent reform documents, Science for All Americans (Project 2061) and National Science Education Standards. The results of factor analysis indicated seven factors for SLI-A and four factors for SLI-B. The second study investigated the criterion-related (conceptual change) predictive validity of the SLI in an instructional setting (a college-level physics course). The findings suggested the possibility of different interplay of factors and dynamics depending on the nature of the criterion (gain scores from a three-week intervention versus final course grade). Gain scores were predicted by "self-reflective study behavior" and "science self-efficacy" scales of SLI, whereas the course grade was predicted by "metacognitive engagement" and "dynamic scientific truth," (a factor from science epistemology). The third study investigated the effects of text-based conceptual-change strategy (Enhanced Refutational Text; ERT) on Newtonian Laws of Motion, and the efficacy of the SLI scales in a controlled setting. Also, initial divergent and convergent validity procedures are reported in the study. The results provided partial support for the superiority of ERT over expository text. The ERT was an effective intervention for students with no prior physics background but not for students with prior physics background.

Sex differences in intrinsic aptitude for mathematics and science?: a critical review.

PubMed

Spelke, Elizabeth S

2005-12-01

This article considers 3 claims that cognitive sex differences account for the differential representation of men and women in high-level careers in mathematics and science: (a) males are more focused on objects from the beginning of life and therefore are predisposed to better learning about mechanical systems; (b) males have a profile of spatial and numerical abilities producing greater aptitude for mathematics; and (c) males are more variable in their cognitive abilities and therefore predominate at the upper reaches of mathematical talent. Research on cognitive development in human infants, preschool children, and students at all levels fails to support these claims. Instead, it provides evidence that mathematical and scientific reasoning develop from a set of biologically based cognitive capacities that males and females share. These capacities lead men and women to develop equal talent for mathematics and science.

Enhancing Human-Machine System Performance by Introducing Artificial Cognition in Vehicle Guidance Work Systems

DTIC Science & Technology

2009-10-01

evaluated after each mission using the NASA - TLX method [21]. Moreover, they were interviewed to be able to state problems and suggest system...France, 3 rd -4 th September 2008. [21] Sandra G. Hart & Lowell E. Staveland (1988). Development of NASA - TLX (Task Load Index): Results of...o b s e rv a b le b e h a v io u r o f C P = A C U b e h a v io u r Interpretation Figure 11: The Cognitive Process for generating knowledge

The games psychologists play (and the data they provide).

PubMed

Washburn, David A

2003-05-01

Computer games and the technologies marketed to support them provide unique resources for psychological research. In contrast to the sterility, simplicity, and artificiality that characterizes many cognitive tests, game-like tasks can be complex, ecologically valid, and even fun. In the present paper,the history of psychological research with video games is reviewed, and several thematic benefits of this paradigm are identified. These benefits, as well as the possible pitfalls of research with computer game technology and game-like tasks, are illustrated with data from comparative and cognitive investigations.

Neurale Netwerken en Radarsystemen (Neural Networks and Radar Systems)

DTIC Science & Technology

1989-08-01

general issues in cognitive science", Parallel distributed processing, Vol 1: Foundations, Rumelhart et al. 1986 pp 110-146 THO rapport Pagina 151 36 D.E...34Neural networks (part 2)",Expert Focus, IEEE Expert, Spring 1988. 61 J.A. Anderson, " Cognitive and Psychological Computations with Neural Models", IEEE...Pagina 154 69 David H. Ackley, Geoffrey E. Hinton and Terrence J. Sejnowski, "A Learning Algorithm for Boltzmann machines", cognitive science 9, 147-169

Lessons from cognitive neuropsychology for cognitive science: a reply to Patterson and Plaut (2009).

PubMed

Coltheart, Max

2010-01-01

A recent article in this journal (Patterson & Plaut, 2009) argued that cognitive neuropsychology has told us very little over the past 30 or 40 years about "how the brain accomplishes its cognitive business." This may well be true, but it is not important, because the principal aim of cognitive neuropsychology is not to learn about the brain. Its principal aim is instead to learn about the mind, that is, to elucidate the functional architecture of cognition. I show that this is so (a) via extensive quotations from leading figures in this field and (b) by analysis of the subject matter of articles in the leading journal in the field, Cognitive Neuropsychology. Recent reviews of the past 25 years of work in this field (Coltheart & Caramazza, 2006) have concluded that cognitive neuropsychology has told us much about the functional architecture of cognition in a variety of cognitive domains. Patterson and Plaut (2009) did not consider this aim of cognitive neuropsychology. Therefore, their conclusions that cognitive neuropsychology has not been successful, and that this is because the particular methods it uses are flawed, are not justified. Copyright © 2009 Cognitive Science Society, Inc.

The re-tooled mind: how culture re-engineers cognition

PubMed Central

2010-01-01

One of the main goals of cognitive science is to discover the underlying principles that characterize human cognition, but this enterprise is complicated by culturally-driven variability. While much fruitful work has focused on how culture influences the contents of cognition, here I argue that culture can in addition exercise a profound effect on the how of cognition—the mechanisms by which cognitive tasks get done. I argue that much of the fundamental processes of daily cognitive activity involve the operation of cognitive tools that are not genetically determined but instead are invented and culturally transmitted. Further, these cognitive inventions become ‘firmware’, consituting a re-engineering of the individual’s cognitive architecture. That is, ontogenetic experience from one’s cultural context serves to re-tool the developing mind into a variety of disparate cognitive phenotypes. Drawing on several mutually isolated literatures, I advance four claims to the effect that cognitive tools (i) are ubitquitous in everyday cognition, (ii) result in reorganization of the neural system, (iii) are founded in embodied representations and (iv) were made possible by the evolution of an unprecedented degree of voluntary control over the body. I conclude by discussing the implications for the agenda of cognitive science. PMID:20068033

The status of women cognitive scientists in Canada: Insights from publicly available NSERC funding data.

PubMed

Titone, Debra; Tiv, Mehrgol; Pexman, Penny M

2018-06-01

A crucial question within science and academia, and cognitive science specifically, is whether there is gender disparity in opportunity and advancement over the professional life span (e.g., Ceci, Ginther, Kahn, & Williams, 2014; Geraci, Balsis, & Busch, 2015; Valian, 1998). To investigate this question, we analyzed gender distributions in publicly available federal funding data from the Natural Sciences and Engineering Research Council (NSERC) of Canada that are specific to cognitive psychology and cognitive neuroscience. There were three key results. First, the proportion of women cognitive scientists progressively diminished at each career stage, particularly at the transition between graduate and postdoctoral studies. Second, female principal investigators (PI) received smaller average Discovery Grant amounts and were less likely to receive Discovery Accelerator Supplements as a proportion of all Discovery Grants funded. Finally, at the PI level, gender differences were relatively smaller for institution-initiated grants (i.e., Canada Research Chairs) versus investigator-initiated grants (i.e., Discovery Grants). It is our hope that presentation of such data, in concert with other recent reports for our field (e.g., Klatzky, Holt, & Behrmann, 2015; Peelle, 2016; Vaid & Geraci, 2016), continues to raise awareness that gender parity issues remain a concern that deserves ongoing attention within the field of cognitive science in Canada. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

A New Direction in Psychology and Politics

ERIC Educational Resources Information Center

Goldstein, Evan R.

2008-01-01

Jonathan Haidt remembers reading "Metaphors We Live By", the influential book that George P. Lakoff, a professor of linguistics and cognitive science at the University of California at Berkeley, wrote with Mark L. Johnson, a professor of philosophy at the University of Oregon. The book drew on cognitive science, psychology, linguistics, and…

Integrating Cognitive Science and Technology Improves Learning in a STEM Classroom

ERIC Educational Resources Information Center

Butler, Andrew C.; Marsh, Elizabeth J.; Slavinsky, J. P.; Baraniuk, Richard G.

2014-01-01

The most effective educational interventions often face significant barriers to widespread implementation because they are highly specific, resource intense, and/or comprehensive. We argue for an alternative approach to improving education: leveraging technology and cognitive science to develop interventions that generalize, scale, and can be…

Cognitive Science and Assessment. ERIC Digest.

ERIC Educational Resources Information Center

Boston, Carol

This Digest provides educators with an overview of some important facets of cognitive science research and suggests implications for classroom assessment. Education researchers study the thinking of experts in various subject areas to understand the concepts and procedures that are the most important to teach and to help determine how to move…

Personalization vs. How People Learn

ERIC Educational Resources Information Center

Riley, Benjamin

2017-01-01

Riley asserts that some findings of cognitive science conflict with key principles of personalized learning--that students should control the content of their learning and that they should control the pace of their learning. A personalized approach is in conflict with the cognitive science principle that committing key facts in a discipline to…

Instructional Design Theory: Advancements from Cognitive Science and Instructional Technology.

ERIC Educational Resources Information Center

Tennyson, Robert D.

Scientific advancements in cognitive science and instructional technology extend the behaviorally-oriented learning paradigm of instructional design and management in three major areas: (1) analysis of information-to-be-learned; (2) means of evaluating learners; and (3) linkage of learning theory to instructional prescriptions. The two basic types…

The Value of Knowing How Students Learn

ERIC Educational Resources Information Center

Riley, Benjamin

2016-01-01

Deans for Impact, a nonprofit organization composed of leaders of educator-preparation programs throughout the U.S., believes cognitive science is an important part of an evidence-based core of knowledge that preservice teachers should possess. Member deans believe that cognitive science holds promise for improving learning and promoting the…

Cognitive and Neural Sciences Division, 1989 Programs.

ERIC Educational Resources Information Center

Vaughan, Willard S., Ed.

This report documents research and development performed by principal investigators under the sponsorship of the Office of Naval Research Cognitive and Neural Sciences Division during fiscal year 1989. Programs are conducted under contracts and grants awarded on the basis of proposals received in response to a Broad Agency Announcement in the…

Cognitive Development and Science Instruction: A Review of Some Recent Research Findings.

ERIC Educational Resources Information Center

Padilla, Michael

Reviewed are several pertinent research articles dealing with cognitive development, Piaget's theories, and science instruction, especially those that relate to procedures that can be implemented by classroom teachers. The research findings on developmental levels of Piaget discuss: (1) tasks that indicate a change from preoperational to concrete…

Exploring cognitive integration of basic science and its effect on diagnostic reasoning in novices.

PubMed

Lisk, Kristina; Agur, Anne M R; Woods, Nicole N

2016-06-01

Integration of basic and clinical science knowledge is increasingly being recognized as important for practice in the health professions. The concept of 'cognitive integration' places emphasis on the value of basic science in providing critical connections to clinical signs and symptoms while accounting for the fact that clinicians may not spontaneously articulate their use of basic science knowledge in clinical reasoning. In this study we used a diagnostic justification test to explore the impact of integrated basic science instruction on novices' diagnostic reasoning process. Participants were allocated to an integrated basic science or clinical science training group. The integrated basic science group was taught the clinical features along with the underlying causal mechanisms of four musculoskeletal pathologies while the clinical science group was taught only the clinical features. Participants completed a diagnostic accuracy test immediately after initial learning, and one week later a diagnostic accuracy and justification test. The results showed that novices who learned the integrated causal mechanisms had superior diagnostic accuracy and better understanding of the relative importance of key clinical features. These findings further our understanding of cognitive integration by providing evidence of the specific changes in clinical reasoning when basic and clinical sciences are integrated during learning.

Research approaches to mass casualty incidents response: development from routine perspectives to complexity science.

PubMed

Shen, Weifeng; Jiang, Libing; Zhang, Mao; Ma, Yuefeng; Jiang, Guanyu; He, Xiaojun

2014-01-01

To review the research methods of mass casualty incident (MCI) systematically and introduce the concept and characteristics of complexity science and artificial system, computational experiments and parallel execution (ACP) method. We searched PubMed, Web of Knowledge, China Wanfang and China Biology Medicine (CBM) databases for relevant studies. Searches were performed without year or language restrictions and used the combinations of the following key words: "mass casualty incident", "MCI", "research method", "complexity science", "ACP", "approach", "science", "model", "system" and "response". Articles were searched using the above keywords and only those involving the research methods of mass casualty incident (MCI) were enrolled. Research methods of MCI have increased markedly over the past few decades. For now, dominating research methods of MCI are theory-based approach, empirical approach, evidence-based science, mathematical modeling and computer simulation, simulation experiment, experimental methods, scenario approach and complexity science. This article provides an overview of the development of research methodology for MCI. The progresses of routine research approaches and complexity science are briefly presented in this paper. Furthermore, the authors conclude that the reductionism underlying the exact science is not suitable for MCI complex systems. And the only feasible alternative is complexity science. Finally, this summary is followed by a review that ACP method combining artificial systems, computational experiments and parallel execution provides a new idea to address researches for complex MCI.

Expertise in Problem Solving.

ERIC Educational Resources Information Center

Chi, Michelene T. H.; And Others

Based on the premise that the quality of domain-specific knowledge is the main determinant of expertise in that domain, an examination was made of the shift from considering general, domain-independent skills and procedures, in both cognitive psychology and artificial intelligence, to the study of the knowledge base. Empirical findings and…

Robotics as an Educational Tool.

ERIC Educational Resources Information Center

Miglino, Orazio; Lund, Henrik Hautop; Cardaci, Maurizio

1999-01-01

Explores a new educational application of Piaget's theories of cognitive development: the use, as a teaching tool, of physical robots conceived as artificial organisms. Reviews educational projects using real robots. Shows that the use of intelligent systems to enlarge the view of biological reality could become an integral part of curricula in…

Computer Tutors Get Personal

ERIC Educational Resources Information Center

Johnson, David L.

2005-01-01

After decades of research in artificial intelligence (AI) and cognitive psychology, a number of companies have emerged that offer intelligent tutor system (ITS) soft ware to schools. These systems try to mimic the help that a human tutor would provide to an individual student, something nearly impossible for teachers to accomplish in the…

Human Intelligence: An Introduction to Advances in Theory and Research.

ERIC Educational Resources Information Center

Lohman, David F.

1989-01-01

Recent advances in three research traditions are summarized: trait theories of intelligence, information-processing theories of intelligence, and general theories of thinking. Work on fluid and crystallized abilities by J. Horn and R. Snow, mental speed, spatial visualization, cognitive psychology, artificial intelligence, and the construct of…

Declarative and Procedural Memory as Individual Differences in Second Language Acquisition

ERIC Educational Resources Information Center

Morgan-Short, Kara; Faretta-Stutenberg, Mandy; Brill-Schuetz, Katherine A.; Carpenter, Helen; Wong, Patrick C. M.

2014-01-01

This study examined how individual differences in cognitive abilities account for variance in the attainment level of adult second language (L2) syntactic development. Participants completed assessments of declarative and procedural learning abilities. They subsequently learned an artificial L2 under implicit training conditions and received…

Incremental Inductive Learning in a Constructivist Agent

NASA Astrophysics Data System (ADS)

Perotto, Filipo Studzinski; Älvares, Luís Otávio

The constructivist paradigm in Artificial Intelligence has been definitively inaugurated in the earlier 1990's by Drescher's pioneer work [10]. He faces the challenge of design an alternative model for machine learning, founded in the human cognitive developmental process described by Piaget [x]. His effort has inspired many other researchers.

Computational Models for Belief Revision, Group Decision-Making and Cultural Shifts

DTIC Science & Technology

2010-10-25

34social" networks; the green numbers are pseudo-trees or artificial (non-social) constructions. The dashed blue line indicates the range of Erdos- Renyi ...non-social networks such as Erdos- Renyi random graphs or the more passive non-cognitive spreading of disease or information flow, As mentioned

Reading Comprehension II. Bibliographies and Summaries of Selected Articles. Volume 6. Research Review Series.

ERIC Educational Resources Information Center

MacGinitie, Walter H.; And Others

Summaries of several papers are presented to develop a working theoretical analysis of reading comprehension and an understanding of development in language comprehension based upon empirical studies. Contributions from the areas of assessment, artificial intelligence, cognition (including schema theory), instruction, linguistics, learning…

Executive Function Predicts Artificial Language Learning in Children and Adults

ERIC Educational Resources Information Center

Kapa, Leah Lynn

2013-01-01

Prior research has established an executive function advantage among bilinguals as compared to monolingual peers. These non-linguistic cognitive advantages are largely assumed to result from the experience of managing two linguistic systems. However, the possibility remains that the relationship between bilingualism and executive function is…

Artificial intelligence in nanotechnology.

PubMed

Sacha, G M; Varona, P

2013-11-15

During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

Artificial intelligence in nanotechnology

NASA Astrophysics Data System (ADS)

Sacha, G. M.; Varona, P.

2013-11-01

During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

Development of artificial meteor for observation of upper atmosphere

NASA Astrophysics Data System (ADS)

Watanabe, Masaki; Sahara, Hironori; Abe, Shinsuke; Watanabe, Takeo; Nojiri, Yuta; Okajima, Lena

2016-04-01

This study proposes a method for the observation of the upper atmosphere using an artificial meteor injected by a mass driver installed on a microsatellite. The mass driver injects a pill at a velocity of 200 m/s and deorbits it into the atmosphere. The emission of the pill can then be observed from the ground at the necessary time and location. This approach could contribute to a better understanding of the global environment as well as different aspects of astronomy and planetary science. To realize the proposed method, the required size and emission of the pill have to be determined. Therefore, we conducted flow-field simulations, spectroscopic estimations, and an experiment on an artificial meteor in the arc heater wind tunnel at the Institute of Space and Astronautical Science in the Japan Aerospace Exploration Agency (ISAS/JAXA). From the results, we confirmed that the light emission could be observed as a shooting star by the naked eye and thus verified the feasibility of the method.

Artificial photosynthesis: understanding water splitting in nature

PubMed Central

Cox, Nicholas; Pantazis, Dimitrios A.; Neese, Frank; Lubitz, Wolfgang

2015-01-01

In the context of a global artificial photosynthesis (GAP) project, we review our current work on nature's water splitting catalyst. In a recent report (Cox et al. 2014 Science 345, 804–808 (doi:10.1126/science.1254910)), we showed that the catalyst—a Mn4O5Ca cofactor—converts into an ‘activated’ form immediately prior to the O–O bond formation step. This activated state, which represents an all MnIV complex, is similar to the structure observed by X-ray crystallography but requires the coordination of an additional water molecule. Such a structure locates two oxygens, both derived from water, in close proximity, which probably come together to form the product O2 molecule. We speculate that formation of the activated catalyst state requires inherent structural flexibility. These features represent new design criteria for the development of biomimetic and bioinspired model systems for water splitting catalysts using first-row transition metals with the aim of delivering globally deployable artificial photosynthesis technologies. PMID:26052426