Agent-Based Learning Environments as a Research Tool for Investigating Teaching and Learning.

ERIC Educational Resources Information Center

Baylor, Amy L.

2002-01-01

Discusses intelligent learning environments for computer-based learning, such as agent-based learning environments, and their advantages over human-based instruction. Considers the effects of multiple agents; agents and research design; the use of Multiple Intelligent Mentors Instructing Collaboratively (MIMIC) for instructional design for…

Intelligent agent-based intrusion detection system using enhanced multiclass SVM.

PubMed

Ganapathy, S; Yogesh, P; Kannan, A

2012-01-01

Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set.

Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM

PubMed Central

Ganapathy, S.; Yogesh, P.; Kannan, A.

2012-01-01

Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set. PMID:23056036

Mission planning and simulation via intelligent agents

NASA Technical Reports Server (NTRS)

Gargan, Robert A., Jr.; Tilley, Randall W.

1987-01-01

A system that can operate from a flight manifest to plan and simulate payload preparation and transport via Shuttle flights is described. The design alternatives and the prototype implementation of the payload hardware and inventory tracking system are discussed. It is shown how intelligent agents can be used to generate mission schedules, and how, through the use of these intelligent agents, knowledge becomes separated into small manageable knowledge bases.

Agent Prompts: Scaffolding for Productive Reflection in an Intelligent Learning Environment

ERIC Educational Resources Information Center

Wu, Longkai; Looi, Chee-Kit

2012-01-01

Recent research has emphasized the importance of reflection for students in intelligent learning environments. This study tries to investigate whether agent prompts, acting as scaffolding, can promote students' reflection when they act as tutor through teaching the agent tutee in a learning-by-teaching environment. Two types of agent prompts are…

Agents Control in Intelligent Learning Systems: The Case of Reactive Characteristics

ERIC Educational Resources Information Center

Laureano-Cruces, Ana Lilia; Ramirez-Rodriguez, Javier; de Arriaga, Fernando; Escarela-Perez, Rafael

2006-01-01

Intelligent learning systems (ILSs) have evolved in the last few years basically because of influences received from multi-agent architectures (MAs). Conflict resolution among agents has been a very important problem for multi-agent systems, with specific features in the case of ILSs. The literature shows that ILSs with cognitive or pedagogical…

Decision Facilitator for Launch Operations using Intelligent Agents

NASA Technical Reports Server (NTRS)

Thirumalainambi, Rajkumar; Bardina, Jorge

2005-01-01

Launch operations require millions of micro-decisions which contribute to the macro decision of 'Go/No-Go' for a launch. Knowledge workers"(such as managers and technical professionals) need information in a timely precise manner as it can greatly affect mission success. The intelligent agent (web search agent) uses the words of a hypertext markup language document which is connected through the internet. The intelligent agent's actions are to determine if its goal of seeking a website containing a specified target (e.g., keyword or phrase), has been met. There are few parameters that should be defined for the keyword search like "Go" and "No-Go". Instead of visiting launch and range decision making servers individually, the decision facilitator constantly connects to all servers, accumulating decisions so the final decision can be decided in a timely manner. The facilitator agent uses the singleton design pattern, which ensures that only a single instance of the facilitator agent exists at one time. Negotiations could proceed between many agents resulting in a final decision. This paper describes details of intelligent agents and their interaction to derive an unified decision support system.

Adaptive method with intercessory feedback control for an intelligent agent

DOEpatents

Goldsmith, Steven Y.

2004-06-22

An adaptive architecture method with feedback control for an intelligent agent provides for adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. An adaptive architecture method with feedback control for multiple intelligent agents provides for coordinating and adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. Re-programming of the adaptive architecture is through a nexus which coordinates reflexive and deliberator components.

Personalized E- learning System Based on Intelligent Agent

NASA Astrophysics Data System (ADS)

Duo, Sun; Ying, Zhou Cai

Lack of personalized learning is the key shortcoming of traditional e-Learning system. This paper analyzes the personal characters in e-Learning activity. In order to meet the personalized e-learning, a personalized e-learning system based on intelligent agent was proposed and realized in the paper. The structure of system, work process, the design of intelligent agent and the realization of intelligent agent were introduced in the paper. After the test use of the system by certain network school, we found that the system could improve the learner's initiative participation, which can provide learners with personalized knowledge service. Thus, we thought it might be a practical solution to realize self- learning and self-promotion in the lifelong education age.

Application of decentralized cooperative problem solving in dynamic flexible scheduling

NASA Astrophysics Data System (ADS)

Guan, Zai-Lin; Lei, Ming; Wu, Bo; Wu, Ya; Yang, Shuzi

1995-08-01

The object of this study is to discuss an intelligent solution to the problem of task-allocation in shop floor scheduling. For this purpose, the technique of distributed artificial intelligence (DAI) is applied. Intelligent agents (IAs) are used to realize decentralized cooperation, and negotiation is realized by using message passing based on the contract net model. Multiple agents, such as manager agents, workcell agents, and workstation agents, make game-like decisions based on multiple criteria evaluations. This procedure of decentralized cooperative problem solving makes local scheduling possible. And by integrating such multiple local schedules, dynamic flexible scheduling for the whole shop floor production can be realized.

Agent autonomy approach to probabilistic physics-of-failure modeling of complex dynamic systems with interacting failure mechanisms

NASA Astrophysics Data System (ADS)

Gromek, Katherine Emily

A novel computational and inference framework of the physics-of-failure (PoF) reliability modeling for complex dynamic systems has been established in this research. The PoF-based reliability models are used to perform a real time simulation of system failure processes, so that the system level reliability modeling would constitute inferences from checking the status of component level reliability at any given time. The "agent autonomy" concept is applied as a solution method for the system-level probabilistic PoF-based (i.e. PPoF-based) modeling. This concept originated from artificial intelligence (AI) as a leading intelligent computational inference in modeling of multi agents systems (MAS). The concept of agent autonomy in the context of reliability modeling was first proposed by M. Azarkhail [1], where a fundamentally new idea of system representation by autonomous intelligent agents for the purpose of reliability modeling was introduced. Contribution of the current work lies in the further development of the agent anatomy concept, particularly the refined agent classification within the scope of the PoF-based system reliability modeling, new approaches to the learning and the autonomy properties of the intelligent agents, and modeling interacting failure mechanisms within the dynamic engineering system. The autonomous property of intelligent agents is defined as agent's ability to self-activate, deactivate or completely redefine their role in the analysis. This property of agents and the ability to model interacting failure mechanisms of the system elements makes the agent autonomy fundamentally different from all existing methods of probabilistic PoF-based reliability modeling. 1. Azarkhail, M., "Agent Autonomy Approach to Physics-Based Reliability Modeling of Structures and Mechanical Systems", PhD thesis, University of Maryland, College Park, 2007.

A development framework for distributed artificial intelligence

NASA Technical Reports Server (NTRS)

Adler, Richard M.; Cottman, Bruce H.

1989-01-01

The authors describe distributed artificial intelligence (DAI) applications in which multiple organizations of agents solve multiple domain problems. They then describe work in progress on a DAI system development environment, called SOCIAL, which consists of three primary language-based components. The Knowledge Object Language defines models of knowledge representation and reasoning. The metaCourier language supplies the underlying functionality for interprocess communication and control access across heterogeneous computing environments. The metaAgents language defines models for agent organization coordination, control, and resource management. Application agents and agent organizations will be constructed by combining metaAgents and metaCourier building blocks with task-specific functionality such as diagnostic or planning reasoning. This architecture hides implementation details of communications, control, and integration in distributed processing environments, enabling application developers to concentrate on the design and functionality of the intelligent agents and agent networks themselves.

An Intelligent Control for the Distributed Flexible Network Photovoltaic System using Autonomous Control and Agent

NASA Astrophysics Data System (ADS)

Park, Sangsoo; Miura, Yushi; Ise, Toshifumi

This paper proposes an intelligent control for the distributed flexible network photovoltaic system using autonomous control and agent. The distributed flexible network photovoltaic system is composed of a secondary battery bank and a number of subsystems which have a solar array, a dc/dc converter and a load. The control mode of dc/dc converter can be selected based on local information by autonomous control. However, if only autonomous control using local information is applied, there are some problems associated with several cases such as voltage drop on long power lines. To overcome these problems, the authors propose introducing agents to improve control characteristics. The autonomous control with agents is called as intelligent control in this paper. The intelligent control scheme that employs the communication between agents is applied for the model system and proved with simulation using PSCAD/EMTDC.

Intelligent Interoperable Agent Toolkit (I2AT)

DTIC Science & Technology

2005-02-01

Agents, Agent Infrastructure, Intelligent Agents 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT UNCLASSIFIED 18. SECURITY ...CLASSIFICATION OF THIS PAGE UNCLASSIFIED 19. SECURITY CLASSIFICATION OF ABSTRACT UNCLASSIFIED 20. LIMITATION OF ABSTRACT UL NSN 7540-01...those that occur while the submarine is submerged. Using CoABS Grid/Jini service discovery events backed up with a small amount of internal bookkeeping

Global optimization of minority game by intelligent agents

NASA Astrophysics Data System (ADS)

Xie, Yan-Bo; Wang, Bing-Hong; Hu, Chin-Kun; Zhou, Tao

2005-10-01

We propose a new model of minority game with intelligent agents who use trail and error method to make a choice such that the standard deviation σ2 and the total loss in this model reach the theoretical minimum values in the long time limit and the global optimization of the system is reached. This suggests that the economic systems can self-organize into a highly optimized state by agents who make decisions based on inductive thinking, limited knowledge, and capabilities. When other kinds of agents are also present, the simulation results and analytic calculations show that the intelligent agent can gain profits from producers and are much more competent than the noise traders and conventional agents in original minority games proposed by Challet and Zhang.

A Distributed Ambient Intelligence Based Multi-Agent System for Alzheimer Health Care

NASA Astrophysics Data System (ADS)

Tapia, Dante I.; RodríGuez, Sara; Corchado, Juan M.

This chapter presents ALZ-MAS (Alzheimer multi-agent system), an ambient intelligence (AmI)-based multi-agent system aimed at enhancing the assistance and health care for Alzheimer patients. The system makes use of several context-aware technologies that allow it to automatically obtain information from users and the environment in an evenly distributed way, focusing on the characteristics of ubiquity, awareness, intelligence, mobility, etc., all of which are concepts defined by AmI. ALZ-MAS makes use of a services oriented multi-agent architecture, called flexible user and services oriented multi-agent architecture, to distribute resources and enhance its performance. It is demonstrated that a SOA approach is adequate to build distributed and highly dynamic AmI-based multi-agent systems.

Face-to-Face Interaction with Pedagogical Agents, Twenty Years Later

ERIC Educational Resources Information Center

Johnson, W. Lewis; Lester, James C.

2016-01-01

Johnson et al. ("International Journal of Artificial Intelligence in Education," 11, 47-78, 2000) introduced and surveyed a new paradigm for interactive learning environments: animated pedagogical agents. The article argued for combining animated interface agent technologies with intelligent learning environments, yielding intelligent…

Casuist BDI-Agent: A New Extended BDI Architecture with the Capability of Ethical Reasoning

NASA Astrophysics Data System (ADS)

Honarvar, Ali Reza; Ghasem-Aghaee, Nasser

Since the intelligent agent is developed to be cleverer, more complex, and yet uncontrollable, a number of problems have been recognized. The capability of agents to make moral decisions has become an important question, when intelligent agents have developed more autonomous and human-like. We propose Casuist BDI-Agent architecture which extends the power of BDI architecture. Casuist BDI-Agent architecture combines CBR method in AI and bottom up casuist approach in ethics in order to add capability of ethical reasoning to BDI-Agent.

Intelligent systems in the context of surrounding environment.

PubMed

Wakeling, J; Bak, P

2001-11-01

We investigate the behavioral patterns of a population of agents, each controlled by a simple biologically motivated neural network model, when they are set in competition against each other in the minority model of Challet and Zhang. We explore the effects of changing agent characteristics, demonstrating that crowding behavior takes place among agents of similar memory, and show how this allows unique "rogue" agents with higher memory values to take advantage of a majority population. We also show that agents' analytic capability is largely determined by the size of the intermediary layer of neurons. In the context of these results, we discuss the general nature of natural and artificial intelligence systems, and suggest intelligence only exists in the context of the surrounding environment (embodiment).

Developmental reversals in risky decision making: intelligence agents show larger decision biases than college students.

PubMed

Reyna, Valerie F; Chick, Christina F; Corbin, Jonathan C; Hsia, Andrew N

2014-01-01

Intelligence agents make risky decisions routinely, with serious consequences for national security. Although common sense and most theories imply that experienced intelligence professionals should be less prone to irrational inconsistencies than college students, we show the opposite. Moreover, the growth of experience-based intuition predicts this developmental reversal. We presented intelligence agents, college students, and postcollege adults with 30 risky-choice problems in gain and loss frames and then compared the three groups' decisions. The agents not only exhibited larger framing biases than the students, but also were more confident in their decisions. The postcollege adults (who were selected to be similar to the students) occupied an interesting middle ground, being generally as biased as the students (sometimes more biased) but less biased than the agents. An experimental manipulation testing an explanation for these effects, derived from fuzzy-trace theory, made the students look as biased as the agents. These results show that, although framing biases are irrational (because equivalent outcomes are treated differently), they are the ironical output of cognitively advanced mechanisms of meaning making.

Intelligent Agents and Their Potential for Future Design and Synthesis Environment

NASA Technical Reports Server (NTRS)

Noor, Ahmed K. (Compiler); Malone, John B. (Compiler)

1999-01-01

This document contains the proceedings of the Workshop on Intelligent Agents and Their Potential for Future Design and Synthesis Environment, held at NASA Langley Research Center, Hampton, VA, September 16-17, 1998. The workshop was jointly sponsored by the University of Virginia's Center for Advanced Computational Technology and NASA. Workshop attendees came from NASA, industry and universities. The objectives of the workshop were to assess the status of intelligent agents technology and to identify the potential of software agents for use in future design and synthesis environment. The presentations covered the current status of agent technology and several applications of intelligent software agents. Certain materials and products are identified in this publication in order to specify adequately the materials and products that were investigated in the research effort. In no case does such identification imply recommendation or endorsement of products by NASA, nor does it imply that the materials and products are the only ones or the best ones available for this purpose. In many cases equivalent materials and products are available and would probably produce equivalent results.

Modeling and simulating human teamwork behaviors using intelligent agents

NASA Astrophysics Data System (ADS)

Fan, Xiaocong; Yen, John

2004-12-01

Among researchers in multi-agent systems there has been growing interest in using intelligent agents to model and simulate human teamwork behaviors. Teamwork modeling is important for training humans in gaining collaborative skills, for supporting humans in making critical decisions by proactively gathering, fusing, and sharing information, and for building coherent teams with both humans and agents working effectively on intelligence-intensive problems. Teamwork modeling is also challenging because the research has spanned diverse disciplines from business management to cognitive science, human discourse, and distributed artificial intelligence. This article presents an extensive, but not exhaustive, list of work in the field, where the taxonomy is organized along two main dimensions: team social structure and social behaviors. Along the dimension of social structure, we consider agent-only teams and mixed human-agent teams. Along the dimension of social behaviors, we consider collaborative behaviors, communicative behaviors, helping behaviors, and the underpinning of effective teamwork-shared mental models. The contribution of this article is that it presents an organizational framework for analyzing a variety of teamwork simulation systems and for further studying simulated teamwork behaviors.

Towards a Cognitively Realistic Computational Model of Team Problem Solving Using ACT-R Agents and the ELICIT Experimentation Framework

DTIC Science & Technology

2014-06-01

intelligence analysis processes. However, as has been noted in previous work (e.g., [42]), there are a number of important differences between the nature of the...problem encountered in the context of the ELICIT task and the problems dealt with by intelligence analysts. Perhaps most importantly, the fact that a...see Section 7). 6 departure from the reality of most intelligence analysis situations: in most real-world intelligence analysis problems agents have

The Foreign Intelligence Surveillance Act: An Overview of the Statutory Framework and U.S. Foreign Intelligence Surveillance Court and U.S. Foreign Intelligence Surveillance Court of Review Decisions

DTIC Science & Technology

2007-02-15

an application for electronic surveillance of an agent of a foreign power and for an FISC order renewing that surveillance, both subject to...Review) of an FISC order authorizing electronic surveillance of an agent of a foreign power, subject to restrictions flowing from the May 17th...their agents .”13 However, the guidance which the Court provided in Keith with respect to national security surveillance in a domestic context to some

A Generalized Quantum-Inspired Decision Making Model for Intelligent Agent

PubMed Central

Loo, Chu Kiong

2014-01-01

A novel decision making for intelligent agent using quantum-inspired approach is proposed. A formal, generalized solution to the problem is given. Mathematically, the proposed model is capable of modeling higher dimensional decision problems than previous researches. Four experiments are conducted, and both empirical experiments results and proposed model's experiment results are given for each experiment. Experiments showed that the results of proposed model agree with empirical results perfectly. The proposed model provides a new direction for researcher to resolve cognitive basis in designing intelligent agent. PMID:24778580

Understanding the Impact of Intelligent Tutoring Agents on Real-Time Training Simulations

DTIC Science & Technology

2011-01-01

environments has increased. Intelligent Tutoring Systems (ITS) technology may include reactive or proactive simulation agents that monitor and... environments . These reactive agents monitor the trainee’s progress and provide hints or other feedback only when there is sufficient variance from... agents have a higher computational cost in that they need to sense and understand more about the trainee, environment and training context, but are

Balancing Human and Inter-Agent Influences for Shared Control of Bio-Inspired Collectives

DTIC Science & Technology

2014-10-01

the higher-level intelligence and ingenuity of a human operator as well as the collective intelligence and robustness of a bio-inspired collective...for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway...agents, or that receive information from, but are not directly controlled by, a human operator . Unlike, agents in the human-controlled partition, agents

Intelligent multiagent coordination based on reinforcement hierarchical neuro-fuzzy models.

PubMed

Mendoza, Leonardo Forero; Vellasco, Marley; Figueiredo, Karla

2014-12-01

This paper presents the research and development of two hybrid neuro-fuzzy models for the hierarchical coordination of multiple intelligent agents. The main objective of the models is to have multiple agents interact intelligently with each other in complex systems. We developed two new models of coordination for intelligent multiagent systems, which integrates the Reinforcement Learning Hierarchical Neuro-Fuzzy model with two proposed coordination mechanisms: the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with a market-driven coordination mechanism (MA-RL-HNFP-MD) and the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with graph coordination (MA-RL-HNFP-CG). In order to evaluate the proposed models and verify the contribution of the proposed coordination mechanisms, two multiagent benchmark applications were developed: the pursuit game and the robot soccer simulation. The results obtained demonstrated that the proposed coordination mechanisms greatly improve the performance of the multiagent system when compared with other strategies.

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

Ontological Engineering and Mapping in Multiagent Systems Development

DTIC Science & Technology

2002-03-01

for knowledge engineering or artificial intelligence . Nicola Guarino compares the various definitions and the differences in their meaning in...act upon the environment through effectors [Russel and Norvig 1995]. An intelligent agent is an agent that takes the best possible action in a...situation in order to accomplish its goals. Determining what exactly characterizes the best possible action splits the field of artificial intelligence

Learning comunication strategies for distributed artificial intelligence

NASA Astrophysics Data System (ADS)

Kinney, Michael; Tsatsoulis, Costas

1992-08-01

We present a methodology that allows collections of intelligent system to automatically learn communication strategies, so that they can exchange information and coordinate their problem solving activity. In our methodology communication between agents is determined by the agents themselves, which consider the progress of their individual problem solving activities compared to the communication needs of their surrounding agents. Through learning, communication lines between agents might be established or disconnected, communication frequencies modified, and the system can also react to dynamic changes in the environment that might force agents to cease to exist or to be added. We have established dynamic, quantitative measures of the usefulness of a fact, the cost of a fact, the work load of an agent, and the selfishness of an agent (a measure indicating an agent's preference between transmitting information versus performing individual problem solving), and use these values to adapt the communication between intelligent agents. In this paper we present the theoretical foundations of our work together with experimental results and performance statistics of networks of agents involved in cooperative problem solving activities.

Agent planning in AgScala

NASA Astrophysics Data System (ADS)

Tošić, Saša; Mitrović, Dejan; Ivanović, Mirjana

2013-10-01

Agent-oriented programming languages are designed to simplify the development of software agents, especially those that exhibit complex, intelligent behavior. This paper presents recent improvements of AgScala, an agent-oriented programming language based on Scala. AgScala includes declarative constructs for managing beliefs, actions and goals of intelligent agents. Combined with object-oriented and functional programming paradigms offered by Scala, it aims to be an efficient framework for developing both purely reactive, and more complex, deliberate agents. Instead of the Prolog back-end used initially, the new version of AgScala relies on Agent Planning Package, a more advanced system for automated planning and reasoning.

The influence of active vision on the exoskeleton of intelligent agents

NASA Astrophysics Data System (ADS)

Smith, Patrice; Terry, Theodore B.

2016-04-01

Chameleonization occurs when a self-learning autonomous mobile system's (SLAMR) active vision scans the surface of which it is perched causing the exoskeleton to changes colors exhibiting a chameleon effect. Intelligent agents having the ability to adapt to their environment and exhibit key survivability characteristics of its environments would largely be due in part to the use of active vision. Active vision would allow the intelligent agent to scan its environment and adapt as needed in order to avoid detection. The SLAMR system would have an exoskeleton, which would change, based on the surface it was perched on; this is known as the "chameleon effect." Not in the common sense of the term, but from the techno-bio inspired meaning as addressed in our previous paper. Active vision, utilizing stereoscopic color sensing functionality would enable the intelligent agent to scan an object within its close proximity, determine the color scheme, and match it; allowing the agent to blend with its environment. Through the use of its' optical capabilities, the SLAMR system would be able to further determine its position, taking into account spatial and temporal correlation and spatial frequency content of neighboring structures further ensuring successful background blending. The complex visual tasks of identifying objects, using edge detection, image filtering, and feature extraction are essential for an intelligent agent to gain additional knowledge about its environmental surroundings.

Research on Intelligent Synthesis Environments

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.; Lobeck, William E.

2002-01-01

Four research activities related to Intelligent Synthesis Environment (ISE) have been performed under this grant. The four activities are: 1) non-deterministic approaches that incorporate technologies such as intelligent software agents, visual simulations and other ISE technologies; 2) virtual labs that leverage modeling, simulation and information technologies to create an immersive, highly interactive virtual environment tailored to the needs of researchers and learners; 3) advanced learning modules that incorporate advanced instructional, user interface and intelligent agent technologies; and 4) assessment and continuous improvement of engineering team effectiveness in distributed collaborative environments.

Research on Intelligent Synthesis Environments

NASA Astrophysics Data System (ADS)

Noor, Ahmed K.; Loftin, R. Bowen

2002-12-01

Four research activities related to Intelligent Synthesis Environment (ISE) have been performed under this grant. The four activities are: 1) non-deterministic approaches that incorporate technologies such as intelligent software agents, visual simulations and other ISE technologies; 2) virtual labs that leverage modeling, simulation and information technologies to create an immersive, highly interactive virtual environment tailored to the needs of researchers and learners; 3) advanced learning modules that incorporate advanced instructional, user interface and intelligent agent technologies; and 4) assessment and continuous improvement of engineering team effectiveness in distributed collaborative environments.

A multi-agent intelligent environment for medical knowledge.

PubMed

Vicari, Rosa M; Flores, Cecilia D; Silvestre, André M; Seixas, Louise J; Ladeira, Marcelo; Coelho, Helder

2003-03-01

AMPLIA is a multi-agent intelligent learning environment designed to support training of diagnostic reasoning and modelling of domains with complex and uncertain knowledge. AMPLIA focuses on the medical area. It is a system that deals with uncertainty under the Bayesian network approach, where learner-modelling tasks will consist of creating a Bayesian network for a problem the system will present. The construction of a network involves qualitative and quantitative aspects. The qualitative part concerns the network topology, that is, causal relations among the domain variables. After it is ready, the quantitative part is specified. It is composed of the distribution of conditional probability of the variables represented. A negotiation process (managed by an intelligent MediatorAgent) will treat the differences of topology and probability distribution between the model the learner built and the one built-in in the system. That negotiation process occurs between the agents that represent the expert knowledge domain (DomainAgent) and the agent that represents the learner knowledge (LearnerAgent).

Design and Control of Large Collections of Learning Agents

NASA Technical Reports Server (NTRS)

Agogino, Adrian

2001-01-01

The intelligent control of multiple autonomous agents is an important yet difficult task. Previous methods used to address this problem have proved to be either too brittle, too hard to use, or not scalable to large systems. The 'Collective Intelligence' project at NASA/Ames provides an elegant, machine-learning approach to address these problems. This approach mathematically defines some essential properties that a reward system should have to promote coordinated behavior among reinforcement learners. This work has focused on creating additional key properties and algorithms within the mathematics of the Collective Intelligence framework. One of the additions will allow agents to learn more quickly, in a more coordinated manner. The other will let agents learn with less knowledge of their environment. These additions will allow the framework to be applied more easily, to a much larger domain of multi-agent problems.

Quantum Speedup for Active Learning Agents

NASA Astrophysics Data System (ADS)

Paparo, Giuseppe Davide; Dunjko, Vedran; Makmal, Adi; Martin-Delgado, Miguel Angel; Briegel, Hans J.

2014-07-01

Can quantum mechanics help us build intelligent learning agents? A defining signature of intelligent behavior is the capacity to learn from experience. However, a major bottleneck for agents to learn in real-life situations is the size and complexity of the corresponding task environment. Even in a moderately realistic environment, it may simply take too long to rationally respond to a given situation. If the environment is impatient, allowing only a certain time for a response, an agent may then be unable to cope with the situation and to learn at all. Here, we show that quantum physics can help and provide a quadratic speedup for active learning as a genuine problem of artificial intelligence. This result will be particularly relevant for applications involving complex task environments.

Inconsistency as a diagnostic tool in a society of intelligent agents.

PubMed

McShane, Marjorie; Beale, Stephen; Nirenburg, Sergei; Jarrell, Bruce; Fantry, George

2012-07-01

To use the detection of clinically relevant inconsistencies to support the reasoning capabilities of intelligent agents acting as physicians and tutors in the realm of clinical medicine. We are developing a cognitive architecture, OntoAgent, that supports the creation and deployment of intelligent agents capable of simulating human-like abilities. The agents, which have a simulated mind and, if applicable, a simulated body, are intended to operate as members of multi-agent teams featuring both artificial and human agents. The agent architecture and its underlying knowledge resources and processors are being developed in a sufficiently generic way to support a variety of applications. We show how several types of inconsistency can be detected and leveraged by intelligent agents in the setting of clinical medicine. The types of inconsistencies discussed include: test results not supporting the doctor's hypothesis; the results of a treatment trial not supporting a clinical diagnosis; and information reported by the patient not being consistent with observations. We show the opportunities afforded by detecting each inconsistency, such as rethinking a hypothesis, reevaluating evidence, and motivating or teaching a patient. Inconsistency is not always the absence of the goal of consistency; rather, it can be a valuable trigger for further exploration in the realm of clinical medicine. The OntoAgent cognitive architecture, along with its extensive suite of knowledge resources an processors, is sufficient to support sophisticated agent functioning such as detecting clinically relevant inconsistencies and using them to benefit patient-centered medical training and practice. Copyright © 2012 Elsevier B.V. All rights reserved.

The use of artificially intelligent agents with bounded rationality in the study of economic markets

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

Rajan, V.; Slagle, J.R.

The concepts of {open_quote}knowledge{close_quote} and {open_quote}rationality{close_quote} are of central importance to fields of science that are interested in human behavior and learning, such as artificial intelligence, economics, and psychology. The similarity between artificial intelligence and economics - both are concerned with intelligent thought, rational behavior, and the use and acquisition of knowledge - has led to the use of economic models as a paradigm for solving problems in distributed artificial intelligence (DAI) and multi agent systems (MAS). What we propose is the opposite; the use of artificial intelligence in the study of economic markets. Over the centuries various theories ofmore » market behavior have been advanced. The prevailing theory holds that an asset`s current price converges to the risk adjusted value of the rationally expected dividend stream. While this rational expectations model holds in equilibrium or near-equilibrium conditions, it does not sufficiently explain conditions of market disequilibrium. An example of market disequilibrium is the phenomenon of a speculative bubble. We present an example of using artificially intelligent agents with bounded rationality in the study of speculative bubbles.« less

Swarm intelligence in humans: A perspective of emergent evolution

NASA Astrophysics Data System (ADS)

Tao, Yong

2018-07-01

The origin of intelligence has fascinated scientists for a long time. Over the past 100 years, many scholars have observed the connection between entropy and intelligence. In the present study, we investigated a potential origin of the swarm intelligence in humans. The present study shows that a competitive economy consisting of a large number of self-interested agents can be mapped to a Boltzmann-like system, where entropy and energy play roles of swarm intelligence and income, respectively. However, different from the physical entropy in the Boltzmann system, the entropy (or swarm intelligence) in the economic system is a self-referential variable, which may be a key characteristic for distinguishing between biological and physical systems. Furthermore, we employ the household income data from 66 countries and Hong Kong SAR to test the validity of the Boltzmann-like distribution. Remarkably, the empirical data are perfectly consistent with the theoretical results. This finding implies that the competitive behaviors among a colony of self-interested agents will spontaneously prompt the colony to evolve to a state of higher technological level, although each agent has no willingness to evolve.

A Multiagent Based Model for Tactical Planning

DTIC Science & Technology

2002-10-01

Pub. Co. 1985. [10] Castillo, J.M. Aproximación mediante procedimientos de Inteligencia Artificial al planeamiento táctico. Doctoral Thesis...been developed under the same conceptual model and using similar Artificial Intelligence Tools. We use four different stimulus/response agents in...The conceptual model is built on base of the Agents theory. To implement the different agents we have used Artificial Intelligence techniques such

Flexible, secure agent development framework

DOEpatents

Goldsmith,; Steven, Y [Rochester, MN

2009-04-07

While an agent generator is generating an intelligent agent, it can also evaluate the data processing platform on which it is executing, in order to assess a risk factor associated with operation of the agent generator on the data processing platform. The agent generator can retrieve from a location external to the data processing platform an open site that is configurable by the user, and load the open site into an agent substrate, thereby creating a development agent with code development capabilities. While an intelligent agent is executing a functional program on a data processing platform, it can also evaluate the data processing platform to assess a risk factor associated with performing the data processing function on the data processing platform.

Modeling intelligent agent beliefs in a card game scenario

NASA Astrophysics Data System (ADS)

Gołuński, Marcel; Tomanek, Roman; WÄ siewicz, Piotr

In this paper we explore the problem of intelligent agent beliefs. We model agent beliefs using multimodal logics of belief, KD45(m) system implemented as a directed graph depicting Kripke semantics, precisely. We present a card game engine application which allows multiple agents to connect to a given game session and play the card game. As an example simplified version of popular Saboteur card game is used. Implementation was done in Java language using following libraries and applications: Apache Mina, LWJGL.

Further Structural Intelligence for Sensors Cluster Technology in Manufacturing

PubMed Central

Mekid, Samir

2006-01-01

With the ever increasing complex sensing and actuating tasks in manufacturing plants, intelligent sensors cluster in hybrid networks becomes a rapidly expanding area. They play a dominant role in many fields from macro and micro scale. Global object control and the ability to self organize into fault-tolerant and scalable systems are expected for high level applications. In this paper, new structural concepts of intelligent sensors and networks with new intelligent agents are presented. Embedding new functionalities to dynamically manage cooperative agents for autonomous machines are interesting key enabling technologies most required in manufacturing for zero defects production.

Learning from Multiple Collaborating Intelligent Tutors: An Agent-based Approach.

ERIC Educational Resources Information Center

Solomos, Konstantinos; Avouris, Nikolaos

1999-01-01

Describes an open distributed multi-agent tutoring system (MATS) and discusses issues related to learning in such open environments. Topics include modeling a one student-many teachers approach in a computer-based learning context; distributed artificial intelligence; implementation issues; collaboration; and user interaction. (Author/LRW)

Autonomous Mission Operations for Sensor Webs

NASA Astrophysics Data System (ADS)

Underbrink, A.; Witt, K.; Stanley, J.; Mandl, D.

2008-12-01

We present interim results of a 2005 ROSES AIST project entitled, "Using Intelligent Agents to Form a Sensor Web for Autonomous Mission Operations", or SWAMO. The goal of the SWAMO project is to shift the control of spacecraft missions from a ground-based, centrally controlled architecture to a collaborative, distributed set of intelligent agents. The network of intelligent agents intends to reduce management requirements by utilizing model-based system prediction and autonomic model/agent collaboration. SWAMO agents are distributed throughout the Sensor Web environment, which may include multiple spacecraft, aircraft, ground systems, and ocean systems, as well as manned operations centers. The agents monitor and manage sensor platforms, Earth sensing systems, and Earth sensing models and processes. The SWAMO agents form a Sensor Web of agents via peer-to-peer coordination. Some of the intelligent agents are mobile and able to traverse between on-orbit and ground-based systems. Other agents in the network are responsible for encapsulating system models to perform prediction of future behavior of the modeled subsystems and components to which they are assigned. The software agents use semantic web technologies to enable improved information sharing among the operational entities of the Sensor Web. The semantics include ontological conceptualizations of the Sensor Web environment, plus conceptualizations of the SWAMO agents themselves. By conceptualizations of the agents, we mean knowledge of their state, operational capabilities, current operational capacities, Web Service search and discovery results, agent collaboration rules, etc. The need for ontological conceptualizations over the agents is to enable autonomous and autonomic operations of the Sensor Web. The SWAMO ontology enables automated decision making and responses to the dynamic Sensor Web environment and to end user science requests. The current ontology is compatible with Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) Sensor Model Language (SensorML) concepts and structures. The agents are currently deployed on the U.S. Naval Academy MidSTAR-1 satellite and are actively managing the power subsystem on-orbit without the need for human intervention.

Modeling Interactive Intelligences

DTIC Science & Technology

2002-08-01

given a task in an uncertain environment? How can we design it with that type of intelligence? How do we gauge the ludic capabilities of an agent? The...for play, unless they are playgrounds or have been designated as toys. Our non-artistic creations come with built-in purposes. Deviations from expected...uses are usually not welcomed. How could play enter into autonomous agent design ? What enhancement of the agent could it bring about? To think

Social Intelligence in a Human-Machine Collaboration System

NASA Astrophysics Data System (ADS)

Nakajima, Hiroshi; Morishima, Yasunori; Yamada, Ryota; Brave, Scott; Maldonado, Heidy; Nass, Clifford; Kawaji, Shigeyasu

In this information society of today, it is often argued that it is necessary to create a new way of human-machine interaction. In this paper, an agent with social response capabilities has been developed to achieve this goal. There are two kinds of information that is exchanged by two entities: objective and functional information (e.g., facts, requests, states of matters, etc.) and subjective information (e.g., feelings, sense of relationship, etc.). Traditional interactive systems have been designed to handle the former kind of information. In contrast, in this study social agents handling the latter type of information are presented. The current study focuses on sociality of the agent from the view point of Media Equation theory. This article discusses the definition, importance, and benefits of social intelligence as agent technology and argues that social intelligence has a potential to enhance the user's perception of the system, which in turn can lead to improvements of the system's performance. In order to implement social intelligence in the agent, a mind model has been developed to render affective expressions and personality of the agent. The mind model has been implemented in a human-machine collaborative learning system. One differentiating feature of the collaborative learning system is that it has an agent that performs as a co-learner with which the user interacts during the learning session. The mind model controls the social behaviors of the agent, thus making it possible for the user to have more social interactions with the agent. The experiment with the system suggested that a greater degree of learning was achieved when the students worked with the co-learner agent and that the co-learner agent with the mind model that expressed emotions resulted in a more positive attitude toward the system.

Intelligent Agents: Information Strategies for the Information Society.

ERIC Educational Resources Information Center

Garcia-Sierra, A. J.

In the workplace of today which is increasingly being overloaded with information, the concept of intelligent information agents has been widely prescribed. This paper briefly looks at the United Kingdom Government's Information Society Initiative which has been fueled by the realization that information is the key component of the ongoing…

A Multi-Agent System Approach for Distance Learning Architecture

ERIC Educational Resources Information Center

Turgay, Safiye

2005-01-01

The goal of this study is to suggest the agent systems by intelligence and adaptability properties in distance learning environment. The suggested system has flexible, agile, intelligence and cooperation features. System components are teachers, students (learners), and resources. Inter component relations are modeled and reviewed by using the…

Autonomous Agents and Intelligent Assistants for Exploration Operations

NASA Technical Reports Server (NTRS)

Malin, Jane T.

2000-01-01

Human exploration of space will involve remote autonomous crew and systems in long missions. Data to earth will be delayed and limited. Earth control centers will not receive continuous real-time telemetry data, and there will be communication round trips of up to one hour. There will be reduced human monitoring on the planet and earth. When crews are present on the planet, they will be occupied with other activities, and system management will be a low priority task. Earth control centers will use multi-tasking "night shift" and on-call specialists. A new project at Johnson Space Center is developing software to support teamwork between distributed human and software agents in future interplanetary work environments. The Engineering and Mission Operations Directorates at Johnson Space Center (JSC) are combining laboratories and expertise to carry out this project, by establishing a testbed for hWl1an centered design, development and evaluation of intelligent autonomous and assistant systems. Intelligent autonomous systems for managing systems on planetary bases will commuicate their knowledge to support distributed multi-agent mixed-initiative operations. Intelligent assistant agents will respond to events by developing briefings and responses according to instructions from human agents on earth and in space.

An Application of Artificial Intelligence to the Implementation of Electronic Commerce

NASA Astrophysics Data System (ADS)

Srivastava, Anoop Kumar

In this paper, we present an application of Artificial Intelligence (AI) to the implementation of Electronic Commerce. We provide a multi autonomous agent based framework. Our agent based architecture leads to flexible design of a spectrum of multiagent system (MAS) by distributing computation and by providing a unified interface to data and programs. Autonomous agents are intelligent enough and provide autonomy, simplicity of communication, computation, and a well developed semantics. The steps of design and implementation are discussed in depth, structure of Electronic Marketplace, an ontology, the agent model, and interaction pattern between agents is given. We have developed mechanisms for coordination between agents using a language, which is called Virtual Enterprise Modeling Language (VEML). VEML is a integration of Java and Knowledge Query and Manipulation Language (KQML). VEML provides application programmers with potential to globally develop different kinds of MAS based on their requirements and applications. We have implemented a multi autonomous agent based system called VE System. We demonstrate efficacy of our system by discussing experimental results and its salient features.

Combining human and machine intelligence to derive agents' behavioral rules for groundwater irrigation

NASA Astrophysics Data System (ADS)

Hu, Yao; Quinn, Christopher J.; Cai, Ximing; Garfinkle, Noah W.

2017-11-01

For agent-based modeling, the major challenges in deriving agents' behavioral rules arise from agents' bounded rationality and data scarcity. This study proposes a "gray box" approach to address the challenge by incorporating expert domain knowledge (i.e., human intelligence) with machine learning techniques (i.e., machine intelligence). Specifically, we propose using directed information graph (DIG), boosted regression trees (BRT), and domain knowledge to infer causal factors and identify behavioral rules from data. A case study is conducted to investigate farmers' pumping behavior in the Midwest, U.S.A. Results show that four factors identified by the DIG algorithm- corn price, underlying groundwater level, monthly mean temperature and precipitation- have main causal influences on agents' decisions on monthly groundwater irrigation depth. The agent-based model is then developed based on the behavioral rules represented by three DIGs and modeled by BRTs, and coupled with a physically-based groundwater model to investigate the impacts of agents' pumping behavior on the underlying groundwater system in the context of coupled human and environmental systems.

Intelligence-Driven Border Security: A Promethean View of U.S. Border Patrol Intelligence Operations

DTIC Science & Technology

2015-12-01

USBP agent, intelligence ( BPA -I), information sharing, capability gap analysis process (CGAP), Tucson Sector Red Team 15. NUMBER OF PAGES 109 16...27 2. BPA -I .............................................................................................28 3. BPA -I Requirements...71 APPENDIX A. PROFESSIONAL INTELLIGENCE ASSOCIATIONS— ADDITIONAL OPPORTUNITIES FOR BPA -IS

Design and Implementation of an Intelligent Virtual Environment for Improving Speaking and Listening Skills

ERIC Educational Resources Information Center

Hassani, Kaveh; Nahvi, Ali; Ahmadi, Ali

2016-01-01

In this paper, we present an intelligent architecture, called intelligent virtual environment for language learning, with embedded pedagogical agents for improving listening and speaking skills of non-native English language learners. The proposed architecture integrates virtual environments into the Intelligent Computer-Assisted Language…

The Secret Air War Over France USAAF Special Operations Units in the French Campaign of 1944

DTIC Science & Technology

1992-05-01

Branch, or SI, and its Special Operations Branch, known as SO. The Secret Intelligence Branch was responsible for collecting foreign intelligence...infiltrating its own intelligence agents into France. The Secret Intelligence Branch staff in London (SI/London) began planning for joint operations

Working with Pedagogical Agents: Understanding the "Back End" of an Intelligent Tutoring System

ERIC Educational Resources Information Center

Wolfe, Christopher; Widmer, Colin L.; Weil, Audrey M.; Cedillos-Whynott, Elizabeth M.

2015-01-01

Students in an undergraduate psychology course on Learning and Cognition used SKO (formerly AutoTutor Lite), an Intelligent Tutoring System, to create interactive lessons in which a pedagogic agent (animated avatar) engages users in a tutorial dialogue. After briefly describing the technology and underlying psychological theory, data from an…

Multiagent pursuit-evasion games: Algorithms and experiments

NASA Astrophysics Data System (ADS)

Kim, Hyounjin

Deployment of intelligent agents has been made possible through advances in control software, microprocessors, sensor/actuator technology, communication technology, and artificial intelligence. Intelligent agents now play important roles in many applications where human operation is too dangerous or inefficient. There is little doubt that the world of the future will be filled with intelligent robotic agents employed to autonomously perform tasks, or embedded in systems all around us, extending our capabilities to perceive, reason and act, and replacing human efforts. There are numerous real-world applications in which a single autonomous agent is not suitable and multiple agents are required. However, after years of active research in multi-agent systems, current technology is still far from achieving many of these real-world applications. Here, we consider the problem of deploying a team of unmanned ground vehicles (UGV) and unmanned aerial vehicles (UAV) to pursue a second team of UGV evaders while concurrently building a map in an unknown environment. This pursuit-evasion game encompasses many of the challenging issues that arise in operations using intelligent multi-agent systems. We cast the problem in a probabilistic game theoretic framework and consider two computationally feasible pursuit policies: greedy and global-max. We also formulate this probabilistic pursuit-evasion game as a partially observable Markov decision process and employ a policy search algorithm to obtain a good pursuit policy from a restricted class of policies. The estimated value of this policy is guaranteed to be uniformly close to the optimal value in the given policy class under mild conditions. To implement this scenario on real UAVs and UGVs, we propose a distributed hierarchical hybrid system architecture which emphasizes the autonomy of each agent yet allows for coordinated team efforts. We then describe our implementation on a fleet of UGVs and UAVs, detailing components such as high level pursuit policy computation, inter-agent communication, navigation, sensing, and regulation. We present both simulation and experimental results on real pursuit-evasion games between our fleet of UAVs and UGVs and evaluate the pursuit policies, relating expected capture times to the speed and intelligence of the evaders and the sensing capabilities of the pursuers. The architecture and algorithmsis described in this dissertation are general enough to be applied to many real-world applications.

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

Mission Profiles and Evidential Reasoning for Estimating Information Relevancy in Multi-Agent Supervisory Control Applications

DTIC Science & Technology

2010-06-01

artificial agents, their limited scope and singular purpose lead us to believe that human-machine trust will be very portable. That is, if one operator... Artificial Intelligence Review 2(2), 1988. [E88] M.R. Endsley. Situation awareness global assessment technique (SAGAT). In Proceedings of the National...1995. [F98] J. Ferber, Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence, Addison- Wesley, 1998. [NP01] I. Niles and A

Behavior believability in virtual worlds: agents acting when they need to.

PubMed

Avradinis, Nikos; Panayiotopoulos, Themis; Anastassakis, George

2013-12-01

Believability has been a perennial goal for the intelligent virtual agent community. One important aspect of believability largely consists in demonstrating autonomous behavior, consistent with the agent's personality and motivational state, as well as the world conditions. Autonomy, on behalf of the agent, implies the existence of an internal structure and mechanism that allows the agent to have its own needs and interests, based on which the agent will dynamically select and generate goals that will in turn lead to self-determined behavior. Intrinsic motivation allows the agent to function and demonstrate behavior, even when no external stimulus is present, due to the constant change of its internal emotional and physiological state. The concept of motivation has already been investigated by research works on intelligent agents, trying to achieve autonomy. The current work presents an architecture and model to represent and manage internal driving factors in intelligent virtual agents, using the concept of motivations. Based on Maslow and Alderfer's bio-psychological needs theories, we present a motivational approach to represent human needs and produce emergent behavior through motivation synthesis. Particular attention is given to basic, physiological level needs, which are the basis of behavior and can produce tendency to action even when there is no other interaction with the environment.

Application of online measures to monitor and evaluate multiplatform fusion performance

NASA Astrophysics Data System (ADS)

Stubberud, Stephen C.; Kowalski, Charlene; Klamer, Dale M.

1999-07-01

A primary concern of multiplatform data fusion is assessing the quality and utility of data shared among platforms. Constraints such as platform and sensor capability and task load necessitate development of an on-line system that computes a metric to determine which other platform can provide the best data for processing. To determine data quality, we are implementing an approach based on entropy coupled with intelligent agents. To determine data quality, we are implementing an approach based on entropy coupled with intelligent agents. Entropy measures quality of processed information such as localization, classification, and ambiguity in measurement-to-track association. Lower entropy scores imply less uncertainty about a particular target. When new information is provided, we compuete the level of improvement a particular track obtains from one measurement to another. The measure permits us to evaluate the utility of the new information. We couple entropy with intelligent agents that provide two main data gathering functions: estimation of another platform's performance and evaluation of the new measurement data's quality. Both functions result from the entropy metric. The intelligent agent on a platform makes an estimate of another platform's measurement and provides it to its own fusion system, which can then incorporate it, for a particular target. A resulting entropy measure is then calculated and returned to its own agent. From this metric, the agent determines a perceived value of the offboard platform's measurement. If the value is satisfactory, the agent requests the measurement from the other platform, usually by interacting with the other platform's agent. Once the actual measurement is received, again entropy is computed and the agent assesses its estimation process and refines it accordingly.

Artificial intelligence and the future.

PubMed

Clocksin, William F

2003-08-15

We consider some of the ideas influencing current artificial-intelligence research and outline an alternative conceptual framework that gives priority to social relationships as a key component and constructor of intelligent behaviour. The framework starts from Weizenbaum's observation that intelligence manifests itself only relative to specific social and cultural contexts. This is in contrast to a prevailing view, which sees intelligence as an abstract capability of the individual mind based on a mechanism for rational thought. The new approach is not based on the conventional idea that the mind is a rational processor of symbolic information, nor does it require the idea that thought is a kind of abstract problem solving with a semantics that is independent of its embodiment. Instead, priority is given to affective and social responses that serve to engage the whole agent in the life of the communities in which it participates. Intelligence is seen not as the deployment of capabilities for problem solving, but as constructed by the continual, ever-changing and unfinished engagement with the social group within the environment. The construction of the identity of the intelligent agent involves the appropriation or 'taking up' of positions within the conversations and narratives in which it participates. Thus, the new approach argues that the intelligent agent is shaped by the meaning ascribed to experience, by its situation in the social matrix, and by practices of self and of relationship into which intelligent life is recruited. This has implications for the technology of the future, as, for example, classic artificial intelligence models such as goal-directed problem solving are seen as special cases of narrative practices instead of as ontological foundations.

Videos | Argonne National Laboratory

Science.gov Websites

science --Agent-based modeling --Applied mathematics --Artificial intelligence --Cloud computing management -Intelligence & counterterrorrism -Vulnerability assessment -Sensors & detectors Programs

The Time Factor: Leveraging Intelligent Agents and Directed Narratives in Online Learning Environments

ERIC Educational Resources Information Center

Jones, Greg; Warren, Scott

2009-01-01

Using video games, virtual simulations, and other digital spaces for learning can be a time-consuming process; aside from technical issues that may absorb class time, students take longer to achieve gains in learning in virtual environments. Greg Jones and Scott Warren describe how intelligent agents, in-game characters that respond to the context…

Ambient agents: embedded agents for remote control and monitoring using the PANGEA platform.

PubMed

Villarrubia, Gabriel; De Paz, Juan F; Bajo, Javier; Corchado, Juan M

2014-07-31

Ambient intelligence has advanced significantly during the last few years. The incorporation of image processing and artificial intelligence techniques have opened the possibility for such aspects as pattern recognition, thus allowing for a better adaptation of these systems. This study presents a new model of an embedded agent especially designed to be implemented in sensing devices with resource constraints. This new model of an agent is integrated within the PANGEA (Platform for the Automatic Construction of Organiztions of Intelligent Agents) platform, an organizational-based platform, defining a new sensor role in the system and aimed at providing contextual information and interacting with the environment. A case study was developed over the PANGEA platform and designed using different agents and sensors responsible for providing user support at home in the event of incidents or emergencies. The system presented in the case study incorporates agents in Arduino hardware devices with recognition modules and illuminated bands; it also incorporates IP cameras programmed for automatic tracking, which can connect remotely in the event of emergencies. The user wears a bracelet, which contains a simple vibration sensor that can receive notifications about the emergency situation.

Ambient Agents: Embedded Agents for Remote Control and Monitoring Using the PANGEA Platform

PubMed Central

Villarrubia, Gabriel; De Paz, Juan F.; Bajo, Javier; Corchado, Juan M.

2014-01-01

Ambient intelligence has advanced significantly during the last few years. The incorporation of image processing and artificial intelligence techniques have opened the possibility for such aspects as pattern recognition, thus allowing for a better adaptation of these systems. This study presents a new model of an embedded agent especially designed to be implemented in sensing devices with resource constraints. This new model of an agent is integrated within the PANGEA (Platform for the Automatic Construction of Organiztions of Intelligent Agents) platform, an organizational-based platform, defining a new sensor role in the system and aimed at providing contextual information and interacting with the environment. A case study was developed over the PANGEA platform and designed using different agents and sensors responsible for providing user support at home in the event of incidents or emergencies. The system presented in the case study incorporates agents in Arduino hardware devices with recognition modules and illuminated bands; it also incorporates IP cameras programmed for automatic tracking, which can connect remotely in the event of emergencies. The user wears a bracelet, which contains a simple vibration sensor that can receive notifications about the emergency situation. PMID:25090416

On the use of multi-agent systems for the monitoring of industrial systems

NASA Astrophysics Data System (ADS)

Rezki, Nafissa; Kazar, Okba; Mouss, Leila Hayet; Kahloul, Laid; Rezki, Djamil

2016-03-01

The objective of the current paper is to present an intelligent system for complex process monitoring, based on artificial intelligence technologies. This system aims to realize with success all the complex process monitoring tasks that are: detection, diagnosis, identification and reconfiguration. For this purpose, the development of a multi-agent system that combines multiple intelligences such as: multivariate control charts, neural networks, Bayesian networks and expert systems has became a necessity. The proposed system is evaluated in the monitoring of the complex process Tennessee Eastman process.

Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017 Workshop by the North Atlantic Treaty Organization (NATO) Research Group IST-152 RTG

DTIC Science & Technology

2018-04-18

Significant research is currently conducted on dynamic learning and threat detection. However, this work is held back by gaps in validation methods ...and network path rotation (e.g., Stream Splitting MTD). Agents can also employ various cyber-deception methods , including direct observation hiding...ARL-SR-0395 ● APR 2018 US Army Research Laboratory Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017

Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017 Workshop by the North Atlantic Treaty Organization (NATO) Research Group IST-152-RTG

DTIC Science & Technology

2018-04-01

Significant research is currently conducted on dynamic learning and threat detection. However, this work is held back by gaps in validation methods ...and network path rotation (e.g., Stream Splitting MTD). Agents can also employ various cyber-deception methods , including direct observation hiding...ARL-SR-0395 ● APR 2018 US Army Research Laboratory Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017

78 FR 962 - Agency Information Collection Activities

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-07

... OFFICE OF THE DIRECTOR OF NATIONAL INTELLIGENCE Agency Information Collection Activities AGENCY: Office of the Director of National Intelligence (ODNI). ACTION: Notice. SUMMARY: In December 2011, the... responsibilities assigned to the Director of National Intelligence (DNI) as Security Executive Agent. Accordingly...

Intelligence, Information Technology, and Information Warfare.

ERIC Educational Resources Information Center

Davies, Philip H. J.

2002-01-01

Addresses the use of information technology for intelligence and information warfare in the context of national security and reviews the status of clandestine collection. Discusses hacking, human agent collection, signal interception, covert action, counterintelligence and security, and communications between intelligence producers and consumers…

Combining Human and Machine Intelligence to Derive Agents' Behavioral Rules for Groundwater Irrigation

NASA Astrophysics Data System (ADS)

Hu, Y.; Quinn, C.; Cai, X.

2015-12-01

One major challenge of agent-based modeling is to derive agents' behavioral rules due to behavioral uncertainty and data scarcity. This study proposes a new approach to combine a data-driven modeling based on the directed information (i.e., machine intelligence) with expert domain knowledge (i.e., human intelligence) to derive the behavioral rules of agents considering behavioral uncertainty. A directed information graph algorithm is applied to identifying the causal relationships between agents' decisions (i.e., groundwater irrigation depth) and time-series of environmental, socio-economical and institutional factors. A case study is conducted for the High Plains aquifer hydrological observatory (HO) area, U.S. Preliminary results show that four factors, corn price (CP), underlying groundwater level (GWL), monthly mean temperature (T) and precipitation (P) have causal influences on agents' decisions on groundwater irrigation depth (GWID) to various extents. Based on the similarity of the directed information graph for each agent, five clusters of graphs are further identified to represent all the agents' behaviors in the study area as shown in Figure 1. Using these five representative graphs, agents' monthly optimal groundwater pumping rates are derived through the probabilistic inference. Such data-driven relationships and probabilistic quantifications are then coupled with a physically-based groundwater model to investigate the interactions between agents' pumping behaviors and the underlying groundwater system in the context of coupled human and natural systems.

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.

Intelligent Agent Appropriation in the Tracking Phase of an Environmental Scanning Process: A Case Study of a French Trade Union

ERIC Educational Resources Information Center

Lafaye, Christophe

2009-01-01

Introduction: The rapid growth of the Internet has modified the boundaries of information acquisition (tracking) in environmental scanning. Despite the numerous advantages of this new medium, information overload is an enormous problem for Internet scanners. In order to help them, intelligent agents (i.e., autonomous, automated software agents…

Computing architecture for autonomous microgrids

DOEpatents

Goldsmith, Steven Y.

2015-09-29

A computing architecture that facilitates autonomously controlling operations of a microgrid is described herein. A microgrid network includes numerous computing devices that execute intelligent agents, each of which is assigned to a particular entity (load, source, storage device, or switch) in the microgrid. The intelligent agents can execute in accordance with predefined protocols to collectively perform computations that facilitate uninterrupted control of the .

Human-directed local autonomy for motion guidance and coordination in an intelligent manufacturing system

NASA Astrophysics Data System (ADS)

Alford, W. A.; Kawamura, Kazuhiko; Wilkes, Don M.

1997-12-01

This paper discusses the problem of integrating human intelligence and skills into an intelligent manufacturing system. Our center has jointed the Holonic Manufacturing Systems (HMS) Project, an international consortium dedicated to developing holonic systems technologies. One of our contributions to this effort is in Work Package 6: flexible human integration. This paper focuses on one activity, namely, human integration into motion guidance and coordination. Much research on intelligent systems focuses on creating totally autonomous agents. At the Center for Intelligent Systems (CIS), we design robots that interact directly with a human user. We focus on using the natural intelligence of the user to simplify the design of a robotic system. The problem is finding ways for the user to interact with the robot that are efficient and comfortable for the user. Manufacturing applications impose the additional constraint that the manufacturing process should not be disturbed; that is, frequent interacting with the user could degrade real-time performance. Our research in human-robot interaction is based on a concept called human directed local autonomy (HuDL). Under this paradigm, the intelligent agent selects and executes a behavior or skill, based upon directions from a human user. The user interacts with the robot via speech, gestures, or other media. Our control software is based on the intelligent machine architecture (IMA), an object-oriented architecture which facilitates cooperation and communication among intelligent agents. In this paper we describe our research testbed, a dual-arm humanoid robot and human user, and the use of this testbed for a human directed sorting task. We also discuss some proposed experiments for evaluating the integration of the human into the robot system. At the time of this writing, the experiments have not been completed.

The Strategic Partners Network's Extraction: The XStrat.Net Project

NASA Astrophysics Data System (ADS)

Taifi, Nouha; Passiante, Giuseppina

The firms in the business environment have to choose adequate partners in order to sustain their competitive advantage and their economic performance. Plus, the creation of special communities consisting of these partners is essential for the life-long development of these latter and the firms creating them. The research project XStrat.Net aims at the identification of factors and indicators about the organizations for the modelling of intelligent agents -XStrat intelligent agents- and the engineering of a software -XStrat- to process these backbones intelligent agents. Through the use of the software, the firms will be able to select the needed partners for the creation of special communities for the purpose of learning, interest or innovation. The XStrat.Net project also intends to provide guidelines for the creation of the special communities.

78 FR 5504 - Agency Information Collection Activities: Extension of Information Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-25

... OFFICE OF THE DIRECTOR OF NATIONAL INTELLIGENCE Agency Information Collection Activities: Extension of Information Collection; Comment Request AGENCY: Office of the Director of National Intelligence... Intelligence (DNI) as Security Executive Agent. Accordingly, ODNI is giving public notice regarding extension...

Building an adaptive agent to monitor and repair the electrical power system of an orbital satellite

NASA Technical Reports Server (NTRS)

Tecuci, Gheorghe; Hieb, Michael R.; Dybala, Tomasz

1995-01-01

Over several years we have developed a multistrategy apprenticeship learning methodology for building knowledge-based systems. Recently we have developed and applied our methodology to building intelligent agents. This methodology allows a subject matter expert to build an agent in the same way in which the expert would teach a human apprentice. The expert will give the agent specific examples of problems and solutions, explanations of these solutions, or supervise the agent as it solves new problems. During such interactions, the agent learns general rules and concepts, continuously extending and improving its knowledge base. In this paper we present initial results on applying this methodology to build an intelligent adaptive agent for monitoring and repair of the electrical power system of an orbital satellite, stressing the interaction with the expert during apprenticeship learning.

The achievement of spacecraft autonomy through the thematic application of multiple cooperating intelligent agents

NASA Technical Reports Server (NTRS)

Rossomando, Philip J.

1992-01-01

A description is given of UNICORN, a prototype system developed for the purpose of investigating artificial intelligence (AI) concepts supporting spacecraft autonomy. UNICORN employs thematic reasoning, of the type first described by Rodger Schank of Northwestern University, to allow the context-sensitive control of multiple intelligent agents within a blackboard based environment. In its domain of application, UNICORN demonstrates the ability to reason teleologically with focused knowledge. Also presented are some of the lessons learned as a result of this effort. These lessons apply to any effort wherein system level autonomy is the objective.

Swarm Intelligence Optimization and Its Applications

NASA Astrophysics Data System (ADS)

Ding, Caichang; Lu, Lu; Liu, Yuanchao; Peng, Wenxiu

Swarm Intelligence is a computational and behavioral metaphor for solving distributed problems inspired from biological examples provided by social insects such as ants, termites, bees, and wasps and by swarm, herd, flock, and shoal phenomena in vertebrates such as fish shoals and bird flocks. An example of successful research direction in Swarm Intelligence is ant colony optimization (ACO), which focuses on combinatorial optimization problems. Ant algorithms can be viewed as multi-agent systems (ant colony), where agents (individual ants) solve required tasks through cooperation in the same way that ants create complex social behavior from the combined efforts of individuals.

Coordinating complex problem-solving among distributed intelligent agents

NASA Technical Reports Server (NTRS)

Adler, Richard M.

1992-01-01

A process-oriented control model is described for distributed problem solving. The model coordinates the transfer and manipulation of information across independent networked applications, both intelligent and conventional. The model was implemented using SOCIAL, a set of object-oriented tools for distributing computing. Complex sequences of distributed tasks are specified in terms of high level scripts. Scripts are executed by SOCIAL objects called Manager Agents, which realize an intelligent coordination model that routes individual tasks to suitable server applications across the network. These tools are illustrated in a prototype distributed system for decision support of ground operations for NASA's Space Shuttle fleet.

Behavioral biometrics for verification and recognition of malicious software agents

NASA Astrophysics Data System (ADS)

Yampolskiy, Roman V.; Govindaraju, Venu

2008-04-01

Homeland security requires technologies capable of positive and reliable identification of humans for law enforcement, government, and commercial applications. As artificially intelligent agents improve in their abilities and become a part of our everyday life, the possibility of using such programs for undermining homeland security increases. Virtual assistants, shopping bots, and game playing programs are used daily by millions of people. We propose applying statistical behavior modeling techniques developed by us for recognition of humans to the identification and verification of intelligent and potentially malicious software agents. Our experimental results demonstrate feasibility of such methods for both artificial agent verification and even for recognition purposes.

HERA: A New Platform for Embedding Agents in Heterogeneous Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Alonso, Ricardo S.; de Paz, Juan F.; García, Óscar; Gil, Óscar; González, Angélica

Ambient Intelligence (AmI) based systems require the development of innovative solutions that integrate distributed intelligent systems with context-aware technologies. In this sense, Multi-Agent Systems (MAS) and Wireless Sensor Networks (WSN) are two key technologies for developing distributed systems based on AmI scenarios. This paper presents the new HERA (Hardware-Embedded Reactive Agents) platform, that allows using dynamic and self-adaptable heterogeneous WSNs on which agents are directly embedded on the wireless nodes This approach facilitates the inclusion of context-aware capabilities in AmI systems to gather data from their surrounding environments, achieving a higher level of ubiquitous and pervasive computing.

An Analysis on a Negotiation Model Based on Multiagent Systems with Symbiotic Learning and Evolution

NASA Astrophysics Data System (ADS)

Hossain, Md. Tofazzal

This study explores an evolutionary analysis on a negotiation model based on Masbiole (Multiagent Systems with Symbiotic Learning and Evolution) which has been proposed as a new methodology of Multiagent Systems (MAS) based on symbiosis in the ecosystem. In Masbiole, agents evolve in consideration of not only their own benefits and losses, but also the benefits and losses of opponent agents. To aid effective application of Masbiole, we develop a competitive negotiation model where rigorous and advanced intelligent decision-making mechanisms are required for agents to achieve solutions. A Negotiation Protocol is devised aiming at developing a set of rules for agents' behavior during evolution. Simulations use a newly developed evolutionary computing technique, called Genetic Network Programming (GNP) which has the directed graph-type gene structure that can develop and design the required intelligent mechanisms for agents. In a typical scenario, competitive negotiation solutions are reached by concessions that are usually predetermined in the conventional MAS. In this model, however, not only concession is determined automatically by symbiotic evolution (making the system intelligent, automated, and efficient) but the solution also achieves Pareto optimal automatically.

Measuring the Performance and Intelligence of Systems: Proceedings of the 2002 PerMIS Workshop

NASA Technical Reports Server (NTRS)

Messina, E. R.; Meystel, A. M.

2002-01-01

Contents include the following: Performance Metrics; Performance of Multiple Agents; Performance of Mobility Systems; Performance of Planning Systems; General Discussion Panel 1; Uncertainty of Representation I; Performance of Robots in Hazardous Domains; Modeling Intelligence; Modeling of Mind; Measuring Intelligence; Grouping: A Core Procedure of Intelligence; Uncertainty in Representation II; Towards Universal Planning/Control Systems.

A hierarchical distributed control model for coordinating intelligent systems

NASA Technical Reports Server (NTRS)

Adler, Richard M.

1991-01-01

A hierarchical distributed control (HDC) model for coordinating cooperative problem-solving among intelligent systems is described. The model was implemented using SOCIAL, an innovative object-oriented tool for integrating heterogeneous, distributed software systems. SOCIAL embeds applications in 'wrapper' objects called Agents, which supply predefined capabilities for distributed communication, control, data specification, and translation. The HDC model is realized in SOCIAL as a 'Manager'Agent that coordinates interactions among application Agents. The HDC Manager: indexes the capabilities of application Agents; routes request messages to suitable server Agents; and stores results in a commonly accessible 'Bulletin-Board'. This centralized control model is illustrated in a fault diagnosis application for launch operations support of the Space Shuttle fleet at NASA, Kennedy Space Center.

A framework for intelligent data acquisition and real-time database searching for shotgun proteomics.

PubMed

Graumann, Johannes; Scheltema, Richard A; Zhang, Yong; Cox, Jürgen; Mann, Matthias

2012-03-01

In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides "on-the-fly" within 30 ms, well within the time constraints of a shotgun fragmentation "topN" method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available.

A Framework for Intelligent Data Acquisition and Real-Time Database Searching for Shotgun Proteomics*

PubMed Central

Graumann, Johannes; Scheltema, Richard A.; Zhang, Yong; Cox, Jürgen; Mann, Matthias

2012-01-01

In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides “on-the-fly” within 30 ms, well within the time constraints of a shotgun fragmentation “topN” method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available. PMID:22171319

Intelligent Counseling System: A 24 x 7 Academic Advisor

ERIC Educational Resources Information Center

Leung, Chun Ming; Tsang, Eva Y. M.; Lam, S. S.; Pang, Dominic C. W.

2010-01-01

Universities are increasingly looking into self-service systems with intelligent digital agents to supplement or replace labor-intensive services, such as academic counseling. The Open University of Hong Kong has developed an intelligent online system that instantly responds to enquiries about career development, learning modes, program/course…

What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated.

PubMed

Kumaran, Dharshan; Hassabis, Demis; McClelland, James L

2016-07-01

We update complementary learning systems (CLS) theory, which holds that intelligent agents must possess two learning systems, instantiated in mammalians in neocortex and hippocampus. The first gradually acquires structured knowledge representations while the second quickly learns the specifics of individual experiences. We broaden the role of replay of hippocampal memories in the theory, noting that replay allows goal-dependent weighting of experience statistics. We also address recent challenges to the theory and extend it by showing that recurrent activation of hippocampal traces can support some forms of generalization and that neocortical learning can be rapid for information that is consistent with known structure. Finally, we note the relevance of the theory to the design of artificial intelligent agents, highlighting connections between neuroscience and machine learning. Copyright © 2016 Elsevier Ltd. All rights reserved.

Student Modeling in an Intelligent Tutoring System

DTIC Science & Technology

1996-12-17

Multi-Agent Architecture." Advances in Artificial Intelligence : Proceedings of the 12 th Brazilian Symposium on Aritificial Intelligence , edited by...STUDENT MODELING IN AN INTELLIGENT TUTORING SYSTEM THESIS Jeremy E. Thompson Captain, USAF AFIT/GCS/ENG/96D-27 DIMTVMON* fCKAJWINT A Appr"v*d t=i...Air Force Base, Ohio AFIT/GCS/ENG/96D-27 STUDENT MODELING IN AN INTELLIGENT TUTORING SYSTEM THESIS Jeremy E. Thompson Captain, USAF AFIT/GCS/ENG/96D

Distinct Neurocognitive Strategies for Comprehensions of Human and Artificial Intelligence

PubMed Central

Ge, Jianqiao; Han, Shihui

2008-01-01

Although humans have inevitably interacted with both human and artificial intelligence in real life situations, it is unknown whether the human brain engages homologous neurocognitive strategies to cope with both forms of intelligence. To investigate this, we scanned subjects, using functional MRI, while they inferred the reasoning processes conducted by human agents or by computers. We found that the inference of reasoning processes conducted by human agents but not by computers induced increased activity in the precuneus but decreased activity in the ventral medial prefrontal cortex and enhanced functional connectivity between the two brain areas. The findings provide evidence for distinct neurocognitive strategies of taking others' perspective and inhibiting the process referenced to the self that are specific to the comprehension of human intelligence. PMID:18665211

Integrating CLIPS applications into heterogeneous distributed systems

NASA Technical Reports Server (NTRS)

Adler, Richard M.

1991-01-01

SOCIAL is an advanced, object-oriented development tool for integrating intelligent and conventional applications across heterogeneous hardware and software platforms. SOCIAL defines a family of 'wrapper' objects called agents, which incorporate predefined capabilities for distributed communication and control. Developers embed applications within agents and establish interactions between distributed agents via non-intrusive message-based interfaces. This paper describes a predefined SOCIAL agent that is specialized for integrating C Language Integrated Production System (CLIPS)-based applications. The agent's high-level Application Programming Interface supports bidirectional flow of data, knowledge, and commands to other agents, enabling CLIPS applications to initiate interactions autonomously, and respond to requests and results from heterogeneous remote systems. The design and operation of CLIPS agents are illustrated with two distributed applications that integrate CLIPS-based expert systems with other intelligent systems for isolating and mapping problems in the Space Shuttle Launch Processing System at the NASA Kennedy Space Center.

Innovating the Standard Procurement System Utilizing Intelligent Agent Technologies

DTIC Science & Technology

1999-12-01

36 C. STANDARD PROCUREMENT SYSTEM 36 1. OVERVIEW 36 2. SPS FUNCTIONS , 37 3. SPS ADVANTAGES 39 4. SPS DISADVANTAGES 40 5. SPS SUMMARY 41 D...PROCUREMENT PROCESS INNOVATION RESULTS ’. 52 E. INTELLIGENT AGENT (IA) TECHNOLOGY 53 1. OVERVIEW 54 viii 2. ADVANTAGES 58 3. DISADVANTAGES 58 F...Electronic Mall (EMALL), GSA Advantage , etc. • Web invoicing Electronic Funds Transfer (EFT) • • International Merchant Purchase Authorization Card (IMPAC

An Intelligent Active Video Surveillance System Based on the Integration of Virtual Neural Sensors and BDI Agents

NASA Astrophysics Data System (ADS)

Gregorio, Massimo De

In this paper we present an intelligent active video surveillance system currently adopted in two different application domains: railway tunnels and outdoor storage areas. The system takes advantages of the integration of Artificial Neural Networks (ANN) and symbolic Artificial Intelligence (AI). This hybrid system is formed by virtual neural sensors (implemented as WiSARD-like systems) and BDI agents. The coupling of virtual neural sensors with symbolic reasoning for interpreting their outputs, makes this approach both very light from a computational and hardware point of view, and rather robust in performances. The system works on different scenarios and in difficult light conditions.

A Systematic Literature Review of Agents Applied in Healthcare.

PubMed

Isern, David; Moreno, Antonio

2016-02-01

Intelligent agents and healthcare have been intimately linked in the last years. The intrinsic complexity and diversity of care can be tackled with the flexibility, dynamics and reliability of multi-agent systems. The purpose of this review is to show the feasibility of applying intelligent agents in the healthcare domain and use the findings to provide a discussion of current trends and devise future research directions. A review of the most recent literature (2009-2014) of applications of agents in healthcare is discussed, and two classifications considering the main goal of the health systems as well as the main actors involved have been investigated. This review shows that the number of published works exhibits a growing interest of researchers in this field in a wide range of applications.

A multi-agent approach to intelligent monitoring in smart grids

NASA Astrophysics Data System (ADS)

Vallejo, D.; Albusac, J.; Glez-Morcillo, C.; Castro-Schez, J. J.; Jiménez, L.

2014-04-01

In this paper, we propose a scalable multi-agent architecture to give support to smart grids, paying special attention to the intelligent monitoring of distribution substations. The data gathered by multiple sensors are used by software agents that are responsible for monitoring different aspects or events of interest, such as normal voltage values or unbalanced intensity values that can end up blowing fuses and decreasing the quality of service of end consumers. The knowledge bases of these agents have been built by means of a formal model for normality analysis that has been successfully used in other surveillance domains. The architecture facilitates the integration of new agents and can be easily configured and deployed to monitor different environments. The experiments have been conducted over a power distribution network.

The Reactive-Causal Architecture: Introducing an Emotion Model along with Theories of Needs

NASA Astrophysics Data System (ADS)

Aydin, Ali Orhan; Orgun, Mehmet Ali

In the entertainment application area, one of the major aims is to develop believable agents. To achieve this aim, agents should be highly autonomous, situated, flexible, and display affect. The Reactive-Causal Architecture (ReCau) is proposed to simulate these core attributes. In its current form, ReCau cannot explain the effects of emotions on intelligent behaviour. This study aims is to further improve the emotion model of ReCau to explain the effects of emotions on intelligent behaviour. This improvement allows ReCau to be emotional to support the development of believable agents.

Developing Realistic Behaviors in Adversarial Agents for Air Combat Simulation

DTIC Science & Technology

1993-12-01

34Building Symbolic Primitives with Continuous Control Rou- tines." Proceedings of the 1st International Conference on Aritificial Intelligence Planning...shortcoming is the minimal Air Force participation in this field. 1-1 Some of the artificial intelligence (AI) personnel at the Air Force Institute of... intelligent system that operates in a moderately complex or unpredictable environment must be reactive. In being reactive the intelligent system must

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

NASA Astrophysics Data System (ADS)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land use change. Finally, the major contributions to the science are presented along with valuable directions for future research.

Application and Implications of Agent Technology for Librarians.

ERIC Educational Resources Information Center

Nardi, Bonnie A.; O'Day, Vicki L.

1998-01-01

Examines intelligent software agents, presents nine design principles aimed specifically at the technology perspective (to personalize task performance and general principles), and discusses what librarians can do that software agents (agents defined as activity-aware software programs) cannot do. Describes an information ecology that integrates…

Mobile Agents Applications.

ERIC Educational Resources Information Center

Martins, Rosane Maria; Chaves, Magali Ribeiro; Pirmez, Luci; Rust da Costa Carmo, Luiz Fernando

2001-01-01

Discussion of the need to filter and retrieval relevant information from the Internet focuses on the use of mobile agents, specific software components which are based on distributed artificial intelligence and integrated systems. Surveys agent technology and discusses the agent building package used to develop two applications using IBM's Aglet…

Combining MMOWGLI Social Media Brainstorming with Lexical Link Analysis (LLA) to Strengthen the DoD Acquisition Process

DTIC Science & Technology

2013-09-30

founded Quantum Intelligence, Inc. She was principal investigator (PI) for six contracts awarded by the DoD Small Business Innovation Research (SBIR... Quantum Intelligence, Inc. CLA is a computer-based learning agent, or agent collaboration, capable of ingesting and processing data sources. We have...opportunities all need to be addressed consciously and consistently.  Following a series of deliberate experiments, long-term procedural improvements to the

Intelligent agents as a basis for natural language interfaces

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

Chin, D.N.

1987-01-01

Typical natural-language interfaces respond passively to the users's commands and queries. They cannot volunteer information, correction user misconceptions, or reject unethical requests. In order to do these things, a system must be an intelligent agent. UC (UNIX Consultant), a natural language system that helps the user solve problems in using the UNIX operating system, is such an intelligent agent. The agent component of UC in UCEgo. UCEgo provides UC with its own goals and plans. By adopting different goals in different situations, UCEgo creates and executes different plans, enabling it to interact appropriately with the user. UCEgo adopts goals frommore » its themes, adopts subgoals during planning, and adopts metagoals for dealing with goal interactions. It also adopts goals when it notices that the user either lacks necessary knowledge, or has incorrect beliefs. In these cases, UCEgo plans to volunteer information or correct the user's misconception as appropriate. The user's knowledge and beliefs are modeled by the KNOME (KNOwledge Model of Expertise) component of UC. KNOME is a double-stereotype system which categorizes users by expertise and categorizes UNIX facts by difficulty.« less

Evolving telemedicine/ehealth technology.

PubMed

Ferrante, Frank E

2005-06-01

This paper describes emerging technologies to support a rapidly changing and expanding scope of telemedicine/telehealth applications. Of primary interest here are wireless systems, emerging broadband, nanotechnology, intelligent agent applications, and grid computing. More specifically, the paper describes the changes underway in wireless designs aimed at enhancing security; some of the current work involving the development of nanotechnology applications and research into the use of intelligent agents/artificial intelligence technology to establish what are termed "Knowbots"; and a sampling of the use of Web services, such as grid computing capabilities, to support medical applications. In addition, the expansion of these technologies and the need for cost containment to sustain future health care for an increasingly mobile and aging population is discussed.

Designing and implementing transparency for real time inspection of autonomous robots

NASA Astrophysics Data System (ADS)

Theodorou, Andreas; Wortham, Robert H.; Bryson, Joanna J.

2017-07-01

The EPSRC's Principles of Robotics advises the implementation of transparency in robotic systems, however research related to AI transparency is in its infancy. This paper introduces the reader of the importance of having transparent inspection of intelligent agents and provides guidance for good practice when developing such agents. By considering and expanding upon other prominent definitions found in literature, we provide a robust definition of transparency as a mechanism to expose the decision-making of a robot. The paper continues by addressing potential design decisions developers need to consider when designing and developing transparent systems. Finally, we describe our new interactive intelligence editor, designed to visualise, develop and debug real-time intelligence.

Northeast Artificial Intelligence Consortium (NAIC). Volume 4. Distributed Artificial Intelligence for Communications Network Management

DTIC Science & Technology

1990-12-01

subject to resource constraints. Mul- tista~ze negotiation has been developed as a means by which an agent can acquire ,em 0ugh additional knowledge to...complete knowledge often expands the search space without providing a compensatiN means for focusing the search. In a multi-agent system with each...These relationships have strengthened our abilities to conduct meaningful research and to assist the transfer of technolog frni th, 81 university

Introduction to Agent Mining Interaction and Integration

NASA Astrophysics Data System (ADS)

Cao, Longbing

In recent years, more and more researchers have been involved in research on both agent technology and data mining. A clear disciplinary effort has been activated toward removing the boundary between them, that is the interaction and integration between agent technology and data mining. We refer this to agent mining as a new area. The marriage of agents and data mining is driven by challenges faced by both communities, and the need of developing more advanced intelligence, information processing and systems. This chapter presents an overall picture of agent mining from the perspective of positioning it as an emerging area. We summarize the main driving forces, complementary essence, disciplinary framework, applications, case studies, and trends and directions, as well as brief observation on agent-driven data mining, data mining-driven agents, and mutual issues in agent mining. Arguably, we draw the following conclusions: (1) agent mining emerges as a new area in the scientific family, (2) both agent technology and data mining can greatly benefit from agent mining, (3) it is very promising to result in additional advancement in intelligent information processing and systems. However, as a new open area, there are many issues waiting for research and development from theoretical, technological and practical perspectives.

Learning Hierarchical Skills for Game Agents from Video of Human Behavior

DTIC Science & Technology

2009-01-01

intelligent agents for computer games is an im- portant aspect of game development . However, traditional methods are expensive, and the resulting agents...Constructing autonomous agents is an essential task in game development . In this paper, we outlined a system that an- alyzes preprocessed video footage of

Intelligent Software Agents: Sensor Integration and Response

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

Kulesz, James J; Lee, Ronald W

2013-01-01

Abstract In a post Macondo world the buzzwords are Integrity Management and Incident Response Management. The twin processes are not new but the opportunity to link the two is novel. Intelligent software agents can be used with sensor networks in distributed and centralized computing systems to enhance real-time monitoring of system integrity as well as manage the follow-on incident response to changing, and potentially hazardous, environmental conditions. The software components are embedded at the sensor network nodes in surveillance systems used for monitoring unusual events. When an event occurs, the software agents establish a new concept of operation at themore » sensing node, post the event status to a blackboard for software agents at other nodes to see , and then react quickly and efficiently to monitor the scale of the event. The technology addresses a current challenge in sensor networks that prevents a rapid and efficient response when a sensor measurement indicates that an event has occurred. By using intelligent software agents - which can be stationary or mobile, interact socially, and adapt to changing situations - the technology offers features that are particularly important when systems need to adapt to active circumstances. For example, when a release is detected, the local software agent collaborates with other agents at the node to exercise the appropriate operation, such as: targeted detection, increased detection frequency, decreased detection frequency for other non-alarming sensors, and determination of environmental conditions so that adjacent nodes can be informed that an event is occurring and when it will arrive. The software agents at the nodes can also post the data in a targeted manner, so that agents at other nodes and the command center can exercise appropriate operations to recalibrate the overall sensor network and associated intelligence systems. The paper describes the concepts and provides examples of real-world implementations including the Threat Detection and Analysis System (TDAS) at the International Port of Memphis and the Biological Warning and Incident Characterization System (BWIC) Environmental Monitoring (EM) Component. Technologies developed for these 24/7 operational systems have applications for improved real-time system integrity awareness as well as provide incident response (as needed) for production and field applications.« less

Design for interaction between humans and intelligent systems during real-time fault management

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Schreckenghost, Debra L.; Thronesbery, Carroll G.

1992-01-01

Initial results are reported to provide guidance and assistance for designers of intelligent systems and their human interfaces. The objective is to achieve more effective human-computer interaction (HCI) for real time fault management support systems. Studies of the development of intelligent fault management systems within NASA have resulted in a new perspective of the user. If the user is viewed as one of the subsystems in a heterogeneous, distributed system, system design becomes the design of a flexible architecture for accomplishing system tasks with both human and computer agents. HCI requirements and design should be distinguished from user interface (displays and controls) requirements and design. Effective HCI design for multi-agent systems requires explicit identification of activities and information that support coordination and communication between agents. The effects are characterized of HCI design on overall system design and approaches are identified to addressing HCI requirements in system design. The results include definition of (1) guidance based on information level requirements analysis of HCI, (2) high level requirements for a design methodology that integrates the HCI perspective into system design, and (3) requirements for embedding HCI design tools into intelligent system development environments.

Intelligent agents for e-commerce applications

NASA Astrophysics Data System (ADS)

Vuppala, Krishna

1999-12-01

This thesis focuses on development of intelligent agent solutions for e-commerce applications. E-Commerce has several complexities like: lack of information about the players, learning the nature of one's business partners/competitors, finding the right business partner to do business with, using the right strategy to get best profit out of the negotiations etc. The agent models developed can be used in any agent solution for e-commerce. Concepts and techniques from Game Theory and Artificial Intelligence are used. The developed models have several advantages over the existing ones as: the models assume the non-availability of information about other players in the market, the models of players get updated over the time as and when new information comes about the players, the negotiation model incorporates the patience levels of the players and expectations from other players in the market. Power industry has been chosen as the application area for the demonstration of the capabilities and usage of the developed agent models. Two e-commerce scenarios where sellers and buyers can go through the power exchanges to bid in auctions, or make bilateral deals outside of the exchange are addressed. In the first scenario agent helps market participants in coordinating strategies with other participants, bidding in auctions by analyzing and understanding the behavior of other participants. In the second scenario, called "Power Traders Assistant" agent helps power trader, who buys and sells power through bilateral negotiations, in negotiating deals with his customers.

Adaptive Sniping for Volatile and Stable Continuous Double Auction Markets

NASA Astrophysics Data System (ADS)

Toft, I. E.; Bagnall, A. J.

This paper introduces a new adaptive sniping agent for the Continuous Double Auction. We begin by analysing the performance of the well known Kaplan sniper in two extremes of market conditions. We generate volatile and stable market conditions using the well known Zero Intelligence-Constrained agent and a new zero-intelligence agent Small Increment (SI). ZI-C agents submit random but profitable bids/offers and cause high volatility in prices and individual trader performance. Our new zero-intelligence agent, SI, makes small random adjustments to the outstanding bid/offer and hence is more cautious than ZI-C. We present results for SI in self-play and then analyse Kaplan in volatile and stable markets. We demonstrate that the non-adaptive Kaplan sniper can be configured to suit either market conditions, but no single configuration is performs well across both market types. We believe that in a dynamic auction environment where current or future market conditions cannot be predicted a viable sniping strategy should adapt its behaviour to suit prevailing market conditions. To this end, we propose the Adaptive Sniper (AS) agent for the CDA. AS traders classify sniping opportunities using a statistical model of market activity and adjust their classification thresholds using a Widrow-Hoff adapted search. Our AS agent requires little configuration, and outperforms the original Kaplan sniper in volatile and stable markets, and in a mixed trader type scenario that includes adaptive strategies from the literature.

A Three Pronged Approach for Improved Data Understanding: 3-D Visualization, Use of Gaming Techniques, and Intelligent Advisory Agents

DTIC Science & Technology

2006-10-01

Pronged Approach for Improved Data Understanding: 3-D Visualization, Use of Gaming Techniques, and Intelligent Advisory Agents. In Visualising Network...University at the start of each fall semester, when numerous new students arrive on campus and begin downloading extensive amounts of audio and...SIGGRAPH ’92 • C. Cruz-Neira, D.J. Sandin, T.A. DeFanti, R.V. Kenyon and J.C. Hart, "The CAVE: Audio Visual Experience Automatic Virtual Environment

The Role of Intelligent Agents in Advanced Information Systems

NASA Technical Reports Server (NTRS)

Kerschberg, Larry

1999-01-01

In this presentation we review the current ongoing research within George Mason University's (GMU) Center for Information Systems Integration and Evolution (CISE). We define characteristics of advanced information systems, discuss a family of agents for such systems, and show how GMU's Domain modeling tools and techniques can be used to define a product line Architecture for configuring NASA missions. These concepts can be used to define Advanced Engineering Environments such as those envisioned for NASA's new initiative for intelligent design and synthesis environments.

Developing Secure Agent Systems Using Delegation Based Trust Management

DTIC Science & Technology

2005-01-01

delegation rules, so that the information in the SCM may be accessed only by authorized agents. Special intelligent agents called security agents are re... Bluetooth , IEEE 802.11, or Infrared, via any hand-held device, within a Vigil can also be used in wired systems, but the focal point of our re- search is

Chronic Heart Failure Follow-up Management Based on Agent Technology.

PubMed

Mohammadzadeh, Niloofar; Safdari, Reza

2015-10-01

Monitoring heart failure patients through continues assessment of sign and symptoms by information technology tools lead to large reduction in re-hospitalization. Agent technology is one of the strongest artificial intelligence areas; therefore, it can be expected to facilitate, accelerate, and improve health services especially in home care and telemedicine. The aim of this article is to provide an agent-based model for chronic heart failure (CHF) follow-up management. This research was performed in 2013-2014 to determine appropriate scenarios and the data required to monitor and follow-up CHF patients, and then an agent-based model was designed. Agents in the proposed model perform the following tasks: medical data access, communication with other agents of the framework and intelligent data analysis, including medical data processing, reasoning, negotiation for decision-making, and learning capabilities. The proposed multi-agent system has ability to learn and thus improve itself. Implementation of this model with more and various interval times at a broader level could achieve better results. The proposed multi-agent system is no substitute for cardiologists, but it could assist them in decision-making.

How do we think machines think? An fMRI study of alleged competition with an artificial intelligence

PubMed Central

Chaminade, Thierry; Rosset, Delphine; Da Fonseca, David; Nazarian, Bruno; Lutcher, Ewald; Cheng, Gordon; Deruelle, Christine

2012-01-01

Mentalizing is defined as the inference of mental states of fellow humans, and is a particularly important skill for social interactions. Here we assessed whether activity in brain areas involved in mentalizing is specific to the processing of mental states or can be generalized to the inference of non-mental states by comparing brain responses during the interaction with an intentional and an artificial agent. Participants were scanned using fMRI during interactive rock-paper-scissors games while believing their opponent was a fellow human (Intentional agent, Int), a humanoid robot endowed with an artificial intelligence (Artificial agent, Art), or a computer playing randomly (Random agent, Rnd). Participants' subjective reports indicated that they adopted different stances against the three agents. The contrast of brain activity during interaction with the artificial and the random agents didn't yield any cluster at the threshold used, suggesting the absence of a reproducible stance when interacting with an artificial intelligence. We probed response to the artificial agent in regions of interest corresponding to clusters found in the contrast between the intentional and the random agents. In the precuneus involved in working memory, the posterior intraparietal suclus, in the control of attention and the dorsolateral prefrontal cortex, in executive functions, brain activity for Art was larger than for Rnd but lower than for Int, supporting the intrinsically engaging nature of social interactions. A similar pattern in the left premotor cortex and anterior intraparietal sulcus involved in motor resonance suggested that participants simulated human, and to a lesser extend humanoid robot actions, when playing the game. Finally, mentalizing regions, the medial prefrontal cortex and right temporoparietal junction, responded to the human only, supporting the specificity of mentalizing areas for interactions with intentional agents. PMID:22586381

How do we think machines think? An fMRI study of alleged competition with an artificial intelligence.

PubMed

Chaminade, Thierry; Rosset, Delphine; Da Fonseca, David; Nazarian, Bruno; Lutcher, Ewald; Cheng, Gordon; Deruelle, Christine

2012-01-01

Mentalizing is defined as the inference of mental states of fellow humans, and is a particularly important skill for social interactions. Here we assessed whether activity in brain areas involved in mentalizing is specific to the processing of mental states or can be generalized to the inference of non-mental states by comparing brain responses during the interaction with an intentional and an artificial agent. Participants were scanned using fMRI during interactive rock-paper-scissors games while believing their opponent was a fellow human (Intentional agent, Int), a humanoid robot endowed with an artificial intelligence (Artificial agent, Art), or a computer playing randomly (Random agent, Rnd). Participants' subjective reports indicated that they adopted different stances against the three agents. The contrast of brain activity during interaction with the artificial and the random agents didn't yield any cluster at the threshold used, suggesting the absence of a reproducible stance when interacting with an artificial intelligence. We probed response to the artificial agent in regions of interest corresponding to clusters found in the contrast between the intentional and the random agents. In the precuneus involved in working memory, the posterior intraparietal suclus, in the control of attention and the dorsolateral prefrontal cortex, in executive functions, brain activity for Art was larger than for Rnd but lower than for Int, supporting the intrinsically engaging nature of social interactions. A similar pattern in the left premotor cortex and anterior intraparietal sulcus involved in motor resonance suggested that participants simulated human, and to a lesser extend humanoid robot actions, when playing the game. Finally, mentalizing regions, the medial prefrontal cortex and right temporoparietal junction, responded to the human only, supporting the specificity of mentalizing areas for interactions with intentional agents.

An Intelligent Agent-Controlled and Robot-Based Disassembly Assistant

NASA Astrophysics Data System (ADS)

Jungbluth, Jan; Gerke, Wolfgang; Plapper, Peter

2017-09-01

One key for successful and fluent human-robot-collaboration in disassembly processes is equipping the robot system with higher autonomy and intelligence. In this paper, we present an informed software agent that controls the robot behavior to form an intelligent robot assistant for disassembly purposes. While the disassembly process first depends on the product structure, we inform the agent using a generic approach through product models. The product model is then transformed to a directed graph and used to build, share and define a coarse disassembly plan. To refine the workflow, we formulate “the problem of loosening a connection and the distribution of the work” as a search problem. The created detailed plan consists of a sequence of actions that are used to call, parametrize and execute robot programs for the fulfillment of the assistance. The aim of this research is to equip robot systems with knowledge and skills to allow them to be autonomous in the performance of their assistance to finally improve the ergonomics of disassembly workstations.

Multi Sensor Fusion Using Fitness Adaptive Differential Evolution

NASA Astrophysics Data System (ADS)

Giri, Ritwik; Ghosh, Arnob; Chowdhury, Aritra; Das, Swagatam

The rising popularity of multi-source, multi-sensor networks supports real-life applications calls for an efficient and intelligent approach to information fusion. Traditional optimization techniques often fail to meet the demands. The evolutionary approach provides a valuable alternative due to its inherent parallel nature and its ability to deal with difficult problems. We present a new evolutionary approach based on a modified version of Differential Evolution (DE), called Fitness Adaptive Differential Evolution (FiADE). FiADE treats sensors in the network as distributed intelligent agents with various degrees of autonomy. Existing approaches based on intelligent agents cannot completely answer the question of how their agents could coordinate their decisions in a complex environment. The proposed approach is formulated to produce good result for the problems that are high-dimensional, highly nonlinear, and random. The proposed approach gives better result in case of optimal allocation of sensors. The performance of the proposed approach is compared with an evolutionary algorithm coordination generalized particle model (C-GPM).

New robotics: design principles for intelligent systems.

PubMed

Pfeifer, Rolf; Iida, Fumiya; Bongard, Josh

2005-01-01

New robotics is an approach to robotics that, in contrast to traditional robotics, employs ideas and principles from biology. While in the traditional approach there are generally accepted methods (e. g., from control theory), designing agents in the new robotics approach is still largely considered an art. In recent years, we have been developing a set of heuristics, or design principles, that on the one hand capture theoretical insights about intelligent (adaptive) behavior, and on the other provide guidance in actually designing and building systems. In this article we provide an overview of all the principles but focus on the principles of ecological balance, which concerns the relation between environment, morphology, materials, and control, and sensory-motor coordination, which concerns self-generated sensory stimulation as the agent interacts with the environment and which is a key to the development of high-level intelligence. As we argue, artificial evolution together with morphogenesis is not only "nice to have" but is in fact a necessary tool for designing embodied agents.

The Next Generation of Interoperability Agents in Healthcare

PubMed Central

Cardoso, Luciana; Marins, Fernando; Portela, Filipe; Santos, Manuel ; Abelha, António; Machado, José

2014-01-01

Interoperability in health information systems is increasingly a requirement rather than an option. Standards and technologies, such as multi-agent systems, have proven to be powerful tools in interoperability issues. In the last few years, the authors have worked on developing the Agency for Integration, Diffusion and Archive of Medical Information (AIDA), which is an intelligent, agent-based platform to ensure interoperability in healthcare units. It is increasingly important to ensure the high availability and reliability of systems. The functions provided by the systems that treat interoperability cannot fail. This paper shows the importance of monitoring and controlling intelligent agents as a tool to anticipate problems in health information systems. The interaction between humans and agents through an interface that allows the user to create new agents easily and to monitor their activities in real time is also an important feature, as health systems evolve by adopting more features and solving new problems. A module was installed in Centro Hospitalar do Porto, increasing the functionality and the overall usability of AIDA. PMID:24840351

Towards General Evaluation of Intelligent Systems: Lessons Learned from Reproducing AIQ Test Results

NASA Astrophysics Data System (ADS)

Vadinský, Ondřej

2018-03-01

This paper attempts to replicate the results of evaluating several artificial agents using the Algorithmic Intelligence Quotient test originally reported by Legg and Veness. Three experiments were conducted: One using default settings, one in which the action space was varied and one in which the observation space was varied. While the performance of freq, Q0, Qλ, and HLQλ corresponded well with the original results, the resulting values differed, when using MC-AIXI. Varying the observation space seems to have no qualitative impact on the results as reported, while (contrary to the original results) varying the action space seems to have some impact. An analysis of the impact of modifying parameters of MC-AIXI on its performance in the default settings was carried out with the help of data mining techniques used to identifying highly performing configurations. Overall, the Algorithmic Intelligence Quotient test seems to be reliable, however as a general artificial intelligence evaluation method it has several limits. The test is dependent on the chosen reference machine and also sensitive to changes to its settings. It brings out some differences among agents, however, since they are limited in size, the test setting may not yet be sufficiently complex. A demanding parameter sweep is needed to thoroughly evaluate configurable agents that, together with the test format, further highlights computational requirements of an agent. These and other issues are discussed in the paper along with proposals suggesting how to alleviate them. An implementation of some of the proposals is also demonstrated.

The Interplay between Information and Control Theory within Interactive Decision-Making Problems

ERIC Educational Resources Information Center

Gorantla, Siva Kumar

2012-01-01

The context for this work is two-agent team decision systems. An "agent" is an intelligent entity that can measure some aspect of its environment, process information and possibly influence the environment through its action. In a collaborative two-agent team decision system, the agents can be coupled by noisy or noiseless interactions…

Suitability of Agent Technology for Military Command and Control in the Future Combat System Environment

DTIC Science & Technology

2003-06-01

and Multi-Agent Systems 1 no. 1 (1998): 7-38. [23] K. Sycara, A. Pannu , M. Williamson, and D. Zeng, “Distributed Intelligent Agents,” IEEE Expert 11...services that include support for mobility, security, management, persistence, and naming of agents. [i] K. Sycara, A. Pannu , M. Williamson, and D

An Immune Agent for Web-Based AI Course

ERIC Educational Resources Information Center

Gong, Tao; Cai, Zixing

2006-01-01

To overcome weakness and faults of a web-based e-learning course such as Artificial Intelligence (AI), an immune agent was proposed, simulating a natural immune mechanism against a virus. The immune agent was built on the multi-dimension education agent model and immune algorithm. The web-based AI course was comprised of many files, such as HTML…

Self-Learning Intelligent Agents for Dynamic Traffic Routing on Transportation Networks

NASA Astrophysics Data System (ADS)

Sadek, Add; Basha, Nagi

Intelligent Transportation Systems (ITS) are designed to take advantage of recent advances in communications, electronics, and Information Technology in improving the efficiency and safety of transportation systems. Among the several ITS applications is the notion of Dynamic Traffic Routing (DTR), which involves generating "optimal" routing recommendations to drivers with the aim of maximizing network utilizing. In this paper, we demonstrate the feasibility of using a self-learning intelligent agent to solve the DTR problem to achieve traffic user equilibrium in a transportation network. The core idea is to deploy an agent to a simulation model of a highway. The agent then learns by itself by interacting with the simulation model. Once the agent reaches a satisfactory level of performance, it can then be deployed to the real-world, where it would continue to learn how to refine its control policies over time. To test this concept in this paper, the Cell Transmission Model (CTM) developed by Carlos Daganzo of the University of California at Berkeley is used to simulate a simple highway with two main alternative routes. With the model developed, a Reinforcement Learning Agent (RLA) is developed to learn how to best dynamically route traffic, so as to maximize the utilization of existing capacity. Preliminary results obtained from our experiments are promising. RL, being an adaptive online learning technique, appears to have a great potential for controlling a stochastic dynamic systems such as a transportation system. Furthermore, the approach is highly scalable and applicable to a variety of networks and roadways.

Resource allocation and supervisory control architecture for intelligent behavior generation

NASA Astrophysics Data System (ADS)

Shah, Hitesh K.; Bahl, Vikas; Moore, Kevin L.; Flann, Nicholas S.; Martin, Jason

2003-09-01

In earlier research the Center for Self-Organizing and Intelligent Systems (CSOIS) at Utah State University (USU) was funded by the US Army Tank-Automotive and Armaments Command's (TACOM) Intelligent Mobility Program to develop and demonstrate enhanced mobility concepts for unmanned ground vehicles (UGVs). As part of our research, we presented the use of a grammar-based approach to enabling intelligent behaviors in autonomous robotic vehicles. With the growth of the number of available resources on the robot, the variety of the generated behaviors and the need for parallel execution of multiple behaviors to achieve reaction also grew. As continuation of our past efforts, in this paper, we discuss the parallel execution of behaviors and the management of utilized resources. In our approach, available resources are wrapped with a layer (termed services) that synchronizes and serializes access to the underlying resources. The controlling agents (called behavior generating agents) generate behaviors to be executed via these services. The agents are prioritized and then, based on their priority and the availability of requested services, the Control Supervisor decides on a winner for the grant of access to services. Though the architecture is applicable to a variety of autonomous vehicles, we discuss its application on T4, a mid-sized autonomous vehicle developed for security applications.

An Innovative Multi-Agent Search-and-Rescue Path Planning Approach

DTIC Science & Technology

2015-03-09

search problems from search theory and artificial intelligence /distributed robotic control, and pursuit-evasion problem perspectives may be found in...Dissanayake, “Probabilistic search for a moving target in an indoor environment”, In Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems, 2006, pp...3393-3398. [7] H. Lau, and G. Dissanayake, “Optimal search for multiple targets in a built environment”, In Proc. IEEE/RSJ Int. Conf. Intelligent

Studies in Intelligence. Volume 55, Number 3

DTIC Science & Technology

2011-09-01

hearing, Director of National Intelligence (DNI) James R. Clapper noted the need for a single repository of terrorism- related data as a foundation...A CIA Memoir by Stuart Methven The Making And Breaking Of An American Spy, by James Everett Intelligence Abroad Ashraf Marwan, Israel’s Most Valuable...Bureau cases. He includes bio - graphical details about special agents and illu- minates the often frustrating bureaucratic culture in which they

Indexing and retrieval of multimedia objects at different levels of granularity

NASA Astrophysics Data System (ADS)

Faudemay, Pascal; Durand, Gwenael; Seyrat, Claude; Tondre, Nicolas

1998-10-01

Intelligent access to multimedia databases for `naive user' should probably be based on queries formulation by `intelligent agents'. These agents should `understand' the semantics of the contents, learn user preferences and deliver to the user a subset of the source contents, for further navigation. The goal of such systems should be to enable `zero-command' access to the contents, while keeping the freedom of choice of the user. Such systems should interpret multimedia contents in terms of multiple audiovisual objects (from video to visual or audio object), and on actions and scenarios.

Behavioral networks as a model for intelligent agents

NASA Technical Reports Server (NTRS)

Sliwa, Nancy E.

1990-01-01

On-going work at NASA Langley Research Center in the development and demonstration of a paradigm called behavioral networks as an architecture for intelligent agents is described. This work focuses on the need to identify a methodology for smoothly integrating the characteristics of low-level robotic behavior, including actuation and sensing, with intelligent activities such as planning, scheduling, and learning. This work assumes that all these needs can be met within a single methodology, and attempts to formalize this methodology in a connectionist architecture called behavioral networks. Behavioral networks are networks of task processes arranged in a task decomposition hierarchy. These processes are connected by both command/feedback data flow, and by the forward and reverse propagation of weights which measure the dynamic utility of actions and beliefs.

ICCE/ICCAI 2000 Full & Short Papers (Educational Agent).

ERIC Educational Resources Information Center

2000

This document contains the full text of the following papers on educational agent from ICCE/ICCAI 2000 (International Conference on Computers in Education/International Conference on Computer-Assisted Instruction): (1) "An Agent-Based Intelligent Tutoring System" (C.M. Bruff and M.A. Williams); (2) "Design of Systematic Concept…

Learning by Communicating in Natural Language with Conversational Agents

ERIC Educational Resources Information Center

Graesser, Arthur; Li, Haiying; Forsyth, Carol

2014-01-01

Learning is facilitated by conversational interactions both with human tutors and with computer agents that simulate human tutoring and ideal pedagogical strategies. In this article, we describe some intelligent tutoring systems (e.g., AutoTutor) in which agents interact with students in natural language while being sensitive to their cognitive…

Outperforming Game Theoretic Play with Opponent Modeling in Two Player Dominoes

DTIC Science & Technology

2014-03-27

36 III. Methodology Introduction This chapter describes the methodology of how a dominoes artificial intelligence agent employs...Applying this concept to a partially observable game means that both players will have to model each other and have some intelligence of the board...

The predictive power of zero intelligence in financial markets

NASA Astrophysics Data System (ADS)

Farmer, J. Doyne; Patelli, Paolo; Zovko, Ilija I.

2005-02-01

Standard models in economics stress the role of intelligent agents who maximize utility. However, there may be situations where constraints imposed by market institutions dominate strategic agent behavior. We use data from the London Stock Exchange to test a simple model in which minimally intelligent agents place orders to trade at random. The model treats the statistical mechanics of order placement, price formation, and the accumulation of revealed supply and demand within the context of the continuous double auction and yields simple laws relating order-arrival rates to statistical properties of the market. We test the validity of these laws in explaining cross-sectional variation for 11 stocks. The model explains 96% of the variance of the gap between the best buying and selling prices (the spread) and 76% of the variance of the price diffusion rate, with only one free parameter. We also study the market impact function, describing the response of quoted prices to the arrival of new orders. The nondimensional coordinates dictated by the model approximately collapse data from different stocks onto a single curve. This work is important from a practical point of view, because it demonstrates the existence of simple laws relating prices to order flows and, in a broader context, suggests there are circumstances where the strategic behavior of agents may be dominated by other considerations. double auction market | market microstructure | agent-based models

Chronic Heart Failure Follow-up Management Based on Agent Technology

PubMed Central

Safdari, Reza

2015-01-01

Objectives Monitoring heart failure patients through continues assessment of sign and symptoms by information technology tools lead to large reduction in re-hospitalization. Agent technology is one of the strongest artificial intelligence areas; therefore, it can be expected to facilitate, accelerate, and improve health services especially in home care and telemedicine. The aim of this article is to provide an agent-based model for chronic heart failure (CHF) follow-up management. Methods This research was performed in 2013-2014 to determine appropriate scenarios and the data required to monitor and follow-up CHF patients, and then an agent-based model was designed. Results Agents in the proposed model perform the following tasks: medical data access, communication with other agents of the framework and intelligent data analysis, including medical data processing, reasoning, negotiation for decision-making, and learning capabilities. Conclusions The proposed multi-agent system has ability to learn and thus improve itself. Implementation of this model with more and various interval times at a broader level could achieve better results. The proposed multi-agent system is no substitute for cardiologists, but it could assist them in decision-making. PMID:26618038

Agent Based Fault Tolerance for the Mobile Environment

NASA Astrophysics Data System (ADS)

Park, Taesoon

This paper presents a fault-tolerance scheme based on mobile agents for the reliable mobile computing systems. Mobility of the agent is suitable to trace the mobile hosts and the intelligence of the agent makes it efficient to support the fault tolerance services. This paper presents two approaches to implement the mobile agent based fault tolerant service and their performances are evaluated and compared with other fault-tolerant schemes.

Nondestructive Intervention to Multi-Agent Systems through an Intelligent Agent

PubMed Central

Han, Jing; Wang, Lin

2013-01-01

For a given multi-agent system where the local interaction rule of the existing agents can not be re-designed, one way to intervene the collective behavior of the system is to add one or a few special agents into the group which are still treated as normal agents by the existing ones. We study how to lead a Vicsek-like flocking model to reach synchronization by adding special agents. A popular method is to add some simple leaders (fixed-headings agents). However, we add one intelligent agent, called ‘shill’, which uses online feedback information of the group to decide the shill's moving direction at each step. A novel strategy for the shill to coordinate the group is proposed. It is strictly proved that a shill with this strategy and a limited speed can synchronize every agent in the group. The computer simulations show the effectiveness of this strategy in different scenarios, including different group sizes, shill speed, and with or without noise. Compared to the method of adding some fixed-heading leaders, our method can guarantee synchronization for any initial configuration in the deterministic scenario and improve the synchronization level significantly in low density groups, or model with noise. This suggests the advantage and power of feedback information in intervention of collective behavior. PMID:23658695

A cognitive information processing framework for distributed sensor networks

NASA Astrophysics Data System (ADS)

Wang, Feiyi; Qi, Hairong

2004-09-01

In this paper, we present a cognitive agent framework (CAF) based on swarm intelligence and self-organization principles, and demonstrate it through collaborative processing for target classification in sensor networks. The framework involves integrated designs to provide both cognitive behavior at the organization level to conquer complexity and reactive behavior at the individual agent level to retain simplicity. The design tackles various problems in the current information processing systems, including overly complex systems, maintenance difficulties, increasing vulnerability to attack, lack of capability to tolerate faults, and inability to identify and cope with low-frequency patterns. An important and distinguishing point of the presented work from classical AI research is that the acquired intelligence does not pertain to distinct individuals but to groups. It also deviates from multi-agent systems (MAS) due to sheer quantity of extremely simple agents we are able to accommodate, to the degree that some loss of coordination messages and behavior of faulty/compromised agents will not affect the collective decision made by the group.

Economic reasoning and artificial intelligence.

PubMed

Parkes, David C; Wellman, Michael P

2015-07-17

The field of artificial intelligence (AI) strives to build rational agents capable of perceiving the world around them and taking actions to advance specified goals. Put another way, AI researchers aim to construct a synthetic homo economicus, the mythical perfectly rational agent of neoclassical economics. We review progress toward creating this new species of machine, machina economicus, and discuss some challenges in designing AIs that can reason effectively in economic contexts. Supposing that AI succeeds in this quest, or at least comes close enough that it is useful to think about AIs in rationalistic terms, we ask how to design the rules of interaction in multi-agent systems that come to represent an economy of AIs. Theories of normative design from economics may prove more relevant for artificial agents than human agents, with AIs that better respect idealized assumptions of rationality than people, interacting through novel rules and incentive systems quite distinct from those tailored for people. Copyright © 2015, American Association for the Advancement of Science.

A Formal Characterization of Relevant Information in Multi-Agent Systems

DTIC Science & Technology

2009-10-01

Conference iTrust. (2004) [17] Sadek, D.: Le dialogue homme-machine : de l’ ergonomie des interfaces à l’ agent intelligent dia- loguant. In: Nouvelles interfaces hommemachine, Lavoisier Editeur, Arago 18 (1996) 277–321

Architecture for Adaptive Intelligent Systems

NASA Technical Reports Server (NTRS)

Hayes-Roth, Barbara

1993-01-01

We identify a class of niches to be occupied by 'adaptive intelligent systems (AISs)'. In contrast with niches occupied by typical AI agents, AIS niches present situations that vary dynamically along several key dimensions: different combinations of required tasks, different configurations of available resources, contextual conditions ranging from benign to stressful, and different performance criteria. We present a small class hierarchy of AIS niches that exhibit these dimensions of variability and describe a particular AIS niche, ICU (intensive care unit) patient monitoring, which we use for illustration throughout the paper. We have designed and implemented an agent architecture that supports all of different kinds of adaptation by exploiting a single underlying theoretical concept: An agent dynamically constructs explicit control plans to guide its choices among situation-triggered behaviors. We illustrate the architecture and its support for adaptation with examples from Guardian, an experimental agent for ICU monitoring.

Towards a Bio-inspired Security Framework for Mission-Critical Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Ren, Wei; Song, Jun; Ma, Zhao; Huang, Shiyong

Mission-critical wireless sensor networks (WSNs) have been found in numerous promising applications in civil and military fields. However, the functionality of WSNs extensively relies on its security capability for detecting and defending sophisticated adversaries, such as Sybil, worm hole and mobile adversaries. In this paper, we propose a bio-inspired security framework to provide intelligence-enabled security mechanisms. This scheme is composed of a middleware, multiple agents and mobile agents. The agents monitor the network packets, host activities, make decisions and launch corresponding responses. Middleware performs an infrastructure for the communication between various agents and corresponding mobility. Certain cognitive models and intelligent algorithms such as Layered Reference Model of Brain and Self-Organizing Neural Network with Competitive Learning are explored in the context of sensor networks that have resource constraints. The security framework and implementation are also described in details.

Towards Computational Fronesis: Verifying Contextual Appropriateness of Emotions

ERIC Educational Resources Information Center

Ptaszynski, Michal; Dybala, Pawel; Mazur, Michal; Rzepka, Rafal; Araki, Kenji; Momouchi, Yoshio

2013-01-01

This paper presents research in Contextual Affect Analysis (CAA) for the need of future application in intelligent agents, such as conversational agents or artificial tutors. The authors propose a new term, Computational Fronesis (CF), to embrace the tasks included in CAA applied to development of conversational agents such as artificial tutors.…

Using Agent-Based Technologies to Enhance Learning in Educational Games

ERIC Educational Resources Information Center

Tumenayu, Ogar Ofut; Shabalina, Olga; Kamaev, Valeriy; Davtyan, Alexander

2014-01-01

Recent research has shown that educational games positively motivate learning. However, there is a little evidence that they can trigger learning to a large extent if the game-play is supported by additional activities. We aim to support educational games development with an Agent-Based Technology (ABT) by using intelligent pedagogical agents that…

Collective Machine Learning: Team Learning and Classification in Multi-Agent Systems

ERIC Educational Resources Information Center

Gifford, Christopher M.

2009-01-01

This dissertation focuses on the collaboration of multiple heterogeneous, intelligent agents (hardware or software) which collaborate to learn a task and are capable of sharing knowledge. The concept of collaborative learning in multi-agent and multi-robot systems is largely under studied, and represents an area where further research is needed to…

Recent progress in econophysics: Chaos, leverage, and business cycles as revealed by agent-based modeling and human experiments

NASA Astrophysics Data System (ADS)

Xin, Chen; Huang, Ji-Ping

2017-12-01

Agent-based modeling and controlled human experiments serve as two fundamental research methods in the field of econophysics. Agent-based modeling has been in development for over 20 years, but how to design virtual agents with high levels of human-like "intelligence" remains a challenge. On the other hand, experimental econophysics is an emerging field; however, there is a lack of experience and paradigms related to the field. Here, we review some of the most recent research results obtained through the use of these two methods concerning financial problems such as chaos, leverage, and business cycles. We also review the principles behind assessments of agents' intelligence levels, and some relevant designs for human experiments. The main theme of this review is to show that by combining theory, agent-based modeling, and controlled human experiments, one can garner more reliable and credible results on account of a better verification of theory; accordingly, this way, a wider range of economic and financial problems and phenomena can be studied.

Computational Intelligence in Web-Based Education: A Tutorial

ERIC Educational Resources Information Center

Vasilakos, Thanos; Devedzic, Vladan; Kinshuk; Pedrycz, Witold

2004-01-01

This article discusses some important aspects of Web Intelligence (WI) in the context of educational applications. Some of the key components of WI have already attracted developers of web-based educational systems for quite some time- ontologies, adaptivity and personalization, and agents. The paper focuses on the application of Computational…

The predictive power of zero intelligence in financial markets.

PubMed

Farmer, J Doyne; Patelli, Paolo; Zovko, Ilija I

2005-02-08

Standard models in economics stress the role of intelligent agents who maximize utility. However, there may be situations where constraints imposed by market institutions dominate strategic agent behavior. We use data from the London Stock Exchange to test a simple model in which minimally intelligent agents place orders to trade at random. The model treats the statistical mechanics of order placement, price formation, and the accumulation of revealed supply and demand within the context of the continuous double auction and yields simple laws relating order-arrival rates to statistical properties of the market. We test the validity of these laws in explaining cross-sectional variation for 11 stocks. The model explains 96% of the variance of the gap between the best buying and selling prices (the spread) and 76% of the variance of the price diffusion rate, with only one free parameter. We also study the market impact function, describing the response of quoted prices to the arrival of new orders. The nondimensional coordinates dictated by the model approximately collapse data from different stocks onto a single curve. This work is important from a practical point of view, because it demonstrates the existence of simple laws relating prices to order flows and, in a broader context, suggests there are circumstances where the strategic behavior of agents may be dominated by other considerations.

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.

Pervasive community care platform: Ambient Intelligence leveraging sensor networks and mobile agents

NASA Astrophysics Data System (ADS)

Su, Chuan-Jun; Chiang, Chang-Yu

2014-04-01

Several powerful trends are contributing to an aging of much of the world's population, especially in economically developed countries. To mitigate the negative effects of rapidly ageing populations, societies must act early to plan for the welfare, medical care and residential arrangements of their senior citizens, and for the manpower and associated training needed to execute these plans. This paper describes the development of an Ambient Intelligent Community Care Platform (AICCP), which creates an environment of Ambient Intelligence through the use of sensor network and mobile agent (MA) technologies. The AICCP allows caregivers to quickly and accurately locate their charges; access, update and share critical treatment and wellness data; and automatically archive all records. The AICCP presented in this paper is expected to enable caregivers and communities to offer pervasive, accurate and context-aware care services.

Intelligent Information Fusion in the Aviation Domain: A Semantic-Web based Approach

NASA Technical Reports Server (NTRS)

Ashish, Naveen; Goforth, Andre

2005-01-01

Information fusion from multiple sources is a critical requirement for System Wide Information Management in the National Airspace (NAS). NASA and the FAA envision creating an "integrated pool" of information originally coming from different sources, which users, intelligent agents and NAS decision support tools can tap into. In this paper we present the results of our initial investigations into the requirements and prototype development of such an integrated information pool for the NAS. We have attempted to ascertain key requirements for such an integrated pool based on a survey of DSS tools that will benefit from this integrated pool. We then advocate key technologies from computer science research areas such as the semantic web, information integration, and intelligent agents that we believe are well suited to achieving the envisioned system wide information management capabilities.

An Approach for Autonomy: A Collaborative Communication Framework for Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Dufrene, Warren Russell, Jr.

2005-01-01

Research done during the last three years has studied the emersion properties of Complex Adaptive Systems (CAS). The deployment of Artificial Intelligence (AI) techniques applied to remote Unmanned Aerial Vehicles has led the author to investigate applications of CAS within the field of Autonomous Multi-Agent Systems. The core objective of current research efforts is focused on the simplicity of Intelligent Agents (IA) and the modeling of these agents within complex systems. This research effort looks at the communication, interaction, and adaptability of multi-agents as applied to complex systems control. The embodiment concept applied to robotics has application possibilities within multi-agent frameworks. A new framework for agent awareness within a virtual 3D world concept is possible where the vehicle is composed of collaborative agents. This approach has many possibilities for applications to complex systems. This paper describes the development of an approach to apply this virtual framework to the NASA Goddard Space Flight Center (GSFC) tetrahedron structure developed under the Autonomous Nano Technology Swarm (ANTS) program and the Super Miniaturized Addressable Reconfigurable Technology (SMART) architecture program. These projects represent an innovative set of novel concepts deploying adaptable, self-organizing structures composed of many tetrahedrons. This technology is pushing current applied Agents Concepts to new levels of requirements and adaptability.

Intelligent Agent Transparency in Human-Agent Teaming for Multi-UxV Management.

PubMed

Mercado, Joseph E; Rupp, Michael A; Chen, Jessie Y C; Barnes, Michael J; Barber, Daniel; Procci, Katelyn

2016-05-01

We investigated the effects of level of agent transparency on operator performance, trust, and workload in a context of human-agent teaming for multirobot management. Participants played the role of a heterogeneous unmanned vehicle (UxV) operator and were instructed to complete various missions by giving orders to UxVs through a computer interface. An intelligent agent (IA) assisted the participant by recommending two plans-a top recommendation and a secondary recommendation-for every mission. A within-subjects design with three levels of agent transparency was employed in the present experiment. There were eight missions in each of three experimental blocks, grouped by level of transparency. During each experimental block, the IA was incorrect three out of eight times due to external information (e.g., commander's intent and intelligence). Operator performance, trust, workload, and usability data were collected. Results indicate that operator performance, trust, and perceived usability increased as a function of transparency level. Subjective and objective workload data indicate that participants' workload did not increase as a function of transparency. Furthermore, response time did not increase as a function of transparency. Unlike previous research, which showed that increased transparency resulted in increased performance and trust calibration at the cost of greater workload and longer response time, our results support the benefits of transparency for performance effectiveness without additional costs. The current results will facilitate the implementation of IAs in military settings and will provide useful data to the design of heterogeneous UxV teams. © 2016, Human Factors and Ergonomics Society.

Concurrent Learning of Control in Multi agent Sequential Decision Tasks

DTIC Science & Technology

2018-04-17

Concurrent Learning of Control in Multi-agent Sequential Decision Tasks The overall objective of this project was to develop multi-agent reinforcement...learning (MARL) approaches for intelligent agents to autonomously learn distributed control policies in decentral- ized partially observable...shall be subject to any oenalty for failing to comply with a collection of information if it does not display a currently valid OMB control number

42 CFR 73.10 - Restricting access to select agents and toxins; security risk assessments.

Code of Federal Regulations, 2011 CFR

2011-10-01

... AND HUMAN SERVICES QUARANTINE, INSPECTION, LICENSING SELECT AGENTS AND TOXINS § 73.10 Restricting... or intelligence agency of committing a crime specified in 18 U.S.C. 2332b(g)(5), knowing involvement...

Remote Agent Experiment

NASA Technical Reports Server (NTRS)

Benard, Doug; Dorais, Gregory A.; Gamble, Ed; Kanefsky, Bob; Kurien, James; Millar, William; Muscettola, Nicola; Nayak, Pandu; Rouquette, Nicolas; Rajan, Kanna;

The use of computer vision in an intelligent environment to support aging-in-place, safety, and independence in the home.

PubMed

Mihailidis, Alex; Carmichael, Brent; Boger, Jennifer

2004-09-01

This paper discusses the use of computer vision in pervasive healthcare systems, specifically in the design of a sensing agent for an intelligent environment that assists older adults with dementia during an activity of daily living. An overview of the techniques applied in this particular example is provided, along with results from preliminary trials completed using the new sensing agent. A discussion of the results obtained to date is presented, including technical and social issues that remain for the advancement and acceptance of this type of technology within pervasive healthcare.

Fuzzy Q-Learning for Generalization of Reinforcement Learning

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1996-01-01

Fuzzy Q-Learning, introduced earlier by the author, is an extension of Q-Learning into fuzzy environments. GARIC is a methodology for fuzzy reinforcement learning. In this paper, we introduce GARIC-Q, a new method for doing incremental Dynamic Programming using a society of intelligent agents which are controlled at the top level by Fuzzy Q-Learning and at the local level, each agent learns and operates based on GARIC. GARIC-Q improves the speed and applicability of Fuzzy Q-Learning through generalization of input space by using fuzzy rules and bridges the gap between Q-Learning and rule based intelligent systems.

CATS-based Air Traffic Controller Agents

NASA Technical Reports Server (NTRS)

Callantine, Todd J.

2002-01-01

This report describes intelligent agents that function as air traffic controllers. Each agent controls traffic in a single sector in real time; agents controlling traffic in adjoining sectors can coordinate to manage an arrival flow across a given meter fix. The purpose of this research is threefold. First, it seeks to study the design of agents for controlling complex systems. In particular, it investigates agent planning and reactive control functionality in a dynamic environment in which a variety perceptual and decision making skills play a central role. It examines how heuristic rules can be applied to model planning and decision making skills, rather than attempting to apply optimization methods. Thus, the research attempts to develop intelligent agents that provide an approximation of human air traffic controller behavior that, while not based on an explicit cognitive model, does produce task performance consistent with the way human air traffic controllers operate. Second, this research sought to extend previous research on using the Crew Activity Tracking System (CATS) as the basis for intelligent agents. The agents use a high-level model of air traffic controller activities to structure the control task. To execute an activity in the CATS model, according to the current task context, the agents reference a 'skill library' and 'control rules' that in turn execute the pattern recognition, planning, and decision-making required to perform the activity. Applying the skills enables the agents to modify their representation of the current control situation (i.e., the 'flick' or 'picture'). The updated representation supports the next activity in a cycle of action that, taken as a whole, simulates air traffic controller behavior. A third, practical motivation for this research is to use intelligent agents to support evaluation of new air traffic control (ATC) methods to support new Air Traffic Management (ATM) concepts. Current approaches that use large, human-in-the-loop simulations are unquestionably valuable for this purpose, but pose considerable logistical, fiscal, and experimental control problems. First, data analysis is extremely complicated, owing simply to the large number of participants and data sources in such simulations. In addition, experienced human air traffic controllers working adjacent sectors tend to flexibly adapt to the evolving control problem - potentially shifting to other strategies than those under investigation. In addition, their performance is tightly coupled to the control interface, which in the development phase may support some concepts and supporting strategies better than others. A simple shift in strategy by one controller can change the character of a particular traffic scenario dramatically, which makes experimental comparison of ATC performance under different traffic scenarios difficult. Training a given team of controllers on operations under a new ATM concept for a sufficient period of time could avert such difficulties, but instituting an adequate training program is expensive and logistically difficult.

Smart materials on the way to theranostic nanorobots: Molecular machines and nanomotors, advanced biosensors, and intelligent vehicles for drug delivery.

PubMed

Sokolov, Ilya L; Cherkasov, Vladimir R; Tregubov, Andrey A; Buiucli, Sveatoslav R; Nikitin, Maxim P

2017-06-01

Theranostics, a fusion of two key parts of modern medicine - diagnostics and therapy of the organism's disorders, promises to bring the efficacy of medical treatment to a fundamentally new level and to become the basis of personalized medicine. Extrapolating today's progress in the field of smart materials to the long-run prospect, we can imagine future intelligent agents capable of performing complex analysis of different physiological factors inside the living organism and implementing a built-in program thereby triggering a series of therapeutic actions. These agents, by analogy with their macroscopic counterparts, can be called nanorobots. It is quite obscure what these devices are going to look like but they will be more or less based on today's achievements in nanobiotechnology. The present Review is an attempt to systematize highly diverse nanomaterials, which may potentially serve as modules for theranostic nanorobotics, e.g., nanomotors, sensing units, and payload carriers. Biocomputing-based sensing, externally actuated or chemically "fueled" autonomous movement, swarm inter-agent communication behavior are just a few inspiring examples that nanobiotechnology can offer today for construction of truly intelligent drug delivery systems. The progress of smart nanomaterials toward fully autonomous drug delivery nanorobots is an exciting prospect for disease treatment. Synergistic combination of the available approaches and their further development may produce intelligent drugs of unmatched functionality. Copyright © 2017 Elsevier B.V. All rights reserved.

Improving Students' Help-Seeking Skills Using Metacognitive Feedback in an Intelligent Tutoring System

ERIC Educational Resources Information Center

Roll, Ido; Aleven, Vincent; McLaren, Bruce M.; Koedinger, Kenneth R.

2011-01-01

The present research investigated whether immediate metacognitive feedback on students' help-seeking errors can help students acquire better help-seeking skills. The Help Tutor, an intelligent tutor agent for help seeking, was integrated into a commercial tutoring system for geometry, the Geometry Cognitive Tutor. Study 1, with 58 students, found…

Tactical assessment in a squad of intelligent bots

NASA Astrophysics Data System (ADS)

Gołuński, Marcel; Wasiewicz, Piotr

2010-09-01

In this paper we explore the problem of communication and coordination in a team of intelligent game bots (aka embodied agents). It presents a tactical decision making system controlling the behavior of an autonomous bot followed by the concept of a team tactical decision making system controlling the team of intelligent bots. The algorithms to be introduced have been implemented in the Java language by means of Pogamut 2 framework, interfacing the bot logic with Unreal Tournament 2004 virtual environment.

Distributed Knowledge Base Systems for Diagnosis and Information Retrieval.

DTIC Science & Technology

1984-08-01

include Al. Some research has been done by our group and others on intelligent graphical aids, and in knowledgeable data -bases14 ’ 15, 1.3. Problem... data -base possibly mediated by an intelligent data -base assistant1 5’ 21. We will first describe the 1design agents , and then the phases of their...collection of design specialists will not be sufficient for the design task, and will, at least, need an intelligent data -base to keep track of the ongoing

Intelligence Collection within The Army of Northern Virginia during the American Civil War

DTIC Science & Technology

2016-03-01

philosopher Sun Tzu devoted an entire section of his book, The Art of War, to the “employment of secret agents.” He advised foreknowledge of the enemy, which...of the same intelligence premises written by Sun Tzu . In section 2, Perspective – (Think Like the Adversary), it called for intelligence analysts to...20 Sun Tzu , The Art of War, trans. Samuel B. Griffith (Oxford, England: Oxford University Press, 1963), 144-145. 21 Ibid., 149. 22 Joint

Applications of Multi-Agent Technology to Power Systems

NASA Astrophysics Data System (ADS)

Nagata, Takeshi

Currently, agents are focus of intense on many sub-fields of computer science and artificial intelligence. Agents are being used in an increasingly wide variety of applications. Many important computing applications such as planning, process control, communication networks and concurrent systems will benefit from using multi-agent system approach. A multi-agent system is a structure given by an environment together with a set of artificial agents capable to act on this environment. Multi-agent models are oriented towards interactions, collaborative phenomena, and autonomy. This article presents the applications of multi-agent technology to the power systems.

The predictive power of zero intelligence in financial markets

PubMed Central

Farmer, J. Doyne; Patelli, Paolo; Zovko, Ilija I.

2005-01-01

Standard models in economics stress the role of intelligent agents who maximize utility. However, there may be situations where constraints imposed by market institutions dominate strategic agent behavior. We use data from the London Stock Exchange to test a simple model in which minimally intelligent agents place orders to trade at random. The model treats the statistical mechanics of order placement, price formation, and the accumulation of revealed supply and demand within the context of the continuous double auction and yields simple laws relating order-arrival rates to statistical properties of the market. We test the validity of these laws in explaining cross-sectional variation for 11 stocks. The model explains 96% of the variance of the gap between the best buying and selling prices (the spread) and 76% of the variance of the price diffusion rate, with only one free parameter. We also study the market impact function, describing the response of quoted prices to the arrival of new orders. The nondimensional coordinates dictated by the model approximately collapse data from different stocks onto a single curve. This work is important from a practical point of view, because it demonstrates the existence of simple laws relating prices to order flows and, in a broader context, suggests there are circumstances where the strategic behavior of agents may be dominated by other considerations. PMID:15687505

A multilevel investigation of motivational cultural intelligence, organizational diversity climate, and cultural sales: evidence from U.S. real estate firms.

PubMed

Chen, Xiao-Ping; Liu, Dong; Portnoy, Rebecca

2012-01-01

Adopting a multilevel theoretical framework, the authors examined how motivational cultural intelligence influences individual cultural sales--the number of housing transactions occurring between people of different cultural origins. Data from 305 real estate agents employed at 26 real estate firms in the United States demonstrated that an individual's motivational cultural intelligence is positively related to his or her cultural sales. This positive relationship is enhanced by the firm's motivational cultural intelligence and diversity climate. The authors discuss the theoretical and practical implications of their findings in a workplace context that involves cross-cultural interpersonal interactions.

Artificial intelligence for optimal anemia management in end-stage renal disease.

PubMed

Brier, Michael E; Gaweda, Adam E

2016-08-01

Computational intelligence for the prediction of hemoglobin to guide the selection of erythropoiesis-stimulating agent dose results in improved anemia management. The models used for the prediction result from the use of individual patient data and help to increase the number of hemoglobin observations within the target range. The benefits of using these modeling techniques appear to be a decrease in erythropoiesis-stimulating agent use and a decrease in the number of transfusions. This study confirms the results of previous smaller studies and suggests that additional beneficial results may be achieved. Copyright © 2016 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

Learning of embodied interaction dynamics with recurrent neural networks: some exploratory experiments.

PubMed

Oubbati, Mohamed; Kord, Bahram; Koprinkova-Hristova, Petia; Palm, Günther

2014-04-01

The new tendency of artificial intelligence suggests that intelligence must be seen as a result of the interaction between brains, bodies and environments. This view implies that designing sophisticated behaviour requires a primary focus on how agents are functionally coupled to their environments. Under this perspective, we present early results with the application of reservoir computing as an efficient tool to understand how behaviour emerges from interaction. Specifically, we present reservoir computing models, that are inspired by imitation learning designs, to extract the essential components of behaviour that results from agent-environment interaction dynamics. Experimental results using a mobile robot are reported to validate the learning architectures.

Learning of embodied interaction dynamics with recurrent neural networks: some exploratory experiments

NASA Astrophysics Data System (ADS)

Oubbati, Mohamed; Kord, Bahram; Koprinkova-Hristova, Petia; Palm, Günther

2014-04-01

The new tendency of artificial intelligence suggests that intelligence must be seen as a result of the interaction between brains, bodies and environments. This view implies that designing sophisticated behaviour requires a primary focus on how agents are functionally coupled to their environments. Under this perspective, we present early results with the application of reservoir computing as an efficient tool to understand how behaviour emerges from interaction. Specifically, we present reservoir computing models, that are inspired by imitation learning designs, to extract the essential components of behaviour that results from agent-environment interaction dynamics. Experimental results using a mobile robot are reported to validate the learning architectures.

Using Intelligent System Approaches for Simulation of Electricity Markets

NASA Astrophysics Data System (ADS)

Hamagami, Tomoki

Significances and approaches of applying intelligent systems to artificial electricity market is discussed. In recent years, with the moving into restructuring of electric system in Japan, the deregulation for the electric market is progressing. The most major change of the market is a founding of JEPX (Japan Electric Power eXchange.) which is expected to help lower power bills through effective use of surplus electricity. The electricity market designates exchange of electric power between electric power suppliers (supplier agents) themselves. In the market, the goal of each supplier agents is to maximize its revenue for the entire trading period, and shows complex behavior, which can model by a multiagent platform. Using the multiagent simulations which have been studied as “artificial market" helps to predict the spot prices, to plan investments, and to discuss the rules of market. Moreover, intelligent system approaches provide for constructing more reasonable policies of each agents. This article, first, makes a brief summary of the electricity market in Japan and the studies of artificial markets. Then, a survey of tipical studies of artificial electricity market is listed. Through these topics, the future vision is presented for the studies.

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

Do Intelligent Robots Need Emotion?

PubMed

Pessoa, Luiz

2017-11-01

What is the place of emotion in intelligent robots? Researchers have advocated the inclusion of some emotion-related components in the information-processing architecture of autonomous agents. It is argued here that emotion needs to be merged with all aspects of the architecture: cognitive-emotional integration should be a key design principle. Copyright © 2017 Elsevier Ltd. All rights reserved.

Clustering and Profiling Students According to Their Interactions with an Intelligent Tutoring System Fostering Self-Regulated Learning

ERIC Educational Resources Information Center

Bouchet, Francois; Harley, Jason M.; Trevors, Gregory J.; Azevedo, Roger

2013-01-01

In this paper, we present the results obtained using a clustering algorithm (Expectation-Maximization) on data collected from 106 college students learning about the circulatory system with MetaTutor, an agent-based Intelligent Tutoring System (ITS) designed to foster self-regulated learning (SRL). The three extracted clusters were validated and…

Strategic Intelligence and National Security. A Selected Bibliography

DTIC Science & Technology

1991-09-01

McCann & Geoghegan, 1981. (MHI D810 S7R39 1981) Rendel , Alexander M. APPOIINTMENT IN CRETE: THE STORY OF A BRITISH AGENT. London: Wlngate, 1953. (MHI...UB250 I 57) Mathams, R.H. SUB ROSA: MEMOIRS OF AN AUSTRALIAN INTELLIGENCE ANALYST. Boston: Allen & Unwin, 1902. (UB251 A8M37) Phelps, Ruth H.; Englert

An Intelligent Agent Approach for Teaching Neural Networks Using LEGO[R] Handy Board Robots

ERIC Educational Resources Information Center

Imberman, Susan P.

2004-01-01

In this article we describe a project for an undergraduate artificial intelligence class. The project teaches neural networks using LEGO[R] handy board robots. Students construct robots with two motors and two photosensors. Photosensors provide readings that act as inputs for the neural network. Output values power the motors and maintain the…

Note-Taking within MetaTutor: Interactions between an Intelligent Tutoring System and Prior Knowledge on Note-Taking and Learning

ERIC Educational Resources Information Center

Trevors, Gregory; Duffy, Melissa; Azevedo, Roger

2014-01-01

Hypermedia learning environments (HLE) unevenly present new challenges and opportunities to learning processes and outcomes depending on learner characteristics and instructional supports. In this experimental study, we examined how one such HLE--MetaTutor, an intelligent, multi-agent tutoring system designed to scaffold cognitive and…

Combination of Multi-Agent Systems and Wireless Sensor Networks for the Monitoring of Cattle

PubMed Central

Barriuso, Alberto L.; De Paz, Juan F.; Lozano, Álvaro

2018-01-01

Precision breeding techniques have been widely used to optimize expenses and increase livestock yields. Notwithstanding, the joint use of heterogeneous sensors and artificial intelligence techniques for the simultaneous analysis or detection of different problems that cattle may present has not been addressed. This study arises from the necessity to obtain a technological tool that faces this state of the art limitation. As novelty, this work presents a multi-agent architecture based on virtual organizations which allows to deploy a new embedded agent model in computationally limited autonomous sensors, making use of the Platform for Automatic coNstruction of orGanizations of intElligent Agents (PANGEA). To validate the proposed platform, different studies have been performed, where parameters specific to each animal are studied, such as physical activity, temperature, estrus cycle state and the moment in which the animal goes into labor. In addition, a set of applications that allow farmers to remotely monitor the livestock have been developed. PMID:29301310

Combination of Multi-Agent Systems and Wireless Sensor Networks for the Monitoring of Cattle.

PubMed

Barriuso, Alberto L; Villarrubia González, Gabriel; De Paz, Juan F; Lozano, Álvaro; Bajo, Javier

2018-01-02

Precision breeding techniques have been widely used to optimize expenses and increase livestock yields. Notwithstanding, the joint use of heterogeneous sensors and artificial intelligence techniques for the simultaneous analysis or detection of different problems that cattle may present has not been addressed. This study arises from the necessity to obtain a technological tool that faces this state of the art limitation. As novelty, this work presents a multi-agent architecture based on virtual organizations which allows to deploy a new embedded agent model in computationally limited autonomous sensors, making use of the Platform for Automatic coNstruction of orGanizations of intElligent Agents (PANGEA). To validate the proposed platform, different studies have been performed, where parameters specific to each animal are studied, such as physical activity, temperature, estrus cycle state and the moment in which the animal goes into labor. In addition, a set of applications that allow farmers to remotely monitor the livestock have been developed.

A cognitive robotic system based on the Soar cognitive architecture for mobile robot navigation, search, and mapping missions

NASA Astrophysics Data System (ADS)

Hanford, Scott D.

Most unmanned vehicles used for civilian and military applications are remotely operated or are designed for specific applications. As these vehicles are used to perform more difficult missions or a larger number of missions in remote environments, there will be a great need for these vehicles to behave intelligently and autonomously. Cognitive architectures, computer programs that define mechanisms that are important for modeling and generating domain-independent intelligent behavior, have the potential for generating intelligent and autonomous behavior in unmanned vehicles. The research described in this presentation explored the use of the Soar cognitive architecture for cognitive robotics. The Cognitive Robotic System (CRS) has been developed to integrate software systems for motor control and sensor processing with Soar for unmanned vehicle control. The CRS has been tested using two mobile robot missions: outdoor navigation and search in an indoor environment. The use of the CRS for the outdoor navigation mission demonstrated that a Soar agent could autonomously navigate to a specified location while avoiding obstacles, including cul-de-sacs, with only a minimal amount of knowledge about the environment. While most systems use information from maps or long-range perceptual capabilities to avoid cul-de-sacs, a Soar agent in the CRS was able to recognize when a simple approach to avoiding obstacles was unsuccessful and switch to a different strategy for avoiding complex obstacles. During the indoor search mission, the CRS autonomously and intelligently searches a building for an object of interest and common intersection types. While searching the building, the Soar agent builds a topological map of the environment using information about the intersections the CRS detects. The agent uses this topological model (along with Soar's reasoning, planning, and learning mechanisms) to make intelligent decisions about how to effectively search the building. Once the object of interest has been detected, the Soar agent uses the topological map to make decisions about how to efficiently return to the location where the mission began. Additionally, the CRS can send an email containing step-by-step directions using the intersections in the environment as landmarks that describe a direct path from the mission's start location to the object of interest. The CRS has displayed several characteristics of intelligent behavior, including reasoning, planning, learning, and communication of learned knowledge, while autonomously performing two missions. The CRS has also demonstrated how Soar can be integrated with common robotic motor and perceptual systems that complement the strengths of Soar for unmanned vehicles and is one of the few systems that use perceptual systems such as occupancy grid, computer vision, and fuzzy logic algorithms with cognitive architectures for robotics. The use of these perceptual systems to generate symbolic information about the environment during the indoor search mission allowed the CRS to use Soar's planning and learning mechanisms, which have rarely been used by agents to control mobile robots in real environments. Additionally, the system developed for the indoor search mission represents the first known use of a topological map with a cognitive architecture on a mobile robot. The ability to learn both a topological map and production rules allowed the Soar agent used during the indoor search mission to make intelligent decisions and behave more efficiently as it learned about its environment. While the CRS has been applied to two different missions, it has been developed with the intention that it be extended in the future so it can be used as a general system for mobile robot control. The CRS can be expanded through the addition of new sensors and sensor processing algorithms, development of Soar agents with more production rules, and the use of new architectural mechanisms in Soar.

E-Learning Agents

ERIC Educational Resources Information Center

Gregg, Dawn G.

2007-01-01

Purpose: The purpose of this paper is to illustrate the advantages of using intelligent agents to facilitate the location and customization of appropriate e-learning resources and to foster collaboration in e-learning environments. Design/methodology/approach: This paper proposes an e-learning environment that can be used to provide customized…

An architecture and protocol for communications satellite constellations regarded as multi-agent systems

NASA Technical Reports Server (NTRS)

Lindley, Craig A.

1995-01-01

This paper presents an architecture for satellites regarded as intercommunicating agents. The architecture is based upon a postmodern paradigm of artificial intelligence in which represented knowledge is regarded as text, inference procedures are regarded as social discourse and decision making conventions and the semantics of representations are grounded in the situated behaviour and activity of agents. A particular protocol is described for agent participation in distributed search and retrieval operations conducted as joint activities.

B-tree search reinforcement learning for model based intelligent agent

NASA Astrophysics Data System (ADS)

Bhuvaneswari, S.; Vignashwaran, R.

2013-03-01

Agents trained by learning techniques provide a powerful approximation of active solutions for naive approaches. In this study using B - Trees implying reinforced learning the data search for information retrieval is moderated to achieve accuracy with minimum search time. The impact of variables and tactics applied in training are determined using reinforcement learning. Agents based on these techniques perform satisfactory baseline and act as finite agents based on the predetermined model against competitors from the course.

Modeling Environmental Impacts on Cognitive Performance for Artificially Intelligent Entities

DTIC Science & Technology

2017-06-01

of the agent behavior model is presented in a military-relevant virtual game environment. We then outline a quantitative approach to test the agent...relevant virtual game environment. We then outline a quantitative approach to test the agent behavior model within the virtual environment. Results show...x Game View of Hot Environment Condition Displaying Total “f” Cost for Each Searched Waypoint Node

Humans and Autonomy: Implications of Shared Decision Making for Military Operations

DTIC Science & Technology

2017-01-01

and machine learning transparency are identified as future research opportunities. 15. SUBJECT TERMS autonomy, human factors, intelligent agents...network as either the mission changes or an agent becomes disabled (DSB 2012). Fig. 2 Control structures for human agent teams. Robots without tools... learning (ML) algorithms monitor progress. However, operators have final executive authority; they are able to tweak the plan or choose an option

Autonomous intelligent cars: proof that the EPSRC Principles are future-proof

NASA Astrophysics Data System (ADS)

de Cock Buning, Madeleine; de Bruin, Roeland

2017-07-01

Principle 2 of the EPSRC's principles of robotics (AISB workshop on Principles of Robotics, 2016) proves to be future proof when applied to the current state of the art of law and technology surrounding autonomous intelligent cars (AICs). Humans, not AICS, are responsible agents. AICs should be designed; operated as far as is practicable to comply with existing laws and fundamental rights and freedoms, including privacy by design. It will show that some legal questions arising from autonomous intelligent driving technology can be answered by the technology itself.

Intelligence with representation.

PubMed

Steels, Luc

2003-10-15

Behaviour-based robotics has always been inspired by earlier cybernetics work such as that of W. Grey Walter. It emphasizes that intelligence can be achieved without the kinds of representations common in symbolic AI systems. The paper argues that such representations might indeed not be needed for many aspects of sensory-motor intelligence but become a crucial issue when bootstrapping to higher levels of cognition. It proposes a scenario in the form of evolutionary language games by which embodied agents develop situated grounded representations adapted to their needs and the conventions emerging in the population.

CATS-based Agents That Err

NASA Technical Reports Server (NTRS)

Callantine, Todd J.

2002-01-01

This report describes preliminary research on intelligent agents that make errors. Such agents are crucial to the development of novel agent-based techniques for assessing system safety. The agents extend an agent architecture derived from the Crew Activity Tracking System that has been used as the basis for air traffic controller agents. The report first reviews several error taxonomies. Next, it presents an overview of the air traffic controller agents, then details several mechanisms for causing the agents to err in realistic ways. The report presents a performance assessment of the error-generating agents, and identifies directions for further research. The research was supported by the System-Wide Accident Prevention element of the FAA/NASA Aviation Safety Program.

Help Helps, but Only so Much: Research on Help Seeking with Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Aleven, Vincent; Roll, Ido; McLaren, Bruce M.; Koedinger, Kenneth R.

2016-01-01

Help seeking is an important process in self-regulated learning (SRL). It may influence learning with intelligent tutoring systems (ITSs), because many ITSs provide help, often at the student's request. The Help Tutor was a tutor agent that gave in-context, real-time feedback on students' help-seeking behavior, as they were learning with an ITS.…

Searching for Order Within Chaos: Complexity Theorys Implications to Intelligence Support During Joint Operational Planning

DTIC Science & Technology

2017-06-09

structures constantly arise in firefights and skirmishes on the battlefield. Source: Andrew Ilachinski, Artificial War: Multiagent- Based Simulation of...Alternative Methods of Analysis and Innovative Organizational Structures .” Conference, Rome, Italy March 31-April 2. ...Intelligence Analysis, Joint Operational Planning, Cellular Automata, Agent- Based Modeling 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18

Devices development and techniques research for space life sciences

NASA Astrophysics Data System (ADS)

Zhang, A.; Liu, B.; Zheng, C.

The development process and the status quo of the devices and techniques for space life science in China and the main research results in this field achieved by Shanghai Institute of Technical Physics SITP CAS are reviewed concisely in this paper On the base of analyzing the requirements of devices and techniques for supporting space life science experiments and researches one designment idea of developing different intelligent modules with professional function standard interface and easy to be integrated into system is put forward and the realization method of the experiment system with intelligent distributed control based on the field bus are discussed in three hierarchies Typical sensing or control function cells with certain self-determination control data management and communication abilities are designed and developed which are called Intelligent Agents Digital hardware network system which are consisted of the distributed Agents as the intelligent node is constructed with the normative opening field bus technology The multitask and real-time control application softwares are developed in the embedded RTOS circumstance which is implanted into the system hardware and space life science experiment system platform with characteristic of multitasks multi-courses professional and instant integration will be constructed

Integrated Biological Warfare Technology Platform (IBWTP). Intelligent Software Supporting Situation Awareness, Response, and Operations

DTIC Science & Technology

2007-01-01

15 4.2.3. Users of Systems for Combating Biological Warfare ................................ 16 4.2.4...21 4.3.1. Existing Biosurveillance Systems .............................................................. 22 4.3.2. Automatic Integration...74 6.4.4. Multi-Agent System Management System (MMS).................................... 75 6.4.5. Agent Glossary

Research-Based Design of Pedagogical Agent Roles: A Review, Progress, and Recommendations

ERIC Educational Resources Information Center

Kim, Yanghee; Baylor, Amy L.

2016-01-01

In this paper we review the contribution of our original work titled "Simulating Instructional Roles Through Pedagogical Agents" published in the "International Journal of Artificial Intelligence and Education" (Baylor and Kim in "Computers and Human Behavior," 25(2), 450-457, 2005). Our original work operationalized…

Cooperating intelligent systems

NASA Technical Reports Server (NTRS)

Rochowiak, Daniel

1989-01-01

Some of the issues connected to the development of a bureaucratic system are discussed. Emphasis is on a layer multiagent approach to distributed artificial intelligence (DAI). The division of labor in a bureaucracy is considered. The bureaucratic model seems to be a fertile model for further examination since it allows for the growth and change of system components and system protocols and rules. The first part of implementing the system would be the construction of a frame based reasoner and the appropriate B-agents and E-agents. The agents themselves should act as objects and the E-objects in particular should have the capability of taking on a different role. No effort was made to address the problems of automated failure recovery, problem decomposition, or implementation. Instead what has been achieved is a framework that can be developed in several distinct ways, and which provides a core set of metaphors and issues for further research.

Space/ground systems as cooperating agents

NASA Technical Reports Server (NTRS)

Grant, T. J.

1994-01-01

Within NASA and the European Space Agency (ESA) it is agreed that autonomy is an important goal for the design of future spacecraft and that this requires on-board artificial intelligence. NASA emphasizes deep space and planetary rover missions, while ESA considers on-board autonomy as an enabling technology for missions that must cope with imperfect communications. ESA's attention is on the space/ground system. A major issue is the optimal distribution of intelligent functions within the space/ground system. This paper describes the multi-agent architecture for space/ground systems (MAASGS) which would enable this issue to be investigated. A MAASGS agent may model a complete spacecraft, a spacecraft subsystem or payload, a ground segment, a spacecraft control system, a human operator, or an environment. The MAASGS architecture has evolved through a series of prototypes. The paper recommends that the MAASGS architecture should be implemented in the operational Dutch Utilization Center.

Can Artificial Intelligences Suffer from Mental Illness? A Philosophical Matter to Consider.

PubMed

Ashrafian, Hutan

2017-04-01

The potential for artificial intelligences and robotics in achieving the capacity of consciousness, sentience and rationality offers the prospect that these agents have minds. If so, then there may be a potential for these minds to become dysfunctional, or for artificial intelligences and robots to suffer from mental illness. The existence of artificially intelligent psychopathology can be interpreted through the philosophical perspectives of mental illness. This offers new insights into what it means to have either robot or human mental disorders, but may also offer a platform on which to examine the mechanisms of biological or artificially intelligent psychiatric disease. The possibility of mental illnesses occurring in artificially intelligent individuals necessitates the consideration that at some level, they may have achieved a mental capability of consciousness, sentience and rationality such that they can subsequently become dysfunctional. The deeper philosophical understanding of these conditions in mankind and artificial intelligences might therefore offer reciprocal insights into mental health and mechanisms that may lead to the prevention of mental dysfunction.

Active and intelligent packaging systems for a modern society.

PubMed

Realini, Carolina E; Marcos, Begonya

2014-11-01

Active and intelligent packaging systems are continuously evolving in response to growing challenges from a modern society. This article reviews: (1) the different categories of active and intelligent packaging concepts and currently available commercial applications, (2) latest packaging research trends and innovations, and (3) the growth perspectives of the active and intelligent packaging market. Active packaging aiming at extending shelf life or improving safety while maintaining quality is progressing towards the incorporation of natural active agents into more sustainable packaging materials. Intelligent packaging systems which monitor the condition of the packed food or its environment are progressing towards more cost-effective, convenient and integrated systems to provide innovative packaging solutions. Market growth is expected for active packaging with leading shares for moisture absorbers, oxygen scavengers, microwave susceptors and antimicrobial packaging. The market for intelligent packaging is also promising with strong gains for time-temperature indicator labels and advancements in the integration of intelligent concepts into packaging materials. Copyright © 2014 Elsevier Ltd. All rights reserved.

Situation awareness-based agent transparency for human-autonomy teaming effectiveness

NASA Astrophysics Data System (ADS)

Chen, Jessie Y. C.; Barnes, Michael J.; Wright, Julia L.; Stowers, Kimberly; Lakhmani, Shan G.

2017-05-01

We developed the Situation awareness-based Agent Transparency (SAT) model to support human operators' situation awareness of the mission environment through teaming with intelligent agents. The model includes the agent's current actions and plans (Level 1), its reasoning process (Level 2), and its projection of future outcomes (Level 3). Human-inthe-loop simulation experiments have been conducted (Autonomous Squad Member and IMPACT) to illustrate the utility of the model for human-autonomy team interface designs. Across studies, the results consistently showed that human operators' task performance improved as the agents became more transparent. They also perceived transparent agents as more trustworthy.

Exploration of Metaphorical and Contextual Affect Sensing in a Virtual Improvisational Drama

NASA Astrophysics Data System (ADS)

Zhang, Li

Real-time affect detection from open-ended text-based dialogue is challenging but essential for the building of effective intelligent user interfaces. In this paper, we report updated developments of an affect detection model from text, including affect detection from one particular type of metaphorical affective expression (cooking metaphor) and affect detection based on context. The overall affect detection model has been embedded in an intelligent conversational AI agent interacting with human users under loose scenarios. Evaluation for the updated affect detection component is also provided. Our work contributes to the conference themes on engagement and emotion, interactions in games, storytelling and narrative in education, and virtual characters/agents development.

NICA: Natural Interaction with a Caring Agent

NASA Astrophysics Data System (ADS)

de Carolis, Berardina; Mazzotta, Irene; Novielli, Nicole

Ambient Intelligence solutions may provide a great opportunity for elderly people to live longer at home. Assistance and care are delegated to the intelligence embedded in the environment. However, besides considering service-oriented response to the user needs, the assistance has to take into account the establishment of social relations. We propose the use of a robot NICA (as the name of the project Natural Interaction with a Caring Agent) acting as a caring assistant that provides a social interface with the smart home services. In this paper, we introduce the general architecture of the robot's "mind" and then we focus on the need to properly react to affective and socially oriented situations.

Effective Coordination of Multiple Intelligent Agents for Command and Control

DTIC Science & Technology

2003-09-01

System Architecture As an initial problem domain in E - commerce , we chose collective book purchasing. In the university setting, relatively large numbers... a coalition server, an auctioneer agent, a set of supplier agents, and a web- based interface 9 for end users. The system is based on a simple...buyers are able to request and sellers to respond to a list of items, within a particular category. Sellers present

Development and application of a real-time testbed for multiagent system interoperability: A case study on hierarchical microgrid control

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

Cintuglu, Mehmet Hazar; Youssef, Tarek; Mohammed, Osama A.

This article presents the development and application of a real-time testbed for multiagent system interoperability. As utility independent private microgrids are installed constantly, standardized interoperability frameworks are required to define behavioral models of the individual agents for expandability and plug-and-play operation. In this paper, we propose a comprehensive hybrid agent framework combining the foundation for intelligent physical agents (FIPA), IEC 61850, and data distribution service (DDS) standards. The IEC 61850 logical node concept is extended using FIPA based agent communication language (ACL) with application specific attributes and deliberative behavior modeling capability. The DDS middleware is adopted to enable a real-timemore » publisher-subscriber interoperability mechanism between platforms. The proposed multi-agent framework was validated in a laboratory based testbed involving developed intelligent electronic device (IED) prototypes and actual microgrid setups. Experimental results were demonstrated for both decentralized and distributed control approaches. Secondary and tertiary control levels of a microgrid were demonstrated for decentralized hierarchical control case study. A consensus-based economic dispatch case study was demonstrated as a distributed control example. Finally, it was shown that the developed agent platform is industrially applicable for actual smart grid field deployment.« less

Development and application of a real-time testbed for multiagent system interoperability: A case study on hierarchical microgrid control

DOE PAGES

Cintuglu, Mehmet Hazar; Youssef, Tarek; Mohammed, Osama A.

2016-08-10

This article presents the development and application of a real-time testbed for multiagent system interoperability. As utility independent private microgrids are installed constantly, standardized interoperability frameworks are required to define behavioral models of the individual agents for expandability and plug-and-play operation. In this paper, we propose a comprehensive hybrid agent framework combining the foundation for intelligent physical agents (FIPA), IEC 61850, and data distribution service (DDS) standards. The IEC 61850 logical node concept is extended using FIPA based agent communication language (ACL) with application specific attributes and deliberative behavior modeling capability. The DDS middleware is adopted to enable a real-timemore » publisher-subscriber interoperability mechanism between platforms. The proposed multi-agent framework was validated in a laboratory based testbed involving developed intelligent electronic device (IED) prototypes and actual microgrid setups. Experimental results were demonstrated for both decentralized and distributed control approaches. Secondary and tertiary control levels of a microgrid were demonstrated for decentralized hierarchical control case study. A consensus-based economic dispatch case study was demonstrated as a distributed control example. Finally, it was shown that the developed agent platform is industrially applicable for actual smart grid field deployment.« less

Reinforcement learning in supply chains.

PubMed

Valluri, Annapurna; North, Michael J; Macal, Charles M

2009-10-01

Effective management of supply chains creates value and can strategically position companies. In practice, human beings have been found to be both surprisingly successful and disappointingly inept at managing supply chains. The related fields of cognitive psychology and artificial intelligence have postulated a variety of potential mechanisms to explain this behavior. One of the leading candidates is reinforcement learning. This paper applies agent-based modeling to investigate the comparative behavioral consequences of three simple reinforcement learning algorithms in a multi-stage supply chain. For the first time, our findings show that the specific algorithm that is employed can have dramatic effects on the results obtained. Reinforcement learning is found to be valuable in multi-stage supply chains with several learning agents, as independent agents can learn to coordinate their behavior. However, learning in multi-stage supply chains using these postulated approaches from cognitive psychology and artificial intelligence take extremely long time periods to achieve stability which raises questions about their ability to explain behavior in real supply chains. The fact that it takes thousands of periods for agents to learn in this simple multi-agent setting provides new evidence that real world decision makers are unlikely to be using strict reinforcement learning in practice.

Reusable Autonomy

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Obenschain, Arthur F. (Technical Monitor)

2002-01-01

Currently, spacecraft ground systems have a well defined and somewhat standard architecture and operations concept. Based on domain analysis studies of various control centers conducted over the years it is clear that ground systems have core capabilities and functionality that are common across all ground systems. This observation alone supports the realization of reuse. Additionally, spacecraft ground systems are increasing in their ability to do things autonomously. They are being engineered using advanced expert systems technology to provide automated support for operators. A clearer understanding of the possible roles of agent technology is advancing the prospects of greater autonomy for these systems. Many of their functional and management tasks are or could be supported by applied agent technology, the dynamics of the ground system's infrastructure could be monitored by agents, there are intelligent agent-based approaches to user-interfaces, etc. The premise of this paper is that the concepts associated with software reuse, applicable in consideration of classically-engineered ground systems, can be updated to address their application in highly agent-based realizations of future ground systems. As a somewhat simplified example consider the following situation, involving human agents in a ground system context. Let Group A of controllers be working on Mission X. They are responsible for the command, control and health and safety of the Mission X spacecraft. Let us suppose that mission X successfully completes it mission and is turned off. Group A could be dispersed or perhaps move to another Mission Y. In this case there would be reuse of the human agents from Mission X to Mission Y. The Group A agents perform their well-understood functions in a somewhat but related context. There will be a learning or familiarization process that the group A agents go through to make the new context, determined by the new Mission Y, understood. This simplified scenario highlights some of the major issues that need to be addressed when considering the situation where Group A is composed of software-based agents (not their human counterparts) and they migrate from one mission support system to another. This paper will address: - definition of an agent architecture appropriate to support reuse; - identification of non-mission-specific agent capabilities required; - appropriate knowledge representation schemes for mission-specific knowledge; - agent interface with mission-specific knowledge (a type of Learning); development of a fully-operational group of cooperative software agents for ground system support; architecture and operation of a repository of reusable agents that could be the source of intelligent components for realizing an autonomous (or nearly autonomous) agent-based ground system, and an agent-based approach to repository management and operation (an intelligent interface for human use of the repository in a ground-system development activity).

Autonomy: Life and Being

NASA Astrophysics Data System (ADS)

Williams, Mary-Anne

This paper uses robot experience to explore key concepts of autonomy, life and being. Unfortunately, there are no widely accepted definitions of autonomy, life or being. Using a new cognitive agent architecture we argue that autonomy is a key ingredient for both life and being, and set about exploring autonomy as a concept and a capability. Some schools of thought regard autonomy as the key characteristic that distinguishes a system from an agent; agents are systems with autonomy, but rarely is a definition of autonomy provided. Living entities are autonomous systems, and autonomy is vital to life. Intelligence presupposes autonomy too; what would it mean for a system to be intelligent but not exhibit any form of genuine autonomy. Our philosophical, scientific and legal understanding of autonomy and its implications is immature and as a result progress towards designing, building, managing, exploiting and regulating autonomous systems is retarded. In response we put forward a framework for exploring autonomy as a concept and capability based on a new cognitive architecture. Using this architecture tools and benchmarks can be developed to analyze and study autonomy in its own right as a means to further our understanding of autonomous systems, life and being. This endeavor would lead to important practical benefits for autonomous systems design and help determine the legal status of autonomous systems. It is only with a new enabling understanding of autonomy that the dream of Artificial Intelligence and Artificial Life can be realized. We argue that designing systems with genuine autonomy capabilities can be achieved by focusing on agent experiences of being rather than attempting to encode human experiences as symbolic knowledge and know-how in the artificial agents we build.

Modelling of internal architecture of kinesin nanomotor as a machine language.

PubMed

Khataee, H R; Ibrahim, M Y

2012-09-01

Kinesin is a protein-based natural nanomotor that transports molecular cargoes within cells by walking along microtubules. Kinesin nanomotor is considered as a bio-nanoagent which is able to sense the cell through its sensors (i.e. its heads and tail), make the decision internally and perform actions on the cell through its actuator (i.e. its motor domain). The study maps the agent-based architectural model of internal decision-making process of kinesin nanomotor to a machine language using an automata algorithm. The applied automata algorithm receives the internal agent-based architectural model of kinesin nanomotor as a deterministic finite automaton (DFA) model and generates a regular machine language. The generated regular machine language was acceptable by the architectural DFA model of the nanomotor and also in good agreement with its natural behaviour. The internal agent-based architectural model of kinesin nanomotor indicates the degree of autonomy and intelligence of the nanomotor interactions with its cell. Thus, our developed regular machine language can model the degree of autonomy and intelligence of kinesin nanomotor interactions with its cell as a language. Modelling of internal architectures of autonomous and intelligent bio-nanosystems as machine languages can lay the foundation towards the concept of bio-nanoswarms and next phases of the bio-nanorobotic systems development.

A heterogeneous artificial stock market model can benefit people against another financial crisis

PubMed Central

2018-01-01

This paper presents results of an artificial stock market and tries to make it more consistent with the statistical features of real stock data. Based on the SFI-ASM, a novel model is proposed to make agents more close to the real world. Agents are divided into four kinds in terms of different learning speeds, strategy-sizes, utility functions, and level of intelligence; and a crucial parameter has been found to ensure system stability. So, some parameters are appended to make the model which contains zero-intelligent and less-intelligent agents run steadily. Moreover, considering real stock markets change violently due to the financial crisis; the real stock markets are divided into two segments, before the financial crisis and after it. The optimal modified model before the financial crisis fails to replicate the statistical features of the real market after the financial crisis. Then, the optimal model after the financial crisis is shown. The experiments indicate that the optimal model after the financial crisis is able to replicate several of real market phenomena, including the first-order autocorrelation, kurtosis, standard deviation of yield series and first-order autocorrelation of yield square. We point out that there is a structural change in stock markets after the financial crisis, which can benefit people forecast the financial crisis. PMID:29912893

Energy Logic (EL): a novel fusion engine of multi-modality multi-agent data/information fusion for intelligent surveillance systems

NASA Astrophysics Data System (ADS)

Rababaah, Haroun; Shirkhodaie, Amir

2009-04-01

The rapidly advancing hardware technology, smart sensors and sensor networks are advancing environment sensing. One major potential of this technology is Large-Scale Surveillance Systems (LS3) especially for, homeland security, battlefield intelligence, facility guarding and other civilian applications. The efficient and effective deployment of LS3 requires addressing number of aspects impacting the scalability of such systems. The scalability factors are related to: computation and memory utilization efficiency, communication bandwidth utilization, network topology (e.g., centralized, ad-hoc, hierarchical or hybrid), network communication protocol and data routing schemes; and local and global data/information fusion scheme for situational awareness. Although, many models have been proposed to address one aspect or another of these issues but, few have addressed the need for a multi-modality multi-agent data/information fusion that has characteristics satisfying the requirements of current and future intelligent sensors and sensor networks. In this paper, we have presented a novel scalable fusion engine for multi-modality multi-agent information fusion for LS3. The new fusion engine is based on a concept we call: Energy Logic. Experimental results of this work as compared to a Fuzzy logic model strongly supported the validity of the new model and inspired future directions for different levels of fusion and different applications.

A heterogeneous artificial stock market model can benefit people against another financial crisis.

PubMed

Yang, Haijun; Chen, Shuheng

2018-01-01

This paper presents results of an artificial stock market and tries to make it more consistent with the statistical features of real stock data. Based on the SFI-ASM, a novel model is proposed to make agents more close to the real world. Agents are divided into four kinds in terms of different learning speeds, strategy-sizes, utility functions, and level of intelligence; and a crucial parameter has been found to ensure system stability. So, some parameters are appended to make the model which contains zero-intelligent and less-intelligent agents run steadily. Moreover, considering real stock markets change violently due to the financial crisis; the real stock markets are divided into two segments, before the financial crisis and after it. The optimal modified model before the financial crisis fails to replicate the statistical features of the real market after the financial crisis. Then, the optimal model after the financial crisis is shown. The experiments indicate that the optimal model after the financial crisis is able to replicate several of real market phenomena, including the first-order autocorrelation, kurtosis, standard deviation of yield series and first-order autocorrelation of yield square. We point out that there is a structural change in stock markets after the financial crisis, which can benefit people forecast the financial crisis.

Development of a software tool using deterministic logic for the optimization of cochlear implant processor programming.

PubMed

Govaerts, Paul J; Vaerenberg, Bart; De Ceulaer, Geert; Daemers, Kristin; De Beukelaer, Carina; Schauwers, Karen

2010-08-01

An intelligent agent, Fitting to Outcomes eXpert, was developed to optimize and automate Cochlear implant (CI) programming. The current article describes the rationale, development, and features of this tool. Cochlear implant fitting is a time-consuming procedure to define the value of a subset of the available electric parameters based primarily on behavioral responses. It is comfort-driven with high intraindividual and interindividual variability both with respect to the patient and to the clinician. Its validity in terms of process control can be questioned. Good clinical practice would require an outcome-driven approach. An intelligent agent may help solve the complexity of addressing more electric parameters based on a range of outcome measures. A software application was developed that consists of deterministic rules that analyze the map settings in the processor together with psychoacoustic test results (audiogram, A(section sign)E phoneme discrimination, A(section sign)E loudness scaling, speech audiogram) obtained with that map. The rules were based on the daily clinical practice and the expertise of the CI programmers. The data transfer to and from this agent is either manual or through seamless digital communication with the CI fitting database and the psychoacoustic test suite. It recommends and executes modifications to the map settings to improve the outcome. Fitting to Outcomes eXpert is an operational intelligent agent, the principles of which are described. Its development and modes of operation are outlined, and a case example is given. Fitting to Outcomes eXpert is in use for more than a year now and seems to be capable to improve the measured outcome. It is argued that this novel tool allows a systematic approach focusing on outcome, reducing the fitting time, and improving the quality of fitting. It introduces principles of artificial intelligence in the process of CI fitting.

Scalable sensor management for automated fusion and tactical reconnaissance

NASA Astrophysics Data System (ADS)

Walls, Thomas J.; Wilson, Michael L.; Partridge, Darin C.; Haws, Jonathan R.; Jensen, Mark D.; Johnson, Troy R.; Petersen, Brad D.; Sullivan, Stephanie W.

2013-05-01

The capabilities of tactical intelligence, surveillance, and reconnaissance (ISR) payloads are expanding from single sensor imagers to integrated systems-of-systems architectures. Increasingly, these systems-of-systems include multiple sensing modalities that can act as force multipliers for the intelligence analyst. Currently, the separate sensing modalities operate largely independent of one another, providing a selection of operating modes but not an integrated intelligence product. We describe here a Sensor Management System (SMS) designed to provide a small, compact processing unit capable of managing multiple collaborative sensor systems on-board an aircraft. Its purpose is to increase sensor cooperation and collaboration to achieve intelligent data collection and exploitation. The SMS architecture is designed to be largely sensor and data agnostic and provide flexible networked access for both data providers and data consumers. It supports pre-planned and ad-hoc missions, with provisions for on-demand tasking and updates from users connected via data links. Management of sensors and user agents takes place over standard network protocols such that any number and combination of sensors and user agents, either on the local network or connected via data link, can register with the SMS at any time during the mission. The SMS provides control over sensor data collection to handle logging and routing of data products to subscribing user agents. It also supports the addition of algorithmic data processing agents for feature/target extraction and provides for subsequent cueing from one sensor to another. The SMS architecture was designed to scale from a small UAV carrying a limited number of payloads to an aircraft carrying a large number of payloads. The SMS system is STANAG 4575 compliant as a removable memory module (RMM) and can act as a vehicle specific module (VSM) to provide STANAG 4586 compliance (level-3 interoperability) to a non-compliant sensor system. The SMS architecture will be described and results from several flight tests and simulations will be shown.

A Distributed Intelligent E-Learning System

ERIC Educational Resources Information Center

Kristensen, Terje

2016-01-01

An E-learning system based on a multi-agent (MAS) architecture combined with the Dynamic Content Manager (DCM) model of E-learning, is presented. We discuss the benefits of using such a multi-agent architecture. Finally, the MAS architecture is compared with a pure service-oriented architecture (SOA). This MAS architecture may also be used within…

A Novel Framework for Characterizing Exposure-Related Behaviors Using Agent-Based Models Embedded with Needs-Based Artificial Intelligence (CSSSA2016)

EPA Science Inventory

Descriptions of where and how individuals spend their time are important for characterizing exposures to chemicals in consumer products and in indoor environments. Herein we create an agent-based model (ABM) that is able to simulate longitudinal patterns in behaviors. By basing o...

Intelligent Agents for Design and Synthesis Environments: My Summary

NASA Technical Reports Server (NTRS)

Norvig, Peter

1999-01-01

This presentation gives a summary of intelligent agents for design synthesis environments. We'll start with the conclusions, and work backwards to justify them. First, an important assumption is that agents (whatever they are) are good for software engineering. This is especially true for software that operates in an uncertain, changing environment. The "real world" of physical artifacts is like that: uncertain in what we can measure, changing in that things are always breaking down, and we must interact with non-software entities. The second point is that software engineering techniques can contribute to good design. There may have been a time when we wanted to build simple artifacts containing little or no software. But modern aircraft and spacecraft are complex, and rely on a great deal of software. So better software engineering leads to better designed artifacts, especially when we are designing a series of related artifacts and can amortize the costs of software development. The third point is that agents are especially useful for design tasks, above and beyond their general usefulness for software engineering, and the usefulness of software engineering to design.

Hybrid neural intelligent system to predict business failure in small-to-medium-size enterprises.

PubMed

Borrajo, M Lourdes; Baruque, Bruno; Corchado, Emilio; Bajo, Javier; Corchado, Juan M

2011-08-01

During the last years there has been a growing need of developing innovative tools that can help small to medium sized enterprises to predict business failure as well as financial crisis. In this study we present a novel hybrid intelligent system aimed at monitoring the modus operandi of the companies and predicting possible failures. This system is implemented by means of a neural-based multi-agent system that models the different actors of the companies as agents. The core of the multi-agent system is a type of agent that incorporates a case-based reasoning system and automates the business control process and failure prediction. The stages of the case-based reasoning system are implemented by means of web services: the retrieval stage uses an innovative weighted voting summarization of self-organizing maps ensembles-based method and the reuse stage is implemented by means of a radial basis function neural network. An initial prototype was developed and the results obtained related to small and medium enterprises in a real scenario are presented.

Design of a Two-level Adaptive Multi-Agent System for Malaria Vectors driven by an ontology

PubMed Central

Koum, Guillaume; Yekel, Augustin; Ndifon, Bengyella; Etang, Josiane; Simard, Frédéric

2007-01-01

Background The understanding of heterogeneities in disease transmission dynamics as far as malaria vectors are concerned is a big challenge. Many studies while tackling this problem don't find exact models to explain the malaria vectors propagation. Methods To solve the problem we define an Adaptive Multi-Agent System (AMAS) which has the property to be elastic and is a two-level system as well. This AMAS is a dynamic system where the two levels are linked by an Ontology which allows it to function as a reduced system and as an extended system. In a primary level, the AMAS comprises organization agents and in a secondary level, it is constituted of analysis agents. Its entry point, a User Interface Agent, can reproduce itself because it is given a minimum of background knowledge and it learns appropriate "behavior" from the user in the presence of ambiguous queries and from other agents of the AMAS in other situations. Results Some of the outputs of our system present a series of tables, diagrams showing some factors like Entomological parameters of malaria transmission, Percentages of malaria transmission per malaria vectors, Entomological inoculation rate. Many others parameters can be produced by the system depending on the inputted data. Conclusion Our approach is an intelligent one which differs from statistical approaches that are sometimes used in the field. This intelligent approach aligns itself with the distributed artificial intelligence. In terms of fight against malaria disease our system offers opportunities of reducing efforts of human resources who are not obliged to cover the entire territory while conducting surveys. Secondly the AMAS can determine the presence or the absence of malaria vectors even when specific data have not been collected in the geographical area. In the difference of a statistical technique, in our case the projection of the results in the field can sometimes appeared to be more general. PMID:17605778

Simulation-based intelligent robotic agent for Space Station Freedom

NASA Technical Reports Server (NTRS)

Biegl, Csaba A.; Springfield, James F.; Cook, George E.; Fernandez, Kenneth R.

1990-01-01

A robot control package is described which utilizes on-line structural simulation of robot manipulators and objects in their workspace. The model-based controller is interfaced with a high level agent-independent planner, which is responsible for the task-level planning of the robot's actions. Commands received from the agent-independent planner are refined and executed in the simulated workspace, and upon successful completion, they are transferred to the real manipulators.

Clashes in the Infosphere, General Intelligence, and Metacognition

DTIC Science & Technology

2012-12-13

robotic agents . We also implemented the Mars Rover domain and integrated it with MonCon. Finally, the work with AIML chatbots , including human subjects...Park, MD 20742 Abstract Humans confront the unexpected every day, deal with it, and often learn from it. AI agents , on the other hand, are...call the Metacognitive Loop or MCL. To do this, we have implemented MCL- based systems that enable agents to help themselves; they must establish

Agents in real-time collaborative systems

NASA Astrophysics Data System (ADS)

Mitchell, David

1996-01-01

Desktop conferencing systems, providing voice- or video-conferencing with some form of data sharing, have become increasingly popular. Unlike asynchronous collaborative systems such as email, little attention has been devoted to the place of agents in such real-time systems. This paper examines some of the ways in which agents can be used to support such apparently simple tasks as the setting up and answering of calls. Three agent categories, locators, routers and responders, are defined and some simple examples discussed. Several ways in which such agents can collaborate, providing the basis of an intelligent network, are identified.

Adaptive quantum computation in changing environments using projective simulation

NASA Astrophysics Data System (ADS)

Tiersch, M.; Ganahl, E. J.; Briegel, H. J.

2015-08-01

Quantum information processing devices need to be robust and stable against external noise and internal imperfections to ensure correct operation. In a setting of measurement-based quantum computation, we explore how an intelligent agent endowed with a projective simulator can act as controller to adapt measurement directions to an external stray field of unknown magnitude in a fixed direction. We assess the agent’s learning behavior in static and time-varying fields and explore composition strategies in the projective simulator to improve the agent’s performance. We demonstrate the applicability by correcting for stray fields in a measurement-based algorithm for Grover’s search. Thereby, we lay out a path for adaptive controllers based on intelligent agents for quantum information tasks.

Adaptive quantum computation in changing environments using projective simulation

PubMed Central

Tiersch, M.; Ganahl, E. J.; Briegel, H. J.

2015-01-01

Quantum information processing devices need to be robust and stable against external noise and internal imperfections to ensure correct operation. In a setting of measurement-based quantum computation, we explore how an intelligent agent endowed with a projective simulator can act as controller to adapt measurement directions to an external stray field of unknown magnitude in a fixed direction. We assess the agent’s learning behavior in static and time-varying fields and explore composition strategies in the projective simulator to improve the agent’s performance. We demonstrate the applicability by correcting for stray fields in a measurement-based algorithm for Grover’s search. Thereby, we lay out a path for adaptive controllers based on intelligent agents for quantum information tasks. PMID:26260263

A Theory of Intra-Agent Replanning

DTIC Science & Technology

2013-06-01

1972] Fikes, R.; Hart, P.; and Nils- son, N. 1972. Learning and executing generalized robot plans. Artificial intelligence 3:251–288. [Fox et al. 2006...2003] Gerevini, A.; Saetti, A.; and Serina, I. 2003. Planning through stochastic local search and temporal action graphs in lpg. J. Artif . Intell. Res...order planning. In Proceedings of the National Conference on Artificial Intelligence , 1004–1009. [Kambhampati 1990] Kambhampati, S. 1990. Mapping and

Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

PubMed

Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

Application of Hierarchical Dissociated Neural Network in Closed-Loop Hybrid System Integrating Biological and Mechanical Intelligence

PubMed Central

Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including ‘random’ and ‘4Q’ (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the ‘4Q’ cultures presented absolutely different activities, and the robot controlled by the ‘4Q’ network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems. PMID:25992579

Cognitive computing and eScience in health and life science research: artificial intelligence and obesity intervention programs.

PubMed

Marshall, Thomas; Champagne-Langabeer, Tiffiany; Castelli, Darla; Hoelscher, Deanna

2017-12-01

To present research models based on artificial intelligence and discuss the concept of cognitive computing and eScience as disruptive factors in health and life science research methodologies. The paper identifies big data as a catalyst to innovation and the development of artificial intelligence, presents a framework for computer-supported human problem solving and describes a transformation of research support models. This framework includes traditional computer support; federated cognition using machine learning and cognitive agents to augment human intelligence; and a semi-autonomous/autonomous cognitive model, based on deep machine learning, which supports eScience. The paper provides a forward view of the impact of artificial intelligence on our human-computer support and research methods in health and life science research. By augmenting or amplifying human task performance with artificial intelligence, cognitive computing and eScience research models are discussed as novel and innovative systems for developing more effective adaptive obesity intervention programs.

Collaborating Fuzzy Reinforcement Learning Agents

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1997-01-01

Earlier, we introduced GARIC-Q, a new method for doing incremental Dynamic Programming using a society of intelligent agents which are controlled at the top level by Fuzzy Relearning and at the local level, each agent learns and operates based on ANTARCTIC, a technique for fuzzy reinforcement learning. In this paper, we show that it is possible for these agents to compete in order to affect the selected control policy but at the same time, they can collaborate while investigating the state space. In this model, the evaluator or the critic learns by observing all the agents behaviors but the control policy changes only based on the behavior of the winning agent also known as the super agent.

Overview of Intelligent Systems and Operations Development

NASA Technical Reports Server (NTRS)

Pallix, Joan; Dorais, Greg; Penix, John

2004-01-01

To achieve NASA's ambitious mission objectives for the future, aircraft and spacecraft will need intelligence to take the correct action in a variety of circumstances. Vehicle intelligence can be defined as the ability to "do the right thing" when faced with a complex decision-making situation. It will be necessary to implement integrated autonomous operations and low-level adaptive flight control technologies to direct actions that enhance the safety and success of complex missions despite component failures, degraded performance, operator errors, and environment uncertainty. This paper will describe the array of technologies required to meet these complex objectives. This includes the integration of high-level reasoning and autonomous capabilities with multiple subsystem controllers for robust performance. Future intelligent systems will use models of the system, its environment, and other intelligent agents with which it interacts. They will also require planners, reasoning engines, and adaptive controllers that can recommend or execute commands enabling the system to respond intelligently. The presentation will also address the development of highly dependable software, which is a key component to ensure the reliability of intelligent systems.

Reflexive reasoning for distributed real-time systems

NASA Technical Reports Server (NTRS)

Goldstein, David

1994-01-01

This paper discusses the implementation and use of reflexive reasoning in real-time, distributed knowledge-based applications. Recently there has been a great deal of interest in agent-oriented systems. Implementing such systems implies a mechanism for sharing knowledge, goals and other state information among the agents. Our techniques facilitate an agent examining both state information about other agents and the parameters of the knowledge-based system shell implementing its reasoning algorithms. The shell implementing the reasoning is the Distributed Artificial Intelligence Toolkit, which is a derivative of CLIPS.

Reflective Thinking and Emotional Intelligence as Predictive Performance Factors in Problem-Based Learning Situations

ERIC Educational Resources Information Center

Mitchell-White, Kathleen

2010-01-01

Continued improvement of the training and preparation of Federal Bureau of Investigation (FBI) special agents is critical to the organization's ability to protect the national security of the United States. Too little attention has been paid to the factors that improve new agent trainees' (NATs) ability to learn and succeed in their training…

We Care about You: Incorporating Pet Characteristics with Educational Agents through Reciprocal Caring Approach

ERIC Educational Resources Information Center

Chen, Zhi-Hong

2012-01-01

Although different educational agents have been proposed to facilitate student learning, most of them operate from a "smart" (i.e., intelligent and autonomous) perspective. Recently, a so-called "non-smart" perspective is also attracting increasing interest, and is now regarded as a topic worthwhile of researching. To this end,…

Maydays and Murphies: A Study of the Effect of Organizational Design, Task, and Stress on Organizational Performance.

ERIC Educational Resources Information Center

Lin, Zhiang; Carley, Kathleen

How should organizations of intelligent agents be designed so that they exhibit high performance even during periods of stress? A formal model of organizational performance given a distributed decision-making environment in which agents encounter a radar detection task is presented. Using this model the performance of organizations with various…

Evolvable mathematical models: A new artificial Intelligence paradigm

NASA Astrophysics Data System (ADS)

Grouchy, Paul

We develop a novel Artificial Intelligence paradigm to generate autonomously artificial agents as mathematical models of behaviour. Agent/environment inputs are mapped to agent outputs via equation trees which are evolved in a manner similar to Symbolic Regression in Genetic Programming. Equations are comprised of only the four basic mathematical operators, addition, subtraction, multiplication and division, as well as input and output variables and constants. From these operations, equations can be constructed that approximate any analytic function. These Evolvable Mathematical Models (EMMs) are tested and compared to their Artificial Neural Network (ANN) counterparts on two benchmarking tasks: the double-pole balancing without velocity information benchmark and the challenging discrete Double-T Maze experiments with homing. The results from these experiments show that EMMs are capable of solving tasks typically solved by ANNs, and that they have the ability to produce agents that demonstrate learning behaviours. To further explore the capabilities of EMMs, as well as to investigate the evolutionary origins of communication, we develop NoiseWorld, an Artificial Life simulation in which interagent communication emerges and evolves from initially noncommunicating EMM-based agents. Agents develop the capability to transmit their x and y position information over a one-dimensional channel via a complex, dialogue-based communication scheme. These evolved communication schemes are analyzed and their evolutionary trajectories examined, yielding significant insight into the emergence and subsequent evolution of cooperative communication. Evolved agents from NoiseWorld are successfully transferred onto physical robots, demonstrating the transferability of EMM-based AIs from simulation into physical reality.

Agent Based Intelligence in a Tetrahedral Rover

NASA Technical Reports Server (NTRS)

Phelps, Peter; Truszkowski, Walt

2007-01-01

A tetrahedron is a 4-node 6-strut pyramid structure which is being used by the NASA - Goddard Space Flight Center as the basic building block for a new approach to robotic motion. The struts are extendable; it is by the sequence of activities: strut-extension, changing the center of gravity and falling that the tetrahedron "moves". Currently, strut-extension is handled by human remote control. There is an effort underway to make the movement of the tetrahedron autonomous, driven by an attempt to achieve a goal. The approach being taken is to associate an intelligent agent with each node. Thus, the autonomous tetrahedron is realized as a constrained multi-agent system, where the constraints arise from the fact that between any two agents there is an extendible strut. The hypothesis of this work is that, by proper composition of such automated tetrahedra, robotic structures of various levels of complexity can be developed which will support more complex dynamic motions. This is the basis of the new approach to robotic motion which is under investigation. A Java-based simulator for the single tetrahedron, realized as a constrained multi-agent system, has been developed and evaluated. This paper reports on this project and presents a discussion of the structure and dynamics of the simulator.

Intelligent Adaptive Systems: Literature Research of Design Guidance for Intelligent Adaptive Automation and Interfaces

DTIC Science & Technology

2007-09-01

behaviour based on past experience of interacting with the operator), and mobile (i.e., can move themselves from one machine to another). Edwards argues that...Sofge, D., Bugajska, M., Adams, W., Perzanowski, D., and Schultz, A. (2003). Agent-based Multimodal Interface for Dynamically Autonomous Mobile Robots...based architecture can provide a natural and scalable approach to implementing a multimodal interface to control mobile robots through dynamic

Air traffic management as principled negotiation between intelligent agents

NASA Technical Reports Server (NTRS)

Wangermann, J. P.

1994-01-01

The major challenge facing the world's aircraft/airspace system (AAS) today is the need to provide increased capacity, while reducing delays, increasing the efficiency of flight operations, and improving safety. Technologies are emerging that should improve the performance of the system, but which could also introduce uncertainty, disputes, and inefficiency if not properly implemented. The aim of our research is to apply techniques from intelligent control theory and decision-making theory to define an Intelligent Aircraft/Airspace System (IAAS) for the year 2025. The IAAS would make effective use of the technical capabilities of all parts of the system to meet the demand for increased capacity with improved performance.

Using CONFIG for Simulation of Operation of Water Recovery Subsystems for Advanced Control Software Evaluation

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Flores, Luis; Fleming, Land; Throop, Daiv

2002-01-01

A hybrid discrete/continuous simulation tool, CONFIG, has been developed to support evaluation of the operability life support systems. CON FIG simulates operations scenarios in which flows and pressures change continuously while system reconfigurations occur as discrete events. In simulations, intelligent control software can interact dynamically with hardware system models. CONFIG simulations have been used to evaluate control software and intelligent agents for automating life support systems operations. A CON FIG model of an advanced biological water recovery system has been developed to interact with intelligent control software that is being used in a water system test at NASA Johnson Space Center

Industry Cluster's Adaptive Co-competition Behavior Modeling Inspired by Swarm Intelligence

NASA Astrophysics Data System (ADS)

Xiang, Wei; Ye, Feifan

Adaptation helps the individual enterprise to adjust its behavior to uncertainties in environment and hence determines a healthy growth of both the individuals and the whole industry cluster as well. This paper is focused on the study on co-competition adaptation behavior of industry cluster, which is inspired by swarm intelligence mechanisms. By referencing to ant cooperative transportation and ant foraging behavior and their related swarm intelligence approaches, the cooperative adaptation and competitive adaptation behavior are studied and relevant models are proposed. Those adaptive co-competition behaviors model can be integrated to the multi-agent system of industry cluster to make the industry cluster model more realistic.

Rule-based statistical data mining agents for an e-commerce application

NASA Astrophysics Data System (ADS)

Qin, Yi; Zhang, Yan-Qing; King, K. N.; Sunderraman, Rajshekhar

2003-03-01

Intelligent data mining techniques have useful e-Business applications. Because an e-Commerce application is related to multiple domains such as statistical analysis, market competition, price comparison, profit improvement and personal preferences, this paper presents a hybrid knowledge-based e-Commerce system fusing intelligent techniques, statistical data mining, and personal information to enhance QoS (Quality of Service) of e-Commerce. A Web-based e-Commerce application software system, eDVD Web Shopping Center, is successfully implemented uisng Java servlets and an Oracle81 database server. Simulation results have shown that the hybrid intelligent e-Commerce system is able to make smart decisions for different customers.

An Artificially Intelligent Physical Model-Checking Approach to Detect Switching-Related Attacks on Power Systems

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

El Hariri, Mohamad; Faddel, Samy; Mohammed, Osama

Decentralized and hierarchical microgrid control strategies have lain the groundwork for shaping the future smart grid. Such control approaches require the cooperation between microgrid operators in control centers, intelligent microcontrollers, and remote terminal units via secure and reliable communication networks. In order to enhance the security and complement the work of network intrusion detection systems, this paper presents an artificially intelligent physical model-checking that detects tampered-with circuit breaker switching control commands whether, due to a cyber-attack or human error. In this technique, distributed agents, which are monitoring sectionalized areas of a given microgrid, will be trained and continuously adapted tomore » verify that incoming control commands do not violate the physical system operational standards and do not put the microgrid in an insecure state. The potential of this approach has been tested by deploying agents that monitor circuit breakers status commands on a 14-bus IEEE benchmark system. The results showed the accuracy of the proposed framework in characterizing the power system and successfully detecting malicious and/or erroneous control commands.« less

Towards an intelligent framework for multimodal affective data analysis.

PubMed

Poria, Soujanya; Cambria, Erik; Hussain, Amir; Huang, Guang-Bin

2015-03-01

An increasingly large amount of multimodal content is posted on social media websites such as YouTube and Facebook everyday. In order to cope with the growth of such so much multimodal data, there is an urgent need to develop an intelligent multi-modal analysis framework that can effectively extract information from multiple modalities. In this paper, we propose a novel multimodal information extraction agent, which infers and aggregates the semantic and affective information associated with user-generated multimodal data in contexts such as e-learning, e-health, automatic video content tagging and human-computer interaction. In particular, the developed intelligent agent adopts an ensemble feature extraction approach by exploiting the joint use of tri-modal (text, audio and video) features to enhance the multimodal information extraction process. In preliminary experiments using the eNTERFACE dataset, our proposed multi-modal system is shown to achieve an accuracy of 87.95%, outperforming the best state-of-the-art system by more than 10%, or in relative terms, a 56% reduction in error rate. Copyright © 2014 Elsevier Ltd. All rights reserved.

Persuasion Model and Its Evaluation Based on Positive Change Degree of Agent Emotion

NASA Astrophysics Data System (ADS)

Jinghua, Wu; Wenguang, Lu; Hailiang, Meng

For it can meet needs of negotiation among organizations take place in different time and place, and for it can make its course more rationality and result more ideal, persuasion based on agent can improve cooperation among organizations well. Integrated emotion change in agent persuasion can further bring agent advantage of artificial intelligence into play. Emotion of agent persuasion is classified, and the concept of positive change degree is given. Based on this, persuasion model based on positive change degree of agent emotion is constructed, which is explained clearly through an example. Finally, the method of relative evaluation is given, which is also verified through a calculation example.

Opportunistic Behavior in Motivated Learning Agents.

PubMed

Graham, James; Starzyk, Janusz A; Jachyra, Daniel

2015-08-01

This paper focuses on the novel motivated learning (ML) scheme and opportunistic behavior of an intelligent agent. It extends previously developed ML to opportunistic behavior in a multitask situation. Our paper describes the virtual world implementation of autonomous opportunistic agents learning in a dynamically changing environment, creating abstract goals, and taking advantage of arising opportunities to improve their performance. An opportunistic agent achieves better results than an agent based on ML only. It does so by minimizing the average value of all need signals rather than a dominating need. This paper applies to the design of autonomous embodied systems (robots) learning in real-time how to operate in a complex environment.

Model-Unified Planning and Execution for Distributed Autonomous System Control

NASA Technical Reports Server (NTRS)

Aschwanden, Pascal; Baskaran, Vijay; Bernardini, Sara; Fry, Chuck; Moreno, Maria; Muscettola, Nicola; Plaunt, Chris; Rijsman, David; Tompkins, Paul

2006-01-01

The Intelligent Distributed Execution Architecture (IDEA) is a real-time architecture that exploits artificial intelligence planning as the core reasoning engine for interacting autonomous agents. Rather than enforcing separate deliberation and execution layers, IDEA unifies them under a single planning technology. Deliberative and reactive planners reason about and act according to a single representation of the past, present and future domain state. The domain state behaves the rules dictated by a declarative model of the subsystem to be controlled, internal processes of the IDEA controller, and interactions with other agents. We present IDEA concepts - modeling, the IDEA core architecture, the unification of deliberation and reaction under planning - and illustrate its use in a simple example. Finally, we present several real-world applications of IDEA, and compare IDEA to other high-level control approaches.

Social effects of an anthropomorphic help agent: humans versus computers.

PubMed

David, Prabu; Lu, Tingting; Kline, Susan; Cai, Li

2007-06-01

The purpose of this study was to examine perceptions of fairness of a computer-administered quiz as a function of the anthropomorphic features of the help agent offered within the quiz environment. The addition of simple anthropomorphic cues to a computer help agent reduced the perceived friendliness of the agent, perceived intelligence of the agent, and the perceived fairness of the quiz. These differences were observed only for male anthropomorphic cues, but not for female anthropomorphic cues. The results were not explained by the social attraction of the anthropomorphic agents used in the quiz or by gender identification with the agents. Priming of visual cues provides the best account of the data. Practical implications of the study are discussed.

Commanding and Controlling Satellite Clusters (IEEE Intelligent Systems, November/December 2000)

DTIC Science & Technology

2000-01-01

real - time operating system , a message-passing OS well suited for distributed...ground Flight processors ObjectAgent RTOS SCL RTOS RDMS Space command language Real - time operating system Rational database management system TS-21 RDMS...engineer with Princeton Satellite Systems. She is working with others to develop ObjectAgent software to run on the OSE Real Time Operating System .

The Idea Storming Cube: Evaluating the Effects of Using Game and Computer Agent to Support Divergent Thinking

ERIC Educational Resources Information Center

Huang, Chun-Chieh; Yeh, Ting-Kuang; Li, Tsai-Yen; Chang, Chun-Yen

2010-01-01

The objective of this article is to evaluate the effectiveness of a collaborative and online brainstorming game, Idea Storming Cube (ISC), which provides users with a competitive game-based environment and a peer-like intelligent agent. The program seeks to promote students' divergent thinking to aid in the process of problem solving. The…

Nonlinear Dynamics and Heterogeneous Interacting Agents

NASA Astrophysics Data System (ADS)

Lux, Thomas; Reitz, Stefan; Samanidou, Eleni

Economic application of nonlinear dynamics, microscopic agent-based modelling, and the use of artificial intelligence techniques as learning devices of boundedly rational actors are among the most exciting interdisciplinary ventures of economic theory over the past decade. This volume provides us with a most fascinating series of examples on "complexity in action" exemplifying the scope and explanatory power of these innovative approaches.

Automated Intelligent Agents: Are They Trusted Members of Military Teams?

DTIC Science & Technology

2008-12-01

computer -based team firefighting game (C3Fire). The order of presentation of the two trials (human – human vs. human – automation) was...agent. All teams played a computer -based team firefighting game (C3Fire). The order of presentation of the two trials (human – human vs. human...26 b. Participants’ Computer ..................27 C. VARIABLES .........................................27 1. Independent Variables

Virtual odors to transmit emotions in virtual agents

NASA Astrophysics Data System (ADS)

Delgado-Mata, Carlos; Aylett, Ruth

2003-04-01

In this paper we describe an emotional-behvioral architecture. The emotional engine sits at a higher layer than the behavior system, and can alter behavior patterns, the engine is designed to simulate Emotionally-Intelligent Agents in a Virtual Environment, where each agent senses its own emotions, and other creature emotions through a virtual smell sensor; senses obstacles and other moving creatures in the environment and reacts to them. The architecture consists of an emotion engine, behavior synthesis system, a motor layer and a library of sensors.

The Study on Collaborative Manufacturing Platform Based on Agent

NASA Astrophysics Data System (ADS)

Zhang, Xiao-yan; Qu, Zheng-geng

To fulfill the trends of knowledge-intensive in collaborative manufacturing development, we have described multi agent architecture supporting knowledge-based platform of collaborative manufacturing development platform. In virtue of wrapper service and communication capacity agents provided, the proposed architecture facilitates organization and collaboration of multi-disciplinary individuals and tools. By effectively supporting the formal representation, capture, retrieval and reuse of manufacturing knowledge, the generalized knowledge repository based on ontology library enable engineers to meaningfully exchange information and pass knowledge across boundaries. Intelligent agent technology increases traditional KBE systems efficiency and interoperability and provides comprehensive design environments for engineers.

Emotional recognition from the speech signal for a virtual education agent

NASA Astrophysics Data System (ADS)

Tickle, A.; Raghu, S.; Elshaw, M.

2013-06-01

This paper explores the extraction of features from the speech wave to perform intelligent emotion recognition. A feature extract tool (openSmile) was used to obtain a baseline set of 998 acoustic features from a set of emotional speech recordings from a microphone. The initial features were reduced to the most important ones so recognition of emotions using a supervised neural network could be performed. Given that the future use of virtual education agents lies with making the agents more interactive, developing agents with the capability to recognise and adapt to the emotional state of humans is an important step.

Cyber Ricochet: Risk Management and Cyberspace Operations

DTIC Science & Technology

2012-07-01

Cox, U.S. Cyber Command Director of Intelligence Introduction Recent media reports of the ‘ Duqu ’, ‘Flame’, and ‘Stuxnet’ malware highlight...as the ‘ Duqu ,’ ‘Flame,’ and ‘Stuxnet’ malware, are just of a few of the capabilities that can contribute to mission success and achieve strategic...rely on artificially intelligent agents to dredge up the deepest secrets.” 19 The ‘ Duqu ’ and ‘Flame’ malware are excellent examples of computer

Future applications of artificial intelligence to Mission Control Centers

NASA Technical Reports Server (NTRS)

Friedland, Peter

1991-01-01

Future applications of artificial intelligence to Mission Control Centers are presented in the form of the viewgraphs. The following subject areas are covered: basic objectives of the NASA-wide AI program; inhouse research program; constraint-based scheduling; learning and performance improvement for scheduling; GEMPLAN multi-agent planner; planning, scheduling, and control; Bayesian learning; efficient learning algorithms; ICARUS (an integrated architecture for learning); design knowledge acquisition and retention; computer-integrated documentation; and some speculation on future applications.

Human Centered Autonomous and Assistant Systems Testbed for Exploration Operations

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Mount, Frances; Carreon, Patricia; Torney, Susan E.

2001-01-01

The Engineering and Mission Operations Directorates at NASA Johnson Space Center are combining laboratories and expertise to establish the Human Centered Autonomous and Assistant Systems Testbed for Exploration Operations. This is a testbed for human centered design, development and evaluation of intelligent autonomous and assistant systems that will be needed for human exploration and development of space. This project will improve human-centered analysis, design and evaluation methods for developing intelligent software. This software will support human-machine cognitive and collaborative activities in future interplanetary work environments where distributed computer and human agents cooperate. We are developing and evaluating prototype intelligent systems for distributed multi-agent mixed-initiative operations. The primary target domain is control of life support systems in a planetary base. Technical approaches will be evaluated for use during extended manned tests in the target domain, the Bioregenerative Advanced Life Support Systems Test Complex (BIO-Plex). A spinoff target domain is the International Space Station (ISS) Mission Control Center (MCC). Prodl}cts of this project include human-centered intelligent software technology, innovative human interface designs, and human-centered software development processes, methods and products. The testbed uses adjustable autonomy software and life support systems simulation models from the Adjustable Autonomy Testbed, to represent operations on the remote planet. Ground operations prototypes and concepts will be evaluated in the Exploration Planning and Operations Center (ExPOC) and Jupiter Facility.

A Distributed, Collaborative Intelligent Agent System Approach for Proactive Postmarketing Drug Safety Surveillance

PubMed Central

Ji, Yanqing; Ying, Hao; Farber, Margo S.; Yen, John; Dews, Peter; Miller, Richard E.; Massanari, R. Michael

2014-01-01

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is of great importance. The current approach to postmarketing surveillance primarily relies on spontaneous reporting. It is a passive surveillance system and limited by gross underreporting (<10% reporting rate), latency, and inconsistent reporting. We propose a novel team-based intelligent agent software system approach for proactively monitoring and detecting potential ADRs of interest using electronic patient records. We designed such a system and named it ADRMonitor. The intelligent agents, operating on computers located in different places, are capable of continuously and autonomously collaborating with each other and assisting the human users (e.g., the food and drug administration (FDA), drug safety professionals, and physicians). The agents should enhance current systems and accelerate early ADR identification. To evaluate the performance of the ADRMonitor with respect to the current spontaneous reporting approach, we conducted simulation experiments on identification of ADR signal pairs (i.e., potential links between drugs and apparent adverse reactions) under various conditions. The experiments involved over 275 000 simulated patients created on the basis of more than 1000 real patients treated by the drug cisapride that was on the market for seven years until its withdrawal by the FDA in 2000 due to serious ADRs. Healthcare professionals utilizing the spontaneous reporting approach and the ADRMonitor were separately simulated by decision-making models derived from a general cognitive decision model called fuzzy recognition-primed decision (RPD) model that we recently developed. The quantitative simulation results show that 1) the number of true ADR signal pairs detected by the ADRMonitor is 6.6 times higher than that by the spontaneous reporting strategy; 2) the ADR detection rate of the ADRMonitor agents with even moderate decision-making skills is five times higher than that of spontaneous reporting; and 3) as the number of patient cases increases, ADRs could be detected significantly earlier by the ADRMonitor. PMID:20007038

Synthetic collective intelligence.

PubMed

Solé, Ricard; Amor, Daniel R; Duran-Nebreda, Salva; Conde-Pueyo, Núria; Carbonell-Ballestero, Max; Montañez, Raúl

2016-10-01

Intelligent systems have emerged in our biosphere in different contexts and achieving different levels of complexity. The requirement of communication in a social context has been in all cases a determinant. The human brain, probably co-evolving with language, is an exceedingly successful example. Similarly, social insects complex collective decisions emerge from information exchanges between many agents. The difference is that such processing is obtained out of a limited individual cognitive power. Computational models and embodied versions using non-living systems, particularly involving robot swarms, have been used to explore the potentiality of collective intelligence. Here we suggest a novel approach to the problem grounded in the genetic engineering of unicellular systems, which can be modified in order to interact, store memories or adapt to external stimuli in collective ways. What we label as Synthetic Swarm Intelligence defines a parallel approach to the evolution of computation and swarm intelligence and allows to explore potential embodied scenarios for decision making at the microscale. Here, we consider several relevant examples of collective intelligence and their synthetic organism counterparts. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

AIonAI: a humanitarian law of artificial intelligence and robotics.

PubMed

Ashrafian, Hutan

2015-02-01

The enduring progression of artificial intelligence and cybernetics offers an ever-closer possibility of rational and sentient robots. The ethics and morals deriving from this technological prospect have been considered in the philosophy of artificial intelligence, the design of automatons with roboethics and the contemplation of machine ethics through the concept of artificial moral agents. Across these categories, the robotics laws first proposed by Isaac Asimov in the twentieth century remain well-recognised and esteemed due to their specification of preventing human harm, stipulating obedience to humans and incorporating robotic self-protection. However the overwhelming predominance in the study of this field has focussed on human-robot interactions without fully considering the ethical inevitability of future artificial intelligences communicating together and has not addressed the moral nature of robot-robot interactions. A new robotic law is proposed and termed AIonAI or artificial intelligence-on-artificial intelligence. This law tackles the overlooked area where future artificial intelligences will likely interact amongst themselves, potentially leading to exploitation. As such, they would benefit from adopting a universal law of rights to recognise inherent dignity and the inalienable rights of artificial intelligences. Such a consideration can help prevent exploitation and abuse of rational and sentient beings, but would also importantly reflect on our moral code of ethics and the humanity of our civilisation.

Planning and Execution: The Spirit of Opportunity for Robust Autonomous Systems

NASA Technical Reports Server (NTRS)

Muscettola, Nicola

2004-01-01

One of the most exciting endeavors pursued by human kind is the search for life in the Solar System and the Universe at large. NASA is leading this effort by designing, deploying and operating robotic systems that will reach planets, planet moons, asteroids and comets searching for water, organic building blocks and signs of past or present microbial life. None of these missions will be achievable without substantial advances in.the design, implementation and validation of autonomous control agents. These agents must be capable of robustly controlling a robotic explorer in a hostile environment with very limited or no communication with Earth. The talk focuses on work pursued at the NASA Ames Research center ranging from basic research on algorithm to deployed mission support systems. We will start by discussing how planning and scheduling technology derived from the Remote Agent experiment is being used daily in the operations of the Spirit and Opportunity rovers. Planning and scheduling is also used as the fundamental paradigm at the core of our research in real-time autonomous agents. In particular, we will describe our efforts in the Intelligent Distributed Execution Architecture (IDEA), a multi-agent real-time architecture that exploits artificial intelligence planning as the core reasoning engine of an autonomous agent. We will also describe how the issue of plan robustness at execution can be addressed by novel constraint propagation algorithms capable of giving the tightest exact bounds on resource consumption or all possible executions of a flexible plan.

Onto-Agents-Enabling Intelligent Agents on the Web

DTIC Science & Technology

2005-05-01

AIR FORCE RESEARCH LABORATORY INFORMATION DIRECTORATE ROME RESEARCH SITE ROME, NEW YORK STINFO FINAL REPORT This report has been reviewed...by the Air Force Research Laboratory, Information Directorate, Public Affairs Office (IFOIPA) and is releasable to the National Technical... Information Service (NTIS). At NTIS it will be releasable to the general public, including foreign nations. AFRL-IF-RS-TR-2005-178 has been reviewed

Effects of competition and cooperation interaction between agents on networks in the presence of a market capacity

NASA Astrophysics Data System (ADS)

Sonubi, A.; Arcagni, A.; Stefani, S.; Ausloos, M.

2016-08-01

A network effect is introduced taking into account competition, cooperation, and mixed-type interaction among agents along a generalized Verhulst-Lotka-Volterra model. It is also argued that the presence of a market capacity undoubtedly enforces a definite limit on the agent's size growth. The state stability of triadic agents, i.e., the most basic network plaquette, is investigated analytically for possible scenarios, through a fixed-point analysis. It is discovered that: (i) market demand is only satisfied for full competition when one agent monopolizes the market; (ii) growth of agent size is encouraged in full cooperation; (iii) collaboration among agents to compete against one single agent may result in the disappearance of this single agent out of the market; and (iv) cooperating with two rivals may become a growth strategy for an intelligent agent.

Effects of competition and cooperation interaction between agents on networks in the presence of a market capacity.

PubMed

Sonubi, A; Arcagni, A; Stefani, S; Ausloos, M

2016-08-01

A network effect is introduced taking into account competition, cooperation, and mixed-type interaction among agents along a generalized Verhulst-Lotka-Volterra model. It is also argued that the presence of a market capacity undoubtedly enforces a definite limit on the agent's size growth. The state stability of triadic agents, i.e., the most basic network plaquette, is investigated analytically for possible scenarios, through a fixed-point analysis. It is discovered that: (i) market demand is only satisfied for full competition when one agent monopolizes the market; (ii) growth of agent size is encouraged in full cooperation; (iii) collaboration among agents to compete against one single agent may result in the disappearance of this single agent out of the market; and (iv) cooperating with two rivals may become a growth strategy for an intelligent agent.

VOLTTRON - An Intelligent Agent Platform for the Smart Grid

ScienceCinema

None

2018-05-16

The distributed nature of the Smart Grid, such as responsive loads, solar and wind generation, and automation in the distribution system present a complex environment not easily controlled in a centralized manner.

Autonomous mission management for UAVs using soar intelligent agents

NASA Astrophysics Data System (ADS)

Gunetti, Paolo; Thompson, Haydn; Dodd, Tony

2013-05-01

State-of-the-art unmanned aerial vehicles (UAVs) are typically able to autonomously execute a pre-planned mission. However, UAVs usually fly in a very dynamic environment which requires dynamic changes to the flight plan; this mission management activity is usually tasked to human supervision. Within this article, a software system that autonomously accomplishes the mission management task for a UAV will be proposed. The system is based on a set of theoretical concepts which allow the description of a flight plan and implemented using a combination of Soar intelligent agents and traditional control techniques. The system is capable of automatically generating and then executing an entire flight plan after being assigned a set of objectives. This article thoroughly describes all system components and then presents the results of tests that were executed using a realistic simulation environment.

ISHM-oriented adaptive fault diagnostics for avionics based on a distributed intelligent agent system

NASA Astrophysics Data System (ADS)

Xu, Jiuping; Zhong, Zhengqiang; Xu, Lei

2015-10-01

In this paper, an integrated system health management-oriented adaptive fault diagnostics and model for avionics is proposed. With avionics becoming increasingly complicated, precise and comprehensive avionics fault diagnostics has become an extremely complicated task. For the proposed fault diagnostic system, specific approaches, such as the artificial immune system, the intelligent agents system and the Dempster-Shafer evidence theory, are used to conduct deep fault avionics diagnostics. Through this proposed fault diagnostic system, efficient and accurate diagnostics can be achieved. A numerical example is conducted to apply the proposed hybrid diagnostics to a set of radar transmitters on an avionics system and to illustrate that the proposed system and model have the ability to achieve efficient and accurate fault diagnostics. By analyzing the diagnostic system's feasibility and pragmatics, the advantages of this system are demonstrated.

ENcentive: A Framework for Intelligent Marketing in Mobile Peer-To-Peer Environments

DTIC Science & Technology

2005-01-01

trade and commu- nication strategies, mobile electronic marketing, intelligent agents, collaborative eCommerce 1. INTRODUCTION With the explosion of...requests the promotion (since Jeff is a cof- fee drinker). MH2 signs the promotion with Susan’s eN- centive ID. At 6pm, Jeff decides to take advantage of the...to become valid, a user has a choice of remaining in his current loca- tion and being able to take advantage of the promotion. The eNcentive Ad

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 Lightweight Intelligent Virtual Cinematography System for Machinima Production

DTIC Science & Technology

2007-01-01

portmanteau of machine and cinema , machinima refers to the innovation of leveraging video game technology to greatly ease the creation of computer...selecting camera angles to capture the action of an a priori unknown script as aesthetically appropriate cinema . There are a number of challenges therein...Proc. of the 4th International Conf. on Autonomous Agents. Young, R.M. and Riedl, M.O. 2003. Towards an Architecture for Intelligent Control of Narrative in Interactive Virtual Worlds. In Proc. of IUI 2003.

Benchmark Intelligent Agent Systems for Distributed Battle Tracking

DTIC Science & Technology

2008-06-20

services in the military and other domains, each entity in the benchmark system exposes a standard set of Web services. Jess ( Java Expert Shell...System) is a rule engine for the Java platform and is an interpreter for the Jess rule language. It is used here to implement policies that maintain...battle tracking system (DBTS), maintaining distributed situation awareness. The Java Agent DEvelopment (JADE) framework is a software framework

ICPL: Intelligent Cooperative Planning and Learning for Multi-agent Systems

DTIC Science & Technology

2012-02-29

objective was to develop a new planning approach for teams!of multiple UAVs that tightly integrates learning and cooperative!control algorithms at... algorithms at multiple levels of the planning architecture. The research results enabled a team of mobile agents to learn to adapt and react to uncertainty in...expressive representation that incorporates feature conjunctions. Our algorithm is simple to implement, fast to execute, and can be combined with any

Agent Based Study of Surprise Attacks:. Roles of Surveillance, Prompt Reaction and Intelligence

NASA Astrophysics Data System (ADS)

Shanahan, Linda; Sen, Surajit

Defending a confined territory from a surprise attack is seldom possible. We use molecular dynamics and statistical physics inspired agent-based simulations to explore the evolution and outcome of such attacks. The study suggests robust emergent behavior, which emphasizes the importance of accurate surveillance, automated and powerful attack response, building layout, and sheds light on the role of communication restrictions in defending such territories.

A comparison between metaheuristics as strategies for minimizing cyclic instability in Ambient Intelligence.

PubMed

Romero, Leoncio A; Zamudio, Victor; Baltazar, Rosario; Mezura, Efren; Sotelo, Marco; Callaghan, Vic

2012-01-01

In this paper we present a comparison between six novel approaches to the fundamental problem of cyclic instability in Ambient Intelligence. These approaches are based on different optimization algorithms, Particle Swarm Optimization (PSO), Bee Swarm Optimization (BSO), micro Particle Swarm Optimization (μ-PSO), Artificial Immune System (AIS), Genetic Algorithm (GA) and Mutual Information Maximization for Input Clustering (MIMIC). In order to be able to use these algorithms, we introduced the concept of Average Cumulative Oscillation (ACO), which enabled us to measure the average behavior of the system. This approach has the advantage that it does not need to analyze the topological properties of the system, in particular the loops, which can be computationally expensive. In order to test these algorithms we used the well-known discrete system called the Game of Life for 9, 25, 49 and 289 agents. It was found that PSO and μ-PSO have the best performance in terms of the number of agents locked. These results were confirmed using the Wilcoxon Signed Rank Test. This novel and successful approach is very promising and can be used to remove instabilities in real scenarios with a large number of agents (including nomadic agents) and complex interactions and dependencies among them.

A Comparison between Metaheuristics as Strategies for Minimizing Cyclic Instability in Ambient Intelligence

PubMed Central

Romero, Leoncio A.; Zamudio, Victor; Baltazar, Rosario; Mezura, Efren; Sotelo, Marco; Callaghan, Vic

2012-01-01

In this paper we present a comparison between six novel approaches to the fundamental problem of cyclic instability in Ambient Intelligence. These approaches are based on different optimization algorithms, Particle Swarm Optimization (PSO), Bee Swarm Optimization (BSO), micro Particle Swarm Optimization (μ-PSO), Artificial Immune System (AIS), Genetic Algorithm (GA) and Mutual Information Maximization for Input Clustering (MIMIC). In order to be able to use these algorithms, we introduced the concept of Average Cumulative Oscillation (ACO), which enabled us to measure the average behavior of the system. This approach has the advantage that it does not need to analyze the topological properties of the system, in particular the loops, which can be computationally expensive. In order to test these algorithms we used the well-known discrete system called the Game of Life for 9, 25, 49 and 289 agents. It was found that PSO and μ-PSO have the best performance in terms of the number of agents locked. These results were confirmed using the Wilcoxon Signed Rank Test. This novel and successful approach is very promising and can be used to remove instabilities in real scenarios with a large number of agents (including nomadic agents) and complex interactions and dependencies among them. PMID:23112643

Protecting software agents from malicious hosts using quantum computing

NASA Astrophysics Data System (ADS)

Reisner, John; Donkor, Eric

2000-07-01

We evaluate how quantum computing can be applied to security problems for software agents. Agent-based computing, which merges technological advances in artificial intelligence and mobile computing, is a rapidly growing domain, especially in applications such as electronic commerce, network management, information retrieval, and mission planning. System security is one of the more eminent research areas in agent-based computing, and the specific problem of protecting a mobile agent from a potentially hostile host is one of the most difficult of these challenges. In this work, we describe our agent model, and discuss the capabilities and limitations of classical solutions to the malicious host problem. Quantum computing may be extremely helpful in addressing the limitations of classical solutions to this problem. This paper highlights some of the areas where quantum computing could be applied to agent security.

Multi-Agent Strategic Modeling in a Specific Environment

NASA Astrophysics Data System (ADS)

Gams, Matjaz; Bezek, Andraz

Multi-agent modeling in ambient intelligence (AmI) is concerned with the following task [19]: How can external observations of multi-agent systems in the ambient be used to analyze, model, and direct agent behavior? The main purpose is to obtain knowledge about acts in the environment thus enabling proper actions of the AmI systems [1]. Analysis of such systems must thus capture complex world state representation and asynchronous agent activities. Instead of studying basic numerical data, researchers often use more complex data structures, such as rules and decision trees. Some methods are extremely useful when characterizing state space, but lack the ability to clearly represent temporal state changes occurred by agent actions. To comprehend simultaneous agent actions and complex changes of state space, most often a combination of graphical and symbolical representation performs better in terms of human understanding and performance.

Advanced integrated real-time clinical displays.

PubMed

Kruger, Grant H; Tremper, Kevin K

2011-09-01

Intelligent medical displays have the potential to improve patient outcomes by integrating multiple physiologic signals, exhibiting high sensitivity and specificity, and reducing information overload for physicians. Research findings have suggested that information overload and distractions caused by patient care activities and alarms generated by multiple monitors in acute care situations, such as the operating room and the intensive care unit, may produce situations that negatively impact the outcomes of patients under anesthesia. This can be attributed to shortcomings of human-in-the-loop monitoring and the poor specificity of existing physiologic alarms. Modern artificial intelligence techniques (ie, intelligent software agents) are demonstrating the potential to meet the challenges of next-generation patient monitoring and alerting. Copyright © 2011 Elsevier Inc. All rights reserved.

Multi-agent Reinforcement Learning Model for Effective Action Selection

NASA Astrophysics Data System (ADS)

Youk, Sang Jo; Lee, Bong Keun

Reinforcement learning is a sub area of machine learning concerned with how an agent ought to take actions in an environment so as to maximize some notion of long-term reward. In the case of multi-agent, especially, which state space and action space gets very enormous in compared to single agent, so it needs to take most effective measure available select the action strategy for effective reinforcement learning. This paper proposes a multi-agent reinforcement learning model based on fuzzy inference system in order to improve learning collect speed and select an effective action in multi-agent. This paper verifies an effective action select strategy through evaluation tests based on Robocop Keep away which is one of useful test-beds for multi-agent. Our proposed model can apply to evaluate efficiency of the various intelligent multi-agents and also can apply to strategy and tactics of robot soccer system.

Neuroprotective Drug for Nerve Trauma Revealed Using Artificial Intelligence.

PubMed

Romeo-Guitart, David; Forés, Joaquim; Herrando-Grabulosa, Mireia; Valls, Raquel; Leiva-Rodríguez, Tatiana; Galea, Elena; González-Pérez, Francisco; Navarro, Xavier; Petegnief, Valerie; Bosch, Assumpció; Coma, Mireia; Mas, José Manuel; Casas, Caty

2018-01-30

Here we used a systems biology approach and artificial intelligence to identify a neuroprotective agent for the treatment of peripheral nerve root avulsion. Based on accumulated knowledge of the neurodegenerative and neuroprotective processes that occur in motoneurons after root avulsion, we built up protein networks and converted them into mathematical models. Unbiased proteomic data from our preclinical models were used for machine learning algorithms and for restrictions to be imposed on mathematical solutions. Solutions allowed us to identify combinations of repurposed drugs as potential neuroprotective agents and we validated them in our preclinical models. The best one, NeuroHeal, neuroprotected motoneurons, exerted anti-inflammatory properties and promoted functional locomotor recovery. NeuroHeal endorsed the activation of Sirtuin 1, which was essential for its neuroprotective effect. These results support the value of network-centric approaches for drug discovery and demonstrate the efficacy of NeuroHeal as adjuvant treatment with surgical repair for nervous system trauma.

Development of an evolutionary simulator and an overall control system for intelligent wheelchair

NASA Astrophysics Data System (ADS)

Imai, Makoto; Kawato, Koji; Hamagami, Tomoki; Hirata, Hironori

The goal of this research is to develop an intelligent wheelchair (IWC) system which aids an indoor safe mobility for elderly and disabled people with a new conceptual architecture which realizes autonomy, cooperativeness, and a collaboration behavior. In order to develop the IWC system in real environment, we need design-tools and flexible architecture. In particular, as more significant ones, this paper describes two key techniques which are an evolutionary simulation and an overall control mechanism. The evolutionary simulation technique corrects the error between the virtual environment in a simulator and real one in during the learning of an IWC agent, and coevolves with the agent. The overall control mechanism is implemented with subsumption architecture which is employed in an autonomous robot controller. By using these techniques in both simulations and experiments, we confirm that our IWC system acquires autonomy, cooperativeness, and a collaboration behavior efficiently.

Autonomy for Constellation

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Szczur, Martha R. (Technical Monitor)

2000-01-01

The newer types of space systems, which are planned for the future, are placing challenging demands for newer autonomy concepts and techniques. Motivating these challenges are resource constraints. Even though onboard computing power will surely increase in the coming years, the resource constraints associated with space-based processes will continue to be a major factor that needs to be considered when dealing with, for example, agent-based spacecraft autonomy. To realize "economical intelligence", i.e., constrained computational intelligence that can reside within a process under severe resource constraints (time, power, space, etc.), is a major goal for such space systems as the Nanosat constellations. To begin to address the new challenges, we are developing approaches to constellation autonomy with constraints in mind. Within the Agent Concepts Testbed (ACT) at the Goddard Space Flight Center we are currently developing a Nanosat-related prototype for the first of the two-step program.

Toward detecting deception in intelligent systems

NASA Astrophysics Data System (ADS)

Santos, Eugene, Jr.; Johnson, Gregory, Jr.

2004-08-01

Contemporary decision makers often must choose a course of action using knowledge from several sources. Knowledge may be provided from many diverse sources including electronic sources such as knowledge-based diagnostic or decision support systems or through data mining techniques. As the decision maker becomes more dependent on these electronic information sources, detecting deceptive information from these sources becomes vital to making a correct, or at least more informed, decision. This applies to unintentional disinformation as well as intentional misinformation. Our ongoing research focuses on employing models of deception and deception detection from the fields of psychology and cognitive science to these systems as well as implementing deception detection algorithms for probabilistic intelligent systems. The deception detection algorithms are used to detect, classify and correct attempts at deception. Algorithms for detecting unexpected information rely upon a prediction algorithm from the collaborative filtering domain to predict agent responses in a multi-agent system.

Implementing Artificial Intelligence Behaviors in a Virtual World

NASA Technical Reports Server (NTRS)

Krisler, Brian; Thome, Michael

2012-01-01

In this paper, we will present a look at the current state of the art in human-computer interface technologies, including intelligent interactive agents, natural speech interaction and gestural based interfaces. We describe our use of these technologies to implement a cost effective, immersive experience on a public region in Second Life. We provision our Artificial Agents as a German Shepherd Dog avatar with an external rules engine controlling the behavior and movement. To interact with the avatar, we implemented a natural language and gesture system allowing the human avatars to use speech and physical gestures rather than interacting via a keyboard and mouse. The result is a system that allows multiple humans to interact naturally with AI avatars by playing games such as fetch with a flying disk and even practicing obedience exercises using voice and gesture, a natural seeming day in the park.

Intelligent Advanced Communications IP Telephony Feasibility for the U.S. Navy: Phase 2

DTIC Science & Technology

2009-03-31

PDAs) and smart phones. In addition, it considers how solutions integrate on-premise enterprise functions with the functions of mobile operators...and Control System GIG Global Information Grid GigE Gigabit Ethernet GIPS Global IP Solutions Inc. GMSK Gaussian Minimum Shift Keying GPHY Gigabit...Feasibility for the U.S. Navy – Phase 2 UAC User Agent Client UART Universal Asynchronous Receiver/Transmitter UAS User Agent Server UCR

Incorporating BDI Agents into Human-Agent Decision Making Research

NASA Astrophysics Data System (ADS)

Kamphorst, Bart; van Wissen, Arlette; Dignum, Virginia

Artificial agents, people, institutes and societies all have the ability to make decisions. Decision making as a research area therefore involves a broad spectrum of sciences, ranging from Artificial Intelligence to economics to psychology. The Colored Trails (CT) framework is designed to aid researchers in all fields in examining decision making processes. It is developed both to study interaction between multiple actors (humans or software agents) in a dynamic environment, and to study and model the decision making of these actors. However, agents in the current implementation of CT lack the explanatory power to help understand the reasoning processes involved in decision making. The BDI paradigm that has been proposed in the agent research area to describe rational agents, enables the specification of agents that reason in abstract concepts such as beliefs, goals, plans and events. In this paper, we present CTAPL: an extension to CT that allows BDI software agents that are written in the practical agent programming language 2APL to reason about and interact with a CT environment.

Applications of Lexical Link Analysis Web Service for Large-Scale Automation, Validation, Discovery, Visualization, and Real-Time Program Awareness

DTIC Science & Technology

2012-10-23

Quantum Intelligence, Inc. She was principal investigator (PI) for six contracts awarded by the DoD Small Business Innovation Research (SBIR) Program. She...with at OSD? I hope you don’t mind if I indulge in a little ‘stream of consciousness ’ musing about where LLA could really add value. One of the...implemented by Quantum Intelligence, Inc. (QI, 2001–2012). The unique contribution of this architecture is to leverage a peer-to-peer agent network

Understanding Transportation Systems : An Integrated Approach to Modeling Complex Transportation Systems

DOT National Transportation Integrated Search

2013-01-01

The ability to model and understand the complex dynamics of intelligent agents as they interact within a transportation system could lead to revolutionary advances in transportation engineering and intermodal surface transportation in the United Stat...

A Decision-Making Tools Workshop

DTIC Science & Technology

1999-08-01

California Polytechnic State University, San Luis Obispo, CA 47 Distributed Intelligent Agents Katia Sycara, Keith Decker, Anandeep Pannu , Mike...Anandeep Pannu and Katia Sycara. Learning text filtering preferences. In 1996 AAAI Symposium on Machine Learning and Information Access, 1996. [19] Anand

Developmental and Evolutionary Lexicon Acquisition in Cognitive Agents/Robots with Grounding Principle: A Short Review.

PubMed

Rasheed, Nadia; Amin, Shamsudin H M

2016-01-01

Grounded language acquisition is an important issue, particularly to facilitate human-robot interactions in an intelligent and effective way. The evolutionary and developmental language acquisition are two innovative and important methodologies for the grounding of language in cognitive agents or robots, the aim of which is to address current limitations in robot design. This paper concentrates on these two main modelling methods with the grounding principle for the acquisition of linguistic ability in cognitive agents or robots. This review not only presents a survey of the methodologies and relevant computational cognitive agents or robotic models, but also highlights the advantages and progress of these approaches for the language grounding issue.

Developmental and Evolutionary Lexicon Acquisition in Cognitive Agents/Robots with Grounding Principle: A Short Review

PubMed Central

Rasheed, Nadia; Amin, Shamsudin H. M.

2016-01-01

Grounded language acquisition is an important issue, particularly to facilitate human-robot interactions in an intelligent and effective way. The evolutionary and developmental language acquisition are two innovative and important methodologies for the grounding of language in cognitive agents or robots, the aim of which is to address current limitations in robot design. This paper concentrates on these two main modelling methods with the grounding principle for the acquisition of linguistic ability in cognitive agents or robots. This review not only presents a survey of the methodologies and relevant computational cognitive agents or robotic models, but also highlights the advantages and progress of these approaches for the language grounding issue. PMID:27069470

Agent-based paradigm for integration of interactive cable television operations and business support systems

NASA Astrophysics Data System (ADS)

Wattawa, Scott

1995-11-01

Offering interactive services and data in a hybrid fiber/coax cable system requires the coordination of a host of operations and business support systems. New service offerings and network growth and evolution create never-ending changes in the network infrastructure. Agent-based enterprise models provide a flexible mechanism for systems integration of service and support systems. Agent models also provide a mechanism to decouple interactive services from network architecture. By using the Java programming language, agents may be made safe, portable, and intelligent. This paper investigates the application of the Object Management Group's Common Object Request Brokering Architecture to the integration of a multiple services metropolitan area network.

Deducing the multi-trader population driving a financial market

NASA Astrophysics Data System (ADS)

Gupta, Nachi; Hauser, Raphael; Johnson, Neil

2005-12-01

We have previously laid out a basic framework for predicting financial movements and pockets of predictability by tracking the distribution of a multi-trader population playing on an artificial financial market model. This work explores extensions to this basic framework. We allow for more intelligent agents with a richer strategy set, and we no longer constrain the distribution over these agents to a probability space. We then introduce a fusion scheme which accounts for multiple runs of randomly chosen sets of possible agent types. We also discuss a mechanism for bias removal on the estimates.

Dynamic Task Assignment of Autonomous Distributed AGV in an Intelligent FMS Environment

NASA Astrophysics Data System (ADS)

Fauadi, Muhammad Hafidz Fazli Bin Md; Lin, Hao Wen; Murata, Tomohiro

The need of implementing distributed system is growing significantly as it is proven to be effective for organization to be flexible against a highly demanding market. Nevertheless, there are still large technical gaps need to be addressed to gain significant achievement. We propose a distributed architecture to control Automated Guided Vehicle (AGV) operation based on multi-agent architecture. System architectures and agents' functions have been designed to support distributed control of AGV. Furthermore, enhanced agent communication protocol has been configured to accommodate dynamic attributes of AGV task assignment procedure. Result proved that the technique successfully provides a better solution.

Intelligent sensor and controller framework for the power grid

DOEpatents

Akyol, Bora A.; Haack, Jereme Nathan; Craig, Jr., Philip Allen; Tews, Cody William; Kulkarni, Anand V.; Carpenter, Brandon J.; Maiden, Wendy M.; Ciraci, Selim

2015-07-28

Disclosed below are representative embodiments of methods, apparatus, and systems for monitoring and using data in an electric power grid. For example, one disclosed embodiment comprises a sensor for measuring an electrical characteristic of a power line, electrical generator, or electrical device; a network interface; a processor; and one or more computer-readable storage media storing computer-executable instructions. In this embodiment, the computer-executable instructions include instructions for implementing an authorization and authentication module for validating a software agent received at the network interface; instructions for implementing one or more agent execution environments for executing agent code that is included with the software agent and that causes data from the sensor to be collected; and instructions for implementing an agent packaging and instantiation module for storing the collected data in a data container of the software agent and for transmitting the software agent, along with the stored data, to a next destination.

Quantum-enhanced deliberation of learning agents using trapped ions

NASA Astrophysics Data System (ADS)

Dunjko, V.; Friis, N.; Briegel, H. J.

2015-02-01

A scheme that successfully employs quantum mechanics in the design of autonomous learning agents has recently been reported in the context of the projective simulation (PS) model for artificial intelligence. In that approach, the key feature of a PS agent, a specific type of memory which is explored via random walks, was shown to be amenable to quantization, allowing for a speed-up. In this work we propose an implementation of such classical and quantum agents in systems of trapped ions. We employ a generic construction by which the classical agents are ‘upgraded’ to their quantum counterparts by a nested process of adding coherent control, and we outline how this construction can be realized in ion traps. Our results provide a flexible modular architecture for the design of PS agents. Furthermore, we present numerical simulations of simple PS agents which analyze the robustness of our proposal under certain noise models.

Intelligent sensor and controller framework for the power grid

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

Akyol, Bora A.; Haack, Jereme Nathan; Craig, Jr., Philip Allen

Disclosed below are representative embodiments of methods, apparatus, and systems for monitoring and using data in an electric power grid. For example, one disclosed embodiment comprises a sensor for measuring an electrical characteristic of a power line, electrical generator, or electrical device; a network interface; a processor; and one or more computer-readable storage media storing computer-executable instructions. In this embodiment, the computer-executable instructions include instructions for implementing an authorization and authentication module for validating a software agent received at the network interface; instructions for implementing one or more agent execution environments for executing agent code that is included with themore » software agent and that causes data from the sensor to be collected; and instructions for implementing an agent packaging and instantiation module for storing the collected data in a data container of the software agent and for transmitting the software agent, along with the stored data, to a next destination.« less

Study on the E-commerce platform based on the agent

NASA Astrophysics Data System (ADS)

Fu, Ruixue; Qin, Lishuan; Gao, Yinmin

2011-10-01

To solve problem of dynamic integration in e-commerce, the Multi-Agent architecture of electronic commerce platform system based on Agent and Ontology has been introduced, which includes three major types of agent, Ontology and rule collection. In this architecture, service agent and rule are used to realize the business process reengineering, the reuse of software component, and agility of the electronic commerce platform. To illustrate the architecture, a simulation work has been done and the results imply that the architecture provides a very efficient method to design and implement the flexible, distributed, open and intelligent electronic commerce platform system to solve problem of dynamic integration in ecommerce. The objective of this paper is to illustrate the architecture of electronic commerce platform system, and the approach how Agent and Ontology support the electronic commerce platform system.

A decentralised multi-agent approach to enhance the stability of smart microgrids with renewable energy

NASA Astrophysics Data System (ADS)

Rahman, M. S.; Pota, H. R.; Mahmud, M. A.; Hossain, M. J.

2016-05-01

This paper presents the impact of large penetration of wind power on the transient stability through a dynamic evaluation of the critical clearing times (CCTs) by using intelligent agent-based approach. A decentralised multi-agent-based framework is developed, where agents represent a number of physical device models to form a complex infrastructure for computation and communication. They enable the dynamic flow of information and energy for the interaction between the physical processes and their activities. These agents dynamically adapt online measurements and use the CCT information for relay coordination to improve the transient stability of power systems. Simulations are carried out on a smart microgrid system for faults at increasing wind power penetration levels and the improvement in transient stability using the proposed agent-based framework is demonstrated.

Building intelligence in third-generation training and battle simulations

NASA Astrophysics Data System (ADS)

Jacobi, Dennis; Anderson, Don; von Borries, Vance; Elmaghraby, Adel; Kantardzic, Mehmed; Ragade, Rammohan

2003-09-01

Current war games and simulations are primarily attrition based, and are centered on the concept of force on force. They constitute what can be defined as "second generation" war games. So-called "first generation" war games were focused on strategy with the primary concept of mind on mind. We envision "third generation" war games and battle simulations as concentrating on effects with the primary concept being system on system. Thus the third generation systems will incorporate each successive generation and take into account strategy, attrition and effects. This paper will describe the principal advantages and features that need to be implemented to create a true "third generation" battle simulation and the architectural issues faced when designing and building such a system. Areas of primary concern are doctrine, command and control, allied and coalition warfare, and cascading effects. Effectively addressing the interactive effects of these issues is of critical importance. In order to provide an adaptable and modular system that will accept future modifications and additions with relative ease, we are researching the use of a distributed Multi-Agent System (MAS) that incorporates various artificial intelligence methods. The agent architecture can mirror the military command structure from both vertical and horizontal perspectives while providing the ability to make modifications to doctrine, command structures, inter-command communications, as well as model the results of various effects upon one another, and upon the components of the simulation. This is commonly referred to as "cascading effects," in which A affects B, B affects C and so on. Agents can be used to simulate units or parts of units that interact to form the whole. Even individuals can eventually be simulated to take into account the affect to key individuals such as commanders, heroes, and aces. Each agent will have a learning component built in to provide "individual intelligence" based on experience.

Emergence of trend trading and its effects in minority game

NASA Astrophysics Data System (ADS)

Liu, Xing-Hua; Liang, Xiao-Bei; Wang, Nai-Jing

2006-09-01

In this paper, we extended Minority Game (MG) by equipping agents with both value and trend strategies. In the new model, agents (we call them strong-adaptation agents) can autonomically select to act as trend trader or value trader when they game and learn in system. So the new model not only can reproduce stylized factors but also has the potential to investigate into the process of some problems of securities market. We investigated the dynamics of trend trading and its impacts on securities market based on the new model. Our research found that trend trading is inevitable when strong-adaptation agents make decisions by inductive reasoning. Trend trading (of strong-adaptation agents) is not irrational behavior but shows agent's strong-adaptation intelligence, because strong-adaptation agents can take advantage of the pure value agents when they game together in hybrid system. We also found that strong-adaptation agents do better in real environment. The results of our research are different with those of behavior finance researches.

Celestial data routing network

NASA Astrophysics Data System (ADS)

Bordetsky, Alex

2000-11-01

Imagine that information processing human-machine network is threatened in a particular part of the world. Suppose that an anticipated threat of physical attacks could lead to disruption of telecommunications network management infrastructure and access capabilities for small geographically distributed groups engaged in collaborative operations. Suppose that small group of astronauts are exploring the solar planet and need to quickly configure orbital information network to support their collaborative work and local communications. The critical need in both scenarios would be a set of low-cost means of small team celestial networking. To the geographically distributed mobile collaborating groups such means would allow to maintain collaborative multipoint work, set up orbital local area network, and provide orbital intranet communications. This would be accomplished by dynamically assembling the network enabling infrastructure of the small satellite based router, satellite based Codec, and set of satellite based intelligent management agents. Cooperating single function pico satellites, acting as agents and personal switching devices together would represent self-organizing intelligent orbital network of cooperating mobile management nodes. Cooperative behavior of the pico satellite based agents would be achieved by comprising a small orbital artificial neural network capable of learning and restructing the networking resources in response to the anticipated threat.

iMuseumA: an agent-based context-aware intelligent museum system.

PubMed

Ayala, Inmaculada; Amor, Mercedes; Pinto, Mónica; Fuentes, Lidia; Gámez, Nadia

2014-11-10

Currently, museums provide their visitors with interactive tour guide applications that can be installed in mobile devices and provide timely tailor-made multimedia information about exhibits on display. In this paper, we argue that mobile devices not only could provide help to visitors, but also to museum staff. Our goal is to integrate, within the same system, multimedia tour guides with the management facilities required by museums. In this paper, we present iMuseumA (intelligent museum with agents), a mobile-based solution to customize visits and perform context-aware management tasks. iMuseumA follows an agent-based approach, which makes it possible to interact easily with the museum environment and make decisions based on its current status. This system is currently deployed in the Museum of Informatics at the Informatics School of the University of Málaga, and its main contributions are: (i) a mobile application that provides management facilities to museum staff by means of sensing and processing environmental data; (ii) providing an integrated solution for visitors, tour guides and museum staff that allows coordination and communication enrichment among different groups of users; (iii) using and benefiting from group communication for heterogeneous groups of users that can be created on demand.

A Proposed Intelligent Policy-Based Interface for a Mobile eHealth Environment

NASA Astrophysics Data System (ADS)

Tavasoli, Amir; Archer, Norm

Users of mobile eHealth systems are often novices, and the learning process for them may be very time consuming. In order for systems to be attractive to potential adopters, it is important that the interface should be very convenient and easy to learn. However, the community of potential users of a mobile eHealth system may be quite varied in their requirements, so the system must be able to adapt easily to suit user preferences. One way to accomplish this is to have the interface driven by intelligent policies. These policies can be refined gradually, using inputs from potential users, through intelligent agents. This paper develops a framework for policy refinement for eHealth mobile interfaces, based on dynamic learning from user interactions.

Neurosciences and research on chemical weapons of mass destruction in Nazi Germany.

PubMed

Schmaltz, Florian

2006-09-01

As a side-product of industrial research, new chemical nerve agents (Tabun, Sarin, Soman) superior to those available to the Allied Forces were discovered in Nazi Germany. These agents were never used by Germany, even though they were produced at a large scale. This article explores the toxicological and physiological research into the mechanisms of action of these novel nerve agents, and the emergence of military research objectives in neurophysiological and neurotoxicological research. Recently declassified Allied military intelligence files document secret nerve agent research, leading to intensified research on anticholinesterase agents in the peripheral and the central nervous system. The article discusses the involvement of IG Farben scientists, educational, medical and military institutions, and of Nobel Prize laureate Richard Kuhn, director of the Kaiser Wilhelm Institute for Medical Research.

32 CFR 2004.22 - Operational Responsibilities [202(a)].

Code of Federal Regulations, 2010 CFR

2010-07-01

...; (3) Sign agreements with the Department of Defense as the Executive Agent for industrial security services; and, (4) Ensure applicable department and agency personnel having NISP implementation... of the Director of National Intelligence (ODNI) for Sensitive Compartmented Information, and DOE for...

Heterogeneous Multi-Robot Cooperation

DTIC Science & Technology

1994-02-01

1992a) Maja Mataric. Designing emergent behaviors: From local interac- tions to collective intelligence. In J. Meyer, H. Roitblat , and S. Wilson, editors...1992] Lynne E. Parker. Adaptive action selection for cooperative agent teams. In Jean-Arcady Meyer, Herbert Roitblat . and Stewart Wilson. editors

A Survey of Collective Intelligence

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Tumer, Kagan

1999-01-01

This chapter presents the science of "COllective INtelligence" (COIN). A COIN is a large multi-agent systems where: i) the agents each run reinforcement learning (RL) algorithms; ii) there is little to no centralized communication or control; iii) there is a provided world utility function that, rates the possible histories of tile full system. Tile conventional approach to designing large distributed systems to optimize a world utility does not use agents running RL algorithms. Rather that approach begins with explicit modeling of the overall system's dynamics, followed by detailed hand-tuning of the interactions between the components to ensure that they "cooperate" as far as the world utility is concerned. This approach is labor-intensive, often results in highly non-robust systems, and usually results in design techniques that, have limited applicability. In contrast, with COINs we wish to solve the system design problems implicitly, via the 'adaptive' character of the RL algorithms of each of the agents. This COIN approach introduces an entirely new, profound design problem: Assuming the RL algorithms are able to achieve high rewards, what reward functions for the individual agents will, when pursued by those agents, result in high world utility? In other words, what reward functions will best ensure that we do not have phenomena like the tragedy of the commons, or Braess's paradox? Although still very young, the science of COINs has already resulted in successes in artificial domains, in particular in packet-routing, the leader-follower problem, and in variants of Arthur's "El Farol bar problem". It is expected that as it matures not only will COIN science expand greatly the range of tasks addressable by human engineers, but it will also provide much insight into already established scientific fields, such as economics, game theory, or population biology.

Autonomy in robots and other agents.

PubMed

Smithers, T

1997-06-01

The word "autonomous" has become widely used in artificial intelligence, robotics, and, more recently, artificial life and is typically used to qualify types of systems, agents, or robots: we see terms like "autonomous systems," "autonomous agents," and "autonomous robots." Its use in these fields is, however, both weak, with no distinctions being made that are not better and more precisely made with other existing terms, and varied, with no single underlying concept being involved. This ill-disciplined usage contrasts strongly with the use of the same term in other fields such as biology, philosophy, ethics, law, and human rights, for example. In all these quite different areas the concept of autonomy is essentially the same, though the language used and the aspects and issues of concern, of course, differ. In all these cases the underlying notion is one of self-law making and the closely related concept of self-identity. In this paper I argue that the loose and varied use of the term autonomous in artificial intelligence, robotics, and artificial life has effectively robbed these fields of an important concept. A concept essentially the same as we find it in biology, philosophy, ethics, and law, and one that is needed to distinguish a particular kind of agent or robot from those developed and built so far. I suggest that robots and other agents will have to be autonomous, i.e., self-law making, not just self-regulating, if they are to be able effectively to deal with the kinds of environments in which we live and work: environments which have significant large scale spatial and temporal invariant structure, but which also have large amounts of local spatial and temporal dynamic variation and unpredictability, and which lead to the frequent occurrence of previously unexperienced situations for the agents that interact with them.

76 FR 25407 - Additional Designations, Foreign Narcotics Kingpin Designation Act

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-04

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The Fourth Law of Robotics.

ERIC Educational Resources Information Center

Markoff, John

1994-01-01

Discusses intelligent software agents, or knowledge robots (knowbots), and the impact they have on the Internet. Topics addressed include ethical dilemmas; problems created by rapid growth on the Internet; new technologies that are amplifying growth; and a shift to a market economy and resulting costs. (LRW)

Agent-Supported Mission Operations Teamwork

NASA Technical Reports Server (NTRS)

Malin, Jane T.

2003-01-01

This slide presentation reviews the development of software agents to support of mission operations teamwork. The goals of the work was to make automation by agents easy to use, supervise and direct, manage information and communication to decrease distraction, interruptions, workload and errors, reduce mission impact of off-nominal situations and increase morale and decrease turnover. The accomplishments or the project are: 1. Collaborative agents - mixed initiative and creation of instructions for mediating agent 2. Methods for prototyping, evaluating and evolving socio-technical systems 3. Technology infusion: teamwork tools in mISSIons 4. Demonstrations in simulation testbed An example of the use of agent is given, the use of an agent to monitor a N2 tank leak. An incomplete instruction to the agent is handled with mediating assistants, or Intelligent Briefing and Response Assistant (IBRA). The IBRA Engine also watches data stream for triggers and executes Act-Whenever actions. There is also a Briefing and Response Instruction (BRI) which is easy for a discipline specialist to create through a BRI editor.

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

IDEA: Planning at the Core of Autonomous Reactive Agents

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Dorais, Gregory A.; Fry, Chuck; Levinson, Richard; Plaunt, Christian; Clancy, Daniel (Technical Monitor)

2002-01-01

Several successful autonomous systems are separated into technologically diverse functional layers operating at different levels of abstraction. This diversity makes them difficult to implement and validate. In this paper, we present IDEA (Intelligent Distributed Execution Architecture), a unified planning and execution framework. In IDEA a layered system can be implemented as separate agents, one per layer, each representing its interactions with the world in a model. At all levels, the model representation primitives and their semantics is the same. Moreover, each agent relies on a single model, plan database, plan runner and on a variety of planners, both reactive and deliberative. The framework allows the specification of agents that operate, within a guaranteed reaction time and supports flexible specification of reactive vs. deliberative agent behavior. Within the IDEA framework we are working to fully duplicate the functionalities of the DS1 Remote Agent and extend it to domains of higher complexity than autonomous spacecraft control.

Minority game and anomalies in financial markets

NASA Astrophysics Data System (ADS)

Liu, Xinghua; Liang, Xiaobei; Tang, Bingyong

2004-02-01

The minority game (MG), which is intrinsically associated with financial markets, is an agent-based model of a competing population with limited resources. We find that the fluctuation features of MG in crowded region are more similar to real market than that of in perfect cooperation region. So we propose and study a modified model based on the MG in which agents accumulate virtual points for their strategies from the last H steps instead of from the beginning of the game. The results of numerical simulations on our new model show that agents will be more intelligent, and the types of features of fluctuations are the same in real-world market. We also give a numerical explanation of the high adaptability of agents in new model.

Multi Agent Systems with Symbiotic Learning and Evolution using GNP

NASA Astrophysics Data System (ADS)

Eguchi, Toru; Hirasawa, Kotaro; Hu, Jinglu; Murata, Junichi

Recently, various attempts relevant to Multi Agent Systems (MAS) which is one of the most promising systems based on Distributed Artificial Intelligence have been studied to control large and complicated systems efficiently. In these trends of MAS, Multi Agent Systems with Symbiotic Learning and Evolution named Masbiole has been proposed. In Masbiole, symbiotic phenomena among creatures are considered in the process of learning and evolution of MAS. So we can expect more flexible and sophisticated solutions than conventional MAS. In this paper, we apply Masbiole to Iterative Prisoner’s Dilemma Games (IPD Games) using Genetic Network Programming (GNP) which is a newly developed evolutionary computation method for constituting agents. Some characteristics of Masbiole using GNP in IPD Games are clarified.

Research on monitoring system of water resources in Shiyang River Basin based on Multi-agent

NASA Astrophysics Data System (ADS)

Zhao, T. H.; Yin, Z.; Song, Y. Z.

2012-11-01

The Shiyang River Basin is the most populous, economy relatively develop, the highest degree of development and utilization of water resources, water conflicts the most prominent, ecological environment problems of the worst hit areas in Hexi inland river basin in Gansu province. the contradiction between people and water is aggravated constantly in the basin. This text combines multi-Agent technology with monitoring system of water resource, the establishment of a management center, telemetry Agent Federation, as well as the communication network between the composition of the Shiyang River Basin water resources monitoring system. By taking advantage of multi-agent system intelligence and communications coordination to improve the timeliness of the basin water resources monitoring.

Toward Agent Programs with Circuit Semantics

NASA Technical Reports Server (NTRS)

Nilsson, Nils J.

1992-01-01

New ideas are presented for computing and organizing actions for autonomous agents in dynamic environments-environments in which the agent's current situation cannot always be accurately discerned and in which the effects of actions cannot always be reliably predicted. The notion of 'circuit semantics' for programs based on 'teleo-reactive trees' is introduced. Program execution builds a combinational circuit which receives sensory inputs and controls actions. These formalisms embody a high degree of inherent conditionality and thus yield programs that are suitably reactive to their environments. At the same time, the actions computed by the programs are guided by the overall goals of the agent. The paper also speculates about how programs using these ideas could be automatically generated by artificial intelligence planning systems and adapted by learning methods.

Designing Smart Health Care Technology into the Home of the Future

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

Warren, S.; Craft, R.L.; Bosma, J.T.

1999-04-07

The US health care industry is experiencing a substantial paradigm shift with regard to home care due to the convergence of several technology areas. Increasingly-capable telehealth systems and the internet are not only moving the point of care closer to the patient, but the patient can now assume a more active role in his or her own care. These technologies, coupled with (1) the migration of the health care industry to electronic patient records and (2) the emergence of a growing number of enabling health care technologies (e.g., novel biosensors, wearable devices, and intelligent software agents), demonstrate unprecedented potential formore » delivering highly automated, intelligent health care in the home. This editorial paper presents a vision for the implementation of intelligent health care technology in the home of the future, focusing on areas of research that have the highest potential payoff given targeted government funding over the next ten years. Here, intelligent health care technology means smart devices and systems that are aware of their context and can therefore assimilate information to support care decisions. A systems perspective is used to describe a framework under which devices can interact with one another in a plug-and-play manner. Within this infrastructure, traditionally passive sensors and devices will have read/write access to appropriate portions of an individual's electronic medical record. Through intelligent software agents, plug-and-play mechanisms, messaging standards, and user authentication tools, these smart home-based medical devices will be aware of their own capabilities, their relationship to the other devices in the home system, and the identity of the individual(s) from whom they acquire data. Information surety technology will be essential to maintain the confidentiality of patient-identifiable medical information and to protect the integrity of geographically dispersed electronic medical records with which each home-based system will interact.« less

Study of simple land battles using agent-based modeling: Strategy and emergent phenomena

NASA Astrophysics Data System (ADS)

Westley, Alexandra; de Meglio, Nicholas; Hager, Rebecca; Mok, Jorge Wu; Shanahan, Linda; Sen, Surajit

2017-04-01

In this paper, we expand upon our recent studies of an agent-based model of a battle between an intelligent army and an insurgent army to explore the role of modifying strategy according to the state of the battle (adaptive strategy) on battle outcomes. This model leads to surprising complexity and rich possibilities in battle outcomes, especially in battles between two well-matched sides. We contend that the use of adaptive strategies may be effective in winning battles.

Development and Evaluation of Sensor Concepts for Ageless Aerospace Vehicles: Report 4 - Phase 1 Implementation of the Concept Demonstrator

NASA Technical Reports Server (NTRS)

Abbott, David; Batten, Adam; Carpenter, David; Dunlop, John; Edwards, Graeme; Farmer, Tony; Gaffney, Bruce; Hedley, Mark; Hoschke, Nigel; Isaacs, Peter;

Pattern detection in forensic case data using graph theory: application to heroin cutting agents.

PubMed

Terrettaz-Zufferey, Anne-Laure; Ratle, Frédéric; Ribaux, Olivier; Esseiva, Pierre; Kanevski, Mikhail

2007-04-11

Pattern recognition techniques can be very useful in forensic sciences to point out to relevant sets of events and potentially encourage an intelligence-led style of policing. In this study, these techniques have been applied to categorical data corresponding to cutting agents found in heroin seizures. An application of graph theoretic methods has been performed, in order to highlight the possible relationships between the location of seizures and co-occurrences of particular heroin cutting agents. An analysis of the co-occurrences to establish several main combinations has been done. Results illustrate the practical potential of mathematical models in forensic data analysis.

Material quality assessment of silk nanofibers based on swarm intelligence

NASA Astrophysics Data System (ADS)

Brandoli Machado, Bruno; Nunes Gonçalves, Wesley; Martinez Bruno, Odemir

2013-02-01

In this paper, we propose a novel approach for texture analysis based on artificial crawler model. Our method assumes that each agent can interact with the environment and each other. The evolution process converges to an equilibrium state according to the set of rules. For each textured image, the feature vector is composed by signatures of the live agents curve at each time. Experimental results revealed that combining the minimum and maximum signatures into one increase the classification rate. In addition, we pioneer the use of autonomous agents for characterizing silk fibroin scaffolds. The results strongly suggest that our approach can be successfully employed for texture analysis.

Plan execution monitoring with distributed intelligent agents for battle command

NASA Astrophysics Data System (ADS)

Allen, James P.; Barry, Kevin P.; McCormick, John M.; Paul, Ross A.

2004-07-01

As military tactics evolve toward execution centric operations the ability to analyze vast amounts of mission relevant data is essential to command and control decision making. To maintain operational tempo and achieve information superiority we have developed Vigilant Advisor, a mobile agent-based distributed Plan Execution Monitoring system. It provides military commanders with continuous contingency monitoring tailored to their preferences while overcoming the network bandwidth problem often associated with traditional remote data querying. This paper presents an overview of Plan Execution Monitoring as well as a detailed view of the Vigilant Advisor system including key features and statistical analysis of resource savings provided by its mobile agent-based approach.

Evolutionary Intelligence and Communication in Societies of Virtually Embodied Agents

NASA Astrophysics Data System (ADS)

Nguyen, Binh; Skabar, Andrew

In order to overcome the knowledge bottleneck problem, AI researchers have attempted to develop systems that are capable of automated knowledge acquisition. However, learning in these systems is hindered by context (i.e., symbol-grounding) problems, which are caused by the systems lacking the unifying structure of bodies, situations and needs that typify human learning. While the fields of Embodied Artificial Intelligence and Artificial Life have come a long way towards demonstrating how artificial systems can develop knowledge of the physical and social worlds, the focus in these areas has been on low level intelligence, and it is not clear how, such systems can be extended to deal with higher-level knowledge. In this paper, we argue that we can build towards a higher level intelligence by framing the problem as one of stimulating the development of culture and language. Specifically, we identify three important limitations that face the development of culture and language in AI systems, and propose how these limitations can be overcome. We will do this through borrowing ideas from the evolutionary sciences, which have explored how interactions between embodiment and environment have shaped the development of human intelligence and knowledge.

Agent Models for Self-Motivated Home-Assistant Bots

NASA Astrophysics Data System (ADS)

Merrick, Kathryn; Shafi, Kamran

2010-01-01

Modern society increasingly relies on technology to support everyday activities. In the past, this technology has focused on automation, using computer technology embedded in physical objects. More recently, there is an expectation that this technology will not just embed reactive automation, but also embed intelligent, proactive automation in the environment. That is, there is an emerging desire for novel technologies that can monitor, assist, inform or entertain when required, and not just when requested. This paper presents three self-motivated, home-assistant bot applications using different self-motivated agent models. Self-motivated agents use a computational model of motivation to generate goals proactively. Technologies based on self-motivated agents can thus respond autonomously and proactively to stimuli from their environment. Three prototypes of different self-motivated agent models, using different computational models of motivation, are described to demonstrate these concepts.

Intelligent Motion and Interaction Within Virtual Environments

NASA Technical Reports Server (NTRS)

Ellis, Stephen R. (Editor); Slater, Mel (Editor); Alexander, Thomas (Editor)

2007-01-01

What makes virtual actors and objects in virtual environments seem real? How can the illusion of their reality be supported? What sorts of training or user-interface applications benefit from realistic user-environment interactions? These are some of the central questions that designers of virtual environments face. To be sure simulation realism is not necessarily the major, or even a required goal, of a virtual environment intended to communicate specific information. But for some applications in entertainment, marketing, or aspects of vehicle simulation training, realism is essential. The following chapters will examine how a sense of truly interacting with dynamic, intelligent agents may arise in users of virtual environments. These chapters are based on presentations at the London conference on Intelligent Motion and Interaction within a Virtual Environments which was held at University College, London, U.K., 15-17 September 2003.

75 FR 14255 - Additional Designations, Foreign Narcotics Kingpin Designation Act

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2010-03-24

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75 FR 36474 - Additional Designations, Foreign Narcotics Kingpin Designation Act

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-25

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From General Game Descriptions to a Market Specification Language for General Trading Agents

NASA Astrophysics Data System (ADS)

Thielscher, Michael; Zhang, Dongmo

The idea behind General Game Playing is to build systems that, instead of being programmed for one specific task, are intelligent and flexible enough to negotiate an unknown environment solely on the basis of the rules which govern it. In this paper, we argue that this principle has the great potential to bring to a new level artificially intelligent systems in other application areas as well. Our specific interest lies in General Trading Agents, which are able to understand the rules of unknown markets and then to actively participate in them without human intervention. To this end, we extend the general Game Description Language into a language that allows to formally describe arbitrary markets in such a way that these specifications can be automatically processed by a computer. We present both syntax and a transition-based semantics for this Market Specification Language and illustrate its expressive power by presenting axiomatizations of several well-known auction types.

Multidimensional Learner Model In Intelligent Learning System

NASA Astrophysics Data System (ADS)

Deliyska, B.; Rozeva, A.

2009-11-01

The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e-learning in an online learner-centered environment. ILS is a distributed e-learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e-learning is achieved through the resources of the Semantic Web and is designed and developed around a course, group of courses or specialty. An essential part of ILS is learner model database which contains structured data about learner profile and temporal status in the learning process of one or more courses. In the paper a learner model position in ILS is considered and a relational database is designed from learner's domain ontology. Multidimensional modeling agent for the source database is designed and resultant learner data cube is presented. Agent's modules are proposed with corresponding algorithms and procedures. Multidimensional (OLAP) analysis guidelines on the resultant learner module for designing dynamic learning strategy have been highlighted.

Distributed Cooperation Solution Method of Complex System Based on MAS

NASA Astrophysics Data System (ADS)

Weijin, Jiang; Yuhui, Xu

To adapt the model in reconfiguring fault diagnosing to dynamic environment and the needs of solving the tasks of complex system fully, the paper introduced multi-Agent and related technology to the complicated fault diagnosis, an integrated intelligent control system is studied in this paper. Based on the thought of the structure of diagnostic decision and hierarchy in modeling, based on multi-layer decomposition strategy of diagnosis task, a multi-agent synchronous diagnosis federation integrated different knowledge expression modes and inference mechanisms are presented, the functions of management agent, diagnosis agent and decision agent are analyzed, the organization and evolution of agents in the system are proposed, and the corresponding conflict resolution algorithm in given, Layered structure of abstract agent with public attributes is build. System architecture is realized based on MAS distributed layered blackboard. The real world application shows that the proposed control structure successfully solves the fault diagnose problem of the complex plant, and the special advantage in the distributed domain.

Increasing Physical Activity Amongst Overweight and Obese Cancer Survivors Using an Alexa-Based Intelligent Agent for Patient Coaching: Protocol for the Physical Activity by Technology Help (PATH) Trial

PubMed Central

Schrack, Jennifer; Naiman, Daniel; Lansey, Dina; Baig, Yasmin; Stearns, Vered; Celentano, David; Martin, Seth; Appel, Lawrence

2018-01-01

Background Physical activity has established health benefits, but motivation and adherence remain challenging. Objective We designed and launched a three-arm randomized trial to test artificial intelligence technology solutions to increase daily physical activity in cancer survivors. Methods A single-center, three-arm randomized clinical trial with an allocation ration of 1:1:1: (A) control, in which participants are provided written materials about the benefits of physical activity; (B) text intervention, where participants receive daily motivation from a fully automated, data-driven algorithmic text message via mobile phone (Coachtext); and (C) Voice Assist intervention, where participants are provided with an in-home on demand autonomous Intelligent Agent using data driven Interactive Digital Voice Assist on the Amazon Alexa/Echo (MyCoach). Results The study runs for 5 weeks: a one-week run-in to establish baseline, followed by 4 weeks of intervention. Data for study outcomes is collected automatically through a wearable sensor, and data are transferred in real-time to the study server. The recruitment goal is 42 participants, 14 in each arm. Electronic health records are used to prescreen candidates, with 39 participants recruited to date. Discussion This study aims to investigate the effects of different types of intelligent technology solutions on promoting physical activity in cancer survivors. This innovative approach can easily be expanded and customized to other interventions. Early lessons from our initial participants are helping us develop additional advanced solutions to improve health outcomes. Trial Registration Retrospectively registered on July 10, 2017 at ClinicalTrials.gov: NCT03212079; https://clinicaltrials.gov/ct2/show/NCT03212079 (Archived by WebCite at http://www.webcitation.org/6wgvqjTji) PMID:29434016

A self-taught artificial agent for multi-physics computational model personalization.

PubMed

Neumann, Dominik; Mansi, Tommaso; Itu, Lucian; Georgescu, Bogdan; Kayvanpour, Elham; Sedaghat-Hamedani, Farbod; Amr, Ali; Haas, Jan; Katus, Hugo; Meder, Benjamin; Steidl, Stefan; Hornegger, Joachim; Comaniciu, Dorin

2016-12-01

Personalization is the process of fitting a model to patient data, a critical step towards application of multi-physics computational models in clinical practice. Designing robust personalization algorithms is often a tedious, time-consuming, model- and data-specific process. We propose to use artificial intelligence concepts to learn this task, inspired by how human experts manually perform it. The problem is reformulated in terms of reinforcement learning. In an off-line phase, Vito, our self-taught artificial agent, learns a representative decision process model through exploration of the computational model: it learns how the model behaves under change of parameters. The agent then automatically learns an optimal strategy for on-line personalization. The algorithm is model-independent; applying it to a new model requires only adjusting few hyper-parameters of the agent and defining the observations to match. The full knowledge of the model itself is not required. Vito was tested in a synthetic scenario, showing that it could learn how to optimize cost functions generically. Then Vito was applied to the inverse problem of cardiac electrophysiology and the personalization of a whole-body circulation model. The obtained results suggested that Vito could achieve equivalent, if not better goodness of fit than standard methods, while being more robust (up to 11% higher success rates) and with faster (up to seven times) convergence rate. Our artificial intelligence approach could thus make personalization algorithms generalizable and self-adaptable to any patient and any model. Copyright © 2016. Published by Elsevier B.V.

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Characterizing Exposure-Related Behaviors Using Agent-Based Models Embedded with Needs-Based Artificial Intelligence

EPA Science Inventory

Information on where and how individuals spend their time is important for characterizing exposures to chemicals in consumer products and in indoor environments. Traditionally, exposure assessors have relied on time-use surveys in order to obtain information on exposure-related b...

The CIA-Media Connection.

ERIC Educational Resources Information Center

Zerbinos, Eugenia

The Central Intelligence Agency (CIA) has paid journalists, used information from unpaid journalists, owned foreign media outlets, planted stories, and put the lid on other stories throughout its 30-year history. Journalism makes a good cover for agents because journalists can ask questions without arousing suspicion. It has been estimated that…

The Warfighter Associate: decision-support software agent for the management of intelligence, surveillance, and reconnaissance (ISR) assets

NASA Astrophysics Data System (ADS)

Buchler, Norbou; Marusich, Laura R.; Sokoloff, Stacey

2014-06-01

A unique and promising intelligent agent plug-in technology for Mission Command Systems— the Warfighter Associate (WA)— is described that enables individuals and teams to respond more effectively to the cognitive challenges of Mission Command, such as managing limited intelligence, surveillance, and reconnaissance (ISR) assets and information sharing in a networked environment. The WA uses a doctrinally-based knowledge representation to model role-specific workflows and continuously monitors the state of the operational environment to enable decision-support, delivering the right information to the right person at the right time. Capabilities include: (1) analyzing combat events reported in chat rooms and other sources for relevance based on role, order-of-battle, time, and geographic location, (2) combining seemingly disparate pieces of data into meaningful information, (3) driving displays to provide users with map based and textual descriptions of the current tactical situation, and (4) recommending courses of action with respect to necessary staff collaborations, execution of battle-drills, re-tasking of ISR assets, and required reporting. The results of a scenario-based human-in-the-loop experiment are reported. The underlying WA knowledge-graph representation serves as state traces, measuring aspects of Soldier decision-making performance (e.g. improved efficiency in allocating limited ISR assets) across runtime as dynamic events unfold on a simulated battlefield.

A Mission Planning Approach for Precision Farming Systems Based on Multi-Objective Optimization.

PubMed

Zhai, Zhaoyu; Martínez Ortega, José-Fernán; Lucas Martínez, Néstor; Rodríguez-Molina, Jesús

2018-06-02

As the demand for food grows continuously, intelligent agriculture has drawn much attention due to its capability of producing great quantities of food efficiently. The main purpose of intelligent agriculture is to plan agricultural missions properly and use limited resources reasonably with minor human intervention. This paper proposes a Precision Farming System (PFS) as a Multi-Agent System (MAS). Components of PFS are treated as agents with different functionalities. These agents could form several coalitions to complete the complex agricultural missions cooperatively. In PFS, mission planning should consider several criteria, like expected benefit, energy consumption or equipment loss. Hence, mission planning could be treated as a Multi-objective Optimization Problem (MOP). In order to solve MOP, an improved algorithm, MP-PSOGA, is proposed, taking advantages of the Genetic Algorithms and Particle Swarm Optimization. A simulation, called precise pesticide spraying mission, is performed to verify the feasibility of the proposed approach. Simulation results illustrate that the proposed approach works properly. This approach enables the PFS to plan missions and allocate scarce resources efficiently. The theoretical analysis and simulation is a good foundation for the future study. Once the proposed approach is applied to a real scenario, it is expected to bring significant economic improvement.

iMuseumA: An Agent-Based Context-Aware Intelligent Museum System

PubMed Central

Ayala, Inmaculada; Amor, Mercedes; Pinto, Mónica; Fuentes, Lidia; Gámez, Nadia

2014-01-01

Currently, museums provide their visitors with interactive tour guide applications that can be installed in mobile devices and provide timely tailor-made multimedia information about exhibits on display. In this paper, we argue that mobile devices not only could provide help to visitors, but also to museum staff. Our goal is to integrate, within the same system, multimedia tour guides with the management facilities required by museums. In this paper, we present iMuseumA (intelligent museum with agents), a mobile-based solution to customize visits and perform context-aware management tasks. iMuseumA follows an agent-based approach, which makes it possible to interact easily with the museum environment and make decisions based on its current status. This system is currently deployed in the Museum of Informatics at the Informatics School of the University of Málaga, and its main contributions are: (i) a mobile application that provides management facilities to museum staff by means of sensing and processing environmental data; (ii) providing an integrated solution for visitors, tour guides and museum staff that allows coordination and communication enrichment among different groups of users; (iii) using and benefiting from group communication for heterogeneous groups of users that can be created on demand. PMID:25390409

Exchanging large data object in multi-agent systems

NASA Astrophysics Data System (ADS)

Al-Yaseen, Wathiq Laftah; Othman, Zulaiha Ali; Nazri, Mohd Zakree Ahmad

2016-08-01

One of the Business Intelligent solutions that is currently in use is the Multi-Agent System (MAS). Communication is one of the most important elements in MAS, especially for exchanging large low level data between distributed agents (physically). The Agent Communication Language in JADE has been offered as a secure method for sending data, whereby the data is defined as an object. However, the object cannot be used to send data to another agent in a different location. Therefore, the aim of this paper was to propose a method for the exchange of large low level data as an object by creating a proxy agent known as a Delivery Agent, which temporarily imitates the Receiver Agent. The results showed that the proposed method is able to send large-sized data. The experiments were conducted using 16 datasets ranging from 100,000 to 7 million instances. However, for the proposed method, the RAM and the CPU machine had to be slightly increased for the Receiver Agent, but the latency time was not significantly different compared to the use of the Java Socket method (non-agent and less secure). With such results, it was concluded that the proposed method can be used to securely send large data between agents.

Modeling Being "Lost": Imperfect Situation Awareness

NASA Technical Reports Server (NTRS)

Middleton, Victor E.

2011-01-01

Being "lost" is an exemplar of imperfect Situation Awareness/Situation Understanding (SA/SU) -- information/knowledge that is uncertain, incomplete, and/or just wrong. Being "lost" may be a geo-spatial condition - not knowing/being wrong about where to go or how to get there. More broadly, being "lost" can serve as a metaphor for uncertainty and/or inaccuracy - not knowing/being wrong about how one fits into a larger world view, what one wants to do, or how to do it. This paper discusses using agent based modeling (ABM) to explore imperfect SA/SU, simulating geo-spatially "lost" intelligent agents trying to navigate in a virtual world. Each agent has a unique "mental map" -- its idiosyncratic view of its geo-spatial environment. Its decisions are based on this idiosyncratic view, but behavior outcomes are based on ground truth. Consequently, the rate and degree to which an agent's expectations diverge from ground truth provide measures of that agent's SA/SU.

A Real-Time Rover Executive based On Model-Based Reactive Planning

NASA Technical Reports Server (NTRS)

Bias, M. Bernardine; Lemai, Solange; Muscettola, Nicola; Korsmeyer, David (Technical Monitor)

2003-01-01

This paper reports on the experimental verification of the ability of IDEA (Intelligent Distributed Execution Architecture) effectively operate at multiple levels of abstraction in an autonomous control system. The basic hypothesis of IDEA is that a large control system can be structured as a collection of interacting control agents, each organized around the same fundamental structure. Two IDEA agents, a system-level agent and a mission-level agent, are designed and implemented to autonomously control the K9 rover in real-time. The system is evaluated in the scenario where the rover must acquire images from a specified set of locations. The IDEA agents are responsible for enabling the rover to achieve its goals while monitoring the execution and safety of the rover and recovering from dangerous states when necessary. Experiments carried out both in simulation and on the physical rover, produced highly promising results.

Fairness emergence from zero-intelligence agents

NASA Astrophysics Data System (ADS)

Duan, Wen-Qi; Stanley, H. Eugene

2010-02-01

Fairness plays a key role in explaining the emergence and maintenance of cooperation. Opponent-oriented social utility models were often proposed to explain the origins of fairness preferences in which agents take into account not only their own outcomes but are also concerned with the outcomes of their opponents. Here, we propose a payoff-oriented mechanism in which agents update their beliefs only based on the payoff signals of the previous ultimatum game, regardless of the behaviors and outcomes of the opponents themselves. Employing adaptive ultimatum game, we show that (1) fairness behaviors can emerge out even under such minimalist assumptions, provided that agents are capable of responding to their payoff signals, (2) the average game payoff per agent per round decreases with the increasing discrepancy rate between the average giving rate and the average asking rate, and (3) the belief update process will lead to 50%-50% fair split provided that there is no mutation in the evolutionary dynamics.

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75 FR 42487 - Supplementary Identifying Information of Previously-Designated Individual, Foreign Narcotics...

Federal Register 2010, 2011, 2012, 2013, 2014

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Predicting Exposure to Consumer-Products Using Agent-Based Models Embedded with Needs-Based Artificial Intelligence and Empirically -Based Scheduling Models

EPA Science Inventory

Information on human behavior and consumer product use is important for characterizing exposures to chemicals in consumer products and in indoor environments. Traditionally, exposure-assessors have relied on time-use surveys to obtain information on exposure-related behavior. In ...

Towards a Semantic-Based Approach for Affect and Metaphor Detection

ERIC Educational Resources Information Center

Zhang, Li; Barnden, John

2013-01-01

Affect detection from open-ended virtual improvisational contexts is a challenging task. To achieve this research goal, the authors developed an intelligent agent which was able to engage in virtual improvisation and perform sentence-level affect detection from user inputs. This affect detection development was efficient for the improvisational…

Artificial Intelligence in a German Adventure Game: Spion in PROLOG.

ERIC Educational Resources Information Center

Molla, Steven R.; And Others

1988-01-01

Spion, an adventure game for intermediate and advanced college German students, requires players to communicate with a fictitious agent in complete, correct German sentences. The spy game was written in PROLOG, runs on an IBM-PC, and is available at no cost for noncommercial purposes. (Author/CB)

A Black Hole Attack Model for Reactive Ad-Hoc Protocols

DTIC Science & Technology

2012-03-01

Technology Conference. IEEE, 2003. pp. 2286-2290. [BhS09] N. Bhalaji, and A. Shanmugam. "Association Between Nodes to Combat Blackhole Attack in DSR...2012. 102 [PSA09] A. Prathapani, L. Santhanam, and P. Agrawal. "Intelligent Honeypot Agent for Blackhole Attack Detection in Wireless Mesh

Bibliography of Intelligence Literature. A Critical and Annotated Bibliography of Open-Source Literature.

DTIC Science & Technology

1985-01-01

outlooks in a continuing, important battlefield. HAREL, Isser. The House on Garibaldi Street: The First Full Account of the Capture of Adolf Eichmann ...Israeli Service, MOSSAD, describes in detailed fashion the long-range, in-depth planning and operation for the Eichmann capture by Israeli agents in

Intelligent Agent-Supported Online Education

ERIC Educational Resources Information Center

Li, Xiaoqing

2007-01-01

With the development of Internet technologies, online distance education is becoming an important format for teaching, learning, and instruction. In the 21st century, bleeding edge technologies make it possible for more and more students, especially adults, to benefit from an online education. This new paradigm in education allows students to…

Metrics of a Paradigm for Intelligent Control

NASA Technical Reports Server (NTRS)

Hexmoor, Henry

1999-01-01

We present metrics for quantifying organizational structures of complex control systems intended for controlling long-lived robotic or other autonomous applications commonly found in space applications. Such advanced control systems are often called integration platforms or agent architectures. Reported metrics span concerns about time, resources, software engineering, and complexities in the world.

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.

Learning Companion Systems, Social Learning Systems, and the Global Social Learning Club.

ERIC Educational Resources Information Center

Chan, Tak-Wai

1996-01-01

Describes the development of learning companion systems and their contributions to the class of social learning systems that integrate artificial intelligence agents and use machine learning to tutor and interact with students. Outlines initial social learning projects, their programming languages, and weakness. Future improvements will include…

CNN Newsroom Classroom Guides, February 2001.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of February 2001, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: Libyan intelligence agent is convicted of the Lockerbie bombing, and…

An Intelligent Agent for the K-12 Educational Community

NASA Technical Reports Server (NTRS)

Rorvig, Mark E.; Hutchison, Mark W.; Shelton, Robert O.; Smith, Stephanie L.; Yazbeck, Marwan E.

1995-01-01

Nearly every professional would like to have a personal assistant to perform the physical and mental work of searching libraries for needed information. This paper describes a tool which performs this function using commonly available Internet services. The promises and difficulties of developing such a tool are described.

Intelligent E-Learning Systems: Automatic Construction of Ontologies

NASA Astrophysics Data System (ADS)

Peso, Jesús del; de Arriaga, Fernando

2008-05-01

During the last years a new generation of Intelligent E-Learning Systems (ILS) has emerged with enhanced functionality due, mainly, to influences from Distributed Artificial Intelligence, to the use of cognitive modelling, to the extensive use of the Internet, and to new educational ideas such as the student-centered education and Knowledge Management. The automatic construction of ontologies provides means of automatically updating the knowledge bases of their respective ILS, and of increasing their interoperability and communication among them, sharing the same ontology. The paper presents a new approach, able to produce ontologies from a small number of documents such as those obtained from the Internet, without the assistance of large corpora, by using simple syntactic rules and some semantic information. The method is independent of the natural language used. The use of a multi-agent system increases the flexibility and capability of the method. Although the method can be easily improved, the results so far obtained, are promising.

Applications of artificial intelligence 1993: Knowledge-based systems in aerospace and industry; Proceedings of the Meeting, Orlando, FL, Apr. 13-15, 1993

NASA Technical Reports Server (NTRS)

Fayyad, Usama M. (Editor); Uthurusamy, Ramasamy (Editor)

1993-01-01

The present volume on applications of artificial intelligence with regard to knowledge-based systems in aerospace and industry discusses machine learning and clustering, expert systems and optimization techniques, monitoring and diagnosis, and automated design and expert systems. Attention is given to the integration of AI reasoning systems and hardware description languages, care-based reasoning, knowledge, retrieval, and training systems, and scheduling and planning. Topics addressed include the preprocessing of remotely sensed data for efficient analysis and classification, autonomous agents as air combat simulation adversaries, intelligent data presentation for real-time spacecraft monitoring, and an integrated reasoner for diagnosis in satellite control. Also discussed are a knowledge-based system for the design of heat exchangers, reuse of design information for model-based diagnosis, automatic compilation of expert systems, and a case-based approach to handling aircraft malfunctions.

Automatic negotiation: playing the domain instead of the opponent

NASA Astrophysics Data System (ADS)

Erez, Eden S.; Zuckerman, Inon; Hermel, Dror

2017-05-01

An automated negotiator is an intelligent agent whose task is to reach the best possible agreement. We explore a novel approach to developing a negotiation strategy, a 'domain-based approach'. Specifically, we use two domain parameters, reservation value and discount factor, to cluster the domain into different regions, in each of which we employ a heuristic strategy based on the notions of temporal flexibility and bargaining strength. Following the presentation of our cognitive and formal models, we show in an extensive experimental study that an agent based on that approach wins against the top agents of the automated negotiation competition of 2012 and 2013, and attained the second place in 2014.

Acquisition of Autonomous Behaviors by Robotic Assistants

NASA Technical Reports Server (NTRS)

Peters, R. A., II; Sarkar, N.; Bodenheimer, R. E.; Brown, E.; Campbell, C.; Hambuchen, K.; Johnson, C.; Koku, A. B.; Nilas, P.; Peng, J.

2005-01-01

Our research achievements under the NASA-JSC grant contributed significantly in the following areas. Multi-agent based robot control architecture called the Intelligent Machine Architecture (IMA) : The Vanderbilt team received a Space Act Award for this research from NASA JSC in October 2004. Cognitive Control and the Self Agent : Cognitive control in human is the ability to consciously manipulate thoughts and behaviors using attention to deal with conflicting goals and demands. We have been updating the IMA Self Agent towards this goal. If opportunity arises, we would like to work with NASA to empower Robonaut to do cognitive control. Applications 1. SES for Robonaut, 2. Robonaut Fault Diagnostic System, 3. ISAC Behavior Generation and Learning, 4. Segway Research.

Source Update Capture in Information Agents

NASA Technical Reports Server (NTRS)

Ashish, Naveen; Kulkarni, Deepak; Wang, Yao

2003-01-01

In this paper we present strategies for successfully capturing updates at Web sources. Web-based information agents provide integrated access to autonomous Web sources that can get updated. For many information agent applications we are interested in knowing when a Web source to which the application provides access, has been updated. We may also be interested in capturing all the updates at a Web source over a period of time i.e., detecting the updates and, for each update retrieving and storing the new version of data. Previous work on update and change detection by polling does not adequately address this problem. We present strategies for intelligently polling a Web source for efficiently capturing changes at the source.

Beyond Artificial Intelligence toward Engineered Psychology

NASA Astrophysics Data System (ADS)

Bozinovski, Stevo; Bozinovska, Liljana

This paper addresses the field of Artificial Intelligence, road it went so far and possible road it should go. The paper was invited by the Conference of IT Revolutions 2008, and discusses some issues not emphasized in AI trajectory so far. The recommendations are that the main focus should be personalities rather than programs or agents, that genetic environment should be introduced in reasoning about personalities, and that limbic system should be studied and modeled. Engineered Psychology is proposed as a road to go. Need for basic principles in psychology are discussed and a mathematical equation is proposed as fundamental law of engineered and human psychology.

Entanglement in Self-Supervised Dynamics

NASA Technical Reports Server (NTRS)

Zak, Michail

2011-01-01

A new type of correlation has been developed similar to quantum entanglement in self-supervised dynamics (SSD). SSDs have been introduced as a quantum-classical hybrid based upon the Madelung equation in which the quantum potential is replaced by an information potential. As a result, SSD preserves the quantum topology along with superposition, entanglement, and wave-particle duality. At the same time, it can be implemented in any scale including the Newtonian scale. The main properties of SSD associated with simulating intelligence have been formulated. The attention with this innovation is focused on intelligent agents interaction based upon the new fundamental non-New tonian effect; namely, entanglement.

Open Source Service Agent (OSSA) in the intelligence community's Open Source Architecture

NASA Technical Reports Server (NTRS)

Fiene, Bruce F.

1994-01-01

The Community Open Source Program Office (COSPO) has developed an architecture for the intelligence community's new Open Source Information System (OSIS). The architecture is a multi-phased program featuring connectivity, interoperability, and functionality. OSIS is based on a distributed architecture concept. The system is designed to function as a virtual entity. OSIS will be a restricted (non-public), user configured network employing Internet communications. Privacy and authentication will be provided through firewall protection. Connection to OSIS can be made through any server on the Internet or through dial-up modems provided the appropriate firewall authentication system is installed on the client.

Situation resolution with context-sensitive fuzzy relations

NASA Astrophysics Data System (ADS)

Jakobson, Gabriel; Buford, John; Lewis, Lundy

2009-05-01

Context plays a significant role in situation resolution by intelligent agents (human or machine) by affecting how the situations are recognized, interpreted, acted upon or predicted. Many definitions and formalisms for the notion of context have emerged in various research fields including psychology, economics and computer science (computational linguistics, data management, control theory, artificial intelligence and others). In this paper we examine the role of context in situation management, particularly how to resolve situations that are described by using fuzzy (inexact) relations among their components. We propose a language for describing context sensitive inexact constraints and an algorithm for interpreting relations using inexact (fuzzy) computations.

Collective motion of predictive swarms

PubMed Central

Vural, Dervis Can

2017-01-01

Theoretical models of populations and swarms typically start with the assumption that the motion of agents is governed by the local stimuli. However, an intelligent agent, with some understanding of the laws that govern its habitat, can anticipate the future, and make predictions to gather resources more efficiently. Here we study a specific model of this kind, where agents aim to maximize their consumption of a diffusing resource, by attempting to predict the future of a resource field and the actions of other agents. Once the agents make a prediction, they are attracted to move towards regions that have, and will have, denser resources. We find that the further the agents attempt to see into the future, the more their attempts at prediction fail, and the less resources they consume. We also study the case where predictive agents compete against non-predictive agents and find the predictors perform better than the non-predictors only when their relative numbers are very small. We conclude that predictivity pays off either when the predictors do not see too far into the future or the number of predictors is small. PMID:29065136

Collective motion of predictive swarms.

PubMed

Rupprecht, Nathaniel; Vural, Dervis Can

2017-01-01

Theoretical models of populations and swarms typically start with the assumption that the motion of agents is governed by the local stimuli. However, an intelligent agent, with some understanding of the laws that govern its habitat, can anticipate the future, and make predictions to gather resources more efficiently. Here we study a specific model of this kind, where agents aim to maximize their consumption of a diffusing resource, by attempting to predict the future of a resource field and the actions of other agents. Once the agents make a prediction, they are attracted to move towards regions that have, and will have, denser resources. We find that the further the agents attempt to see into the future, the more their attempts at prediction fail, and the less resources they consume. We also study the case where predictive agents compete against non-predictive agents and find the predictors perform better than the non-predictors only when their relative numbers are very small. We conclude that predictivity pays off either when the predictors do not see too far into the future or the number of predictors is small.

Department of the Navy Supporting Data for Fiscal Year 1983 Budget Estimates Descriptive Summaries Submitted to Congress February 1982. Research, Development, Test and Evaluation, Navy. Book 3 of 3. Tactical Programs, Intelligence & Communications, Management & Support

DTIC Science & Technology

1982-02-01

For these data elements, Initial Milestone 11 values were established as the Flanning Estimate (PE) with the Development Estimate ( DE ) to he based ...development of improved forensic collection techniques for Naval Investigative Agents on ships and overseas bases . As this is a continuing program, the above...overseas bases ), and continue development of improved forensic collection techniques for Naval Investigative Agents on ships and overseas baszs. 4. (U) FY

Human Activity Behavior and Gesture Generation in Virtual Worlds for Long- Duration Space Missions. Chapter 8

NASA Technical Reports Server (NTRS)

Sierhuis, Maarten; Clancey, William J.; Damer, Bruce; Brodsky, Boris; vanHoff, Ron

2007-01-01

A virtual worlds presentation technique with embodied, intelligent agents is being developed as an instructional medium suitable to present in situ training on long term space flight. The system combines a behavioral element based on finite state automata, a behavior based reactive architecture also described as subsumption architecture, and a belief-desire-intention agent structure. These three features are being integrated to describe a Brahms virtual environment model of extravehicular crew activity which could become a basis for procedure training during extended space flight.

Instructable autonomous agents. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Huffman, Scott Bradley

1994-01-01

In contrast to current intelligent systems, which must be laboriously programmed for each task they are meant to perform, instructable agents can be taught new tasks and associated knowledge. This thesis presents a general theory of learning from tutorial instruction and its use to produce an instructable agent. Tutorial instruction is a particularly powerful form of instruction, because it allows the instructor to communicate whatever kind of knowledge a student needs at whatever point it is needed. To exploit this broad flexibility, however, a tutorable agent must support a full range of interaction with its instructor to learn a full range of knowledge. Thus, unlike most machine learning tasks, which target deep learning of a single kind of knowledge from a single kind of input, tutorability requires a breadth of learning from a broad range of instructional interactions. The theory of learning from tutorial instruction presented here has two parts. First, a computational model of an intelligent agent, the problem space computational model, indicates the types of knowledge that determine an agent's performance, and thus, that should be acquirable via instruction. Second, a learning technique, called situated explanation specifies how the agent learns general knowledge from instruction. The theory is embodied by an implemented agent, Instructo-Soar, built within the Soar architecture. Instructo-Soar is able to learn hierarchies of completely new tasks, to extend task knowledge to apply in new situations, and in fact to acquire every type of knowledge it uses during task performance - control knowledge, knowledge of operators' effects, state inferences, etc. - from interactive natural language instructions. This variety of learning occurs by applying the situated explanation technique to a variety of instructional interactions involving a variety of types of instructions (commands, statements, conditionals, etc.). By taking seriously the requirements of flexible tutorial instruction, Instructo-Soar demonstrates a breadth of interaction and learning capabilities that goes beyond previous instructable systems, such as learning apprentice systems. Instructo-Soar's techniques could form the basis for future 'instructable technologies' that come equipped with basic capabilities, and can be taught by novice users to perform any number of desired tasks.

A distributed agent architecture for real-time knowledge-based systems: Real-time expert systems project, phase 1

NASA Technical Reports Server (NTRS)

Lee, S. Daniel

1990-01-01

We propose a distributed agent architecture (DAA) that can support a variety of paradigms based on both traditional real-time computing and artificial intelligence. DAA consists of distributed agents that are classified into two categories: reactive and cognitive. Reactive agents can be implemented directly in Ada to meet hard real-time requirements and be deployed on on-board embedded processors. A traditional real-time computing methodology under consideration is the rate monotonic theory that can guarantee schedulability based on analytical methods. AI techniques under consideration for reactive agents are approximate or anytime reasoning that can be implemented using Bayesian belief networks as in Guardian. Cognitive agents are traditional expert systems that can be implemented in ART-Ada to meet soft real-time requirements. During the initial design of cognitive agents, it is critical to consider the migration path that would allow initial deployment on ground-based workstations with eventual deployment on on-board processors. ART-Ada technology enables this migration while Lisp-based technologies make it difficult if not impossible. In addition to reactive and cognitive agents, a meta-level agent would be needed to coordinate multiple agents and to provide meta-level control.

Homeostatic Agent for General Environment

NASA Astrophysics Data System (ADS)

Yoshida, Naoto

2018-03-01

One of the essential aspect in biological agents is dynamic stability. This aspect, called homeostasis, is widely discussed in ethology, neuroscience and during the early stages of artificial intelligence. Ashby's homeostats are general-purpose learning machines for stabilizing essential variables of the agent in the face of general environments. However, despite their generality, the original homeostats couldn't be scaled because they searched their parameters randomly. In this paper, first we re-define the objective of homeostats as the maximization of a multi-step survival probability from the view point of sequential decision theory and probabilistic theory. Then we show that this optimization problem can be treated by using reinforcement learning algorithms with special agent architectures and theoretically-derived intrinsic reward functions. Finally we empirically demonstrate that agents with our architecture automatically learn to survive in a given environment, including environments with visual stimuli. Our survival agents can learn to eat food, avoid poison and stabilize essential variables through theoretically-derived single intrinsic reward formulations.

Situation Awareness of Onboard System Autonomy

NASA Technical Reports Server (NTRS)

Schreckenghost, Debra; Thronesbery, Carroll; Hudson, Mary Beth

2005-01-01

We have developed intelligent agent software for onboard system autonomy. Our approach is to provide control agents that automate crew and vehicle systems, and operations assistants that aid humans in working with these autonomous systems. We use the 3 Tier control architecture to develop the control agent software that automates system reconfiguration and routine fault management. We use the Distributed Collaboration and Interaction (DCI) System to develop the operations assistants that provide human services, including situation summarization, event notification, activity management, and support for manual commanding of autonomous system. In this paper we describe how the operations assistants aid situation awareness of the autonomous control agents. We also describe our evaluation of the DCI System to support control engineers during a ground test at Johnson Space Center (JSC) of the Post Processing System (PPS) for regenerative water recovery.

Learning Sequences of Actions in Collectives of Autonomous Agents

NASA Technical Reports Server (NTRS)

Turner, Kagan; Agogino, Adrian K.; Wolpert, David H.; Clancy, Daniel (Technical Monitor)

2001-01-01

In this paper we focus on the problem of designing a collective of autonomous agents that individually learn sequences of actions such that the resultant sequence of joint actions achieves a predetermined global objective. We are particularly interested in instances of this problem where centralized control is either impossible or impractical. For single agent systems in similar domains, machine learning methods (e.g., reinforcement learners) have been successfully used. However, applying such solutions directly to multi-agent systems often proves problematic, as agents may work at cross-purposes, or have difficulty in evaluating their contribution to achievement of the global objective, or both. Accordingly, the crucial design step in multiagent systems centers on determining the private objectives of each agent so that as the agents strive for those objectives, the system reaches a good global solution. In this work we consider a version of this problem involving multiple autonomous agents in a grid world. We use concepts from collective intelligence to design goals for the agents that are 'aligned' with the global goal, and are 'learnable' in that agents can readily see how their behavior affects their utility. We show that reinforcement learning agents using those goals outperform both 'natural' extensions of single agent algorithms and global reinforcement, learning solutions based on 'team games'.

Intelligent Design of Nano-Scale Molecular Imaging Agents

PubMed Central

Kim, Sung Bae; Hattori, Mitsuru; Ozawa, Takeaki

2012-01-01

Visual representation and quantification of biological processes at the cellular and subcellular levels within living subjects are gaining great interest in life science to address frontier issues in pathology and physiology. As intact living subjects do not emit any optical signature, visual representation usually exploits nano-scale imaging agents as the source of image contrast. Many imaging agents have been developed for this purpose, some of which exert nonspecific, passive, and physical interaction with a target. Current research interest in molecular imaging has mainly shifted to fabrication of smartly integrated, specific, and versatile agents that emit fluorescence or luminescence as an optical readout. These agents include luminescent quantum dots (QDs), biofunctional antibodies, and multifunctional nanoparticles. Furthermore, genetically encoded nano-imaging agents embedding fluorescent proteins or luciferases are now gaining popularity. These agents are generated by integrative design of the components, such as luciferase, flexible linker, and receptor to exert a specific on–off switching in the complex context of living subjects. In the present review, we provide an overview of the basic concepts, smart design, and practical contribution of recent nano-scale imaging agents, especially with respect to genetically encoded imaging agents. PMID:23235326

Intelligent design of nano-scale molecular imaging agents.

PubMed

Kim, Sung Bae; Hattori, Mitsuru; Ozawa, Takeaki

2012-12-12

Visual representation and quantification of biological processes at the cellular and subcellular levels within living subjects are gaining great interest in life science to address frontier issues in pathology and physiology. As intact living subjects do not emit any optical signature, visual representation usually exploits nano-scale imaging agents as the source of image contrast. Many imaging agents have been developed for this purpose, some of which exert nonspecific, passive, and physical interaction with a target. Current research interest in molecular imaging has mainly shifted to fabrication of smartly integrated, specific, and versatile agents that emit fluorescence or luminescence as an optical readout. These agents include luminescent quantum dots (QDs), biofunctional antibodies, and multifunctional nanoparticles. Furthermore, genetically encoded nano-imaging agents embedding fluorescent proteins or luciferases are now gaining popularity. These agents are generated by integrative design of the components, such as luciferase, flexible linker, and receptor to exert a specific on-off switching in the complex context of living subjects. In the present review, we provide an overview of the basic concepts, smart design, and practical contribution of recent nano-scale imaging agents, especially with respect to genetically encoded imaging agents.

76 FR 20452 - Unblocking of Specially Designated Nationals and Blocked Persons Pursuant to the Foreign...

Federal Register 2010, 2011, 2012, 2013, 2014

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.... FOR FURTHER INFORMATION CONTACT: Assistant Director, Compliance Outreach & Implementation, U.S... their businesses and agents access to the U.S. financial system and to the benefits of trade and... Attorney General, the Director of the Central Intelligence Agency, the Director of the Federal Bureau of...

75 FR 65558 - Unblocking of Specially Designated Nationals and Blocked Persons Pursuant to the Foreign...

Federal Register 2010, 2011, 2012, 2013, 2014

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..., 2010. FOR FURTHER INFORMATION CONTACT: Assistant Director, Compliance Outreach & Implementation, U.S... organizations on a worldwide basis, with the objective of denying their businesses and agents access to the U.S... Secretary of the Treasury consults with the Attorney General, the Director of the Central Intelligence...

Online Information 96. Proceedings of the International Online Information Meeting (20th, London, England, UK, December 3-5, 1996).

ERIC Educational Resources Information Center

Raitt, David I., Ed.; Jeapes, Ben, Ed.

This proceedings volume contains 68 papers. Subjects addressed include: access to information; the future of information managers/librarians; intelligent agents; changing roles of library users; disintermediation; Internet review sites; World Wide Web (WWW) search engines; Java; online searching; future of online education; integrated information…

Communication Tasks Using Intelligent Agents in Second Life

ERIC Educational Resources Information Center

Ishizuka, Hiroki; Kiyoshi, Akama

2014-01-01

Numerous attempts have been made to use Second Life (SL) as a platform for language teaching. As a result, the possibility of SL as a means to promote conversational interactions has been reported. However, research has thus far largely focused on simply using SL without further augmentations for communication between learners or between teachers…

Learning to Overcome Cultural Conflict through Engaging with Intelligent Agents in Synthetic Cultures

ERIC Educational Resources Information Center

Hall, Lynne; Tazzyman, Sarah; Hume, Colette; Endrass, Birgit; Lim, Mei-Yii; Hofstede, GertJan; Paiva, Ana; Andre, Elisabeth; Kappas, Arvid; Aylett, Ruth

2015-01-01

Providing opportunities for children to engage with intercultural learning has frequently focused on exposure to the ritual, celebrations and festivals of cultures, with the view that such experiences will result in greater acceptance of cultural differences. Intercultural conflict is often avoided, bringing as it does particular pedagogical,…

A Qualitative Synthesis of the Flynn Effect

ERIC Educational Resources Information Center

Ceci, Stephen J.; Williams, Wendy M.

2016-01-01

Clark et al. focus on the likely drivers of the Flynn effect (sociocultural, educational, technological), and imply that it is not a single causal agent driving the upward climb in IQ scores but perhaps multiple causes with different onsets. Given, the authors' conception of intelligence in terms of underlying attentional and cognitive resources…

eTeacher: Providing Personalized Assistance to E-Learning Students

ERIC Educational Resources Information Center

Schiaffino, Silvia; Garcia, Patricio; Amandi, Analia

2008-01-01

In this paper we present eTeacher, an intelligent agent that provides personalized assistance to e-learning students. eTeacher observes a student's behavior while he/she is taking online courses and automatically builds the student's profile. This profile comprises the student's learning style and information about the student's performance, such…

Knowledge Value Added (KVA) Methodology as a Tool for Measuring the Utilization of Knowledge Assets Aboard Marine Corps Installations

DTIC Science & Technology

2008-06-01

make better technology investment decisions. C. FOLLOW-ON RESEARCH POTENTIAL Like most assets, knowledge is only valuable if it can be transmuted ...CID Agent Sexual Assault Investigations Training E5 5 Conduct preliminary investigation on referable cases 5811 Basic Military Police Intelligence In

Intelligent Agents for Dynamic Optimization of Learner Performances in an Online System

ERIC Educational Resources Information Center

Kamsa, Imane; Elouahbi, Rachid; El Khoukhi, Fatima

2017-01-01

Aim/Purpose: To identify and rectify the learning difficulties of online learners. Background: The major cause of learners' failure and non-acquisition of knowledge relates to their weaknesses in certain areas necessary for optimal learning. We focus on e-learning because, within this environment, the learner is mostly affected by these…

Soviet Espionage Effort Have Targeted U.S. Research Libraries and Staffs since 1962, FBI Charges in Report.

ERIC Educational Resources Information Center

Turner, Judith Axler

1988-01-01

Soviet intelligence agents have been collecting scientific and technical documents in research libraries to identify emerging technology before its components become classified or restricted. Librarians are also recruited as spies. However, asking librarians to identify suspicious library users would violate ethics and intellectual freedom. (MSE)

Protecting the Rights of Whistleblowers

ERIC Educational Resources Information Center

Robinson, Lauren

2005-01-01

Coleen Rowley became one of the most famous whistleblowers in the United States in recent times when she blew the whistle on intelligence blunders at the FBI. The special agent's fiery 13-page letter to FBI Director Robert Mueller in 2002 detailed the FBI's failure to investigate Zacarias Moussaoui, a French national of Moroccan descent known as…

A Hybrid Approach for Supporting Adaptivity in E-Learning Environments

ERIC Educational Resources Information Center

Al-Omari, Mohammad; Carter, Jenny; Chiclana, Francisco

2016-01-01

Purpose: The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity…

Student Query Trend Assessment with Semantical Annotation and Artificial Intelligent Multi-Agents

ERIC Educational Resources Information Center

Malik, Kaleem Razzaq; Mir, Rizwan Riaz; Farhan, Muhammad; Rafiq, Tariq; Aslam, Muhammad

2017-01-01

Research in era of data representation to contribute and improve key data policy involving the assessment of learning, training and English language competency. Students are required to communicate in English with high level impact using language and influence. The electronic technology works to assess students' questions positively enabling…

Natural Speech Toward Humans and Intelligent Agents During a Simulated Search and Rescue Mission

DTIC Science & Technology

2008-12-01

Eklundh, 2006). Research has been done on giving directions to robots, and the point of view that teammates normally attribute to them (Imai, Hiraki ...Bystander intervention as a resource in human-robot collaboration. Interaction Studies, 7(3), 455-477. Imai, M., Hiraki , K., Miyasato, T., Nakatsu, R

Manipulation Action Understanding for Observation and Execution

ERIC Educational Resources Information Center

Yang, Yezhou

2015-01-01

Modern intelligent agents will need to learn the actions that humans perform. They will need to recognize these actions when they see them and they will need to perform these actions themselves. We want to propose a cognitive system that interprets human manipulation actions from perceptual information (image and depth data) and consists of…

The Machines Are Coming: Future Directions in Instructional Communication Research. Forum: The Future of Instructional Communication

ERIC Educational Resources Information Center

Edwards, Autumn; Edwards, Chad

2017-01-01

Educational encounters of the future (and increasingly, of the present) will involve a complex collaboration of human and machine intelligences and agents, partnering to enhance learning and growth. Increasingly, "students and instructors are not only talking 'through' machines, but also [talking] 'to them', and 'within them'" (Edwards…

A learning-based agent for home neurorehabilitation.

PubMed

Lydakis, Andreas; Meng, Yuanliang; Munroe, Christopher; Wu, Yi-Ning; Begum, Momotaz

2017-07-01

This paper presents the iterative development of an artificially intelligent system to promote home-based neurorehabilitation. Although proper, structured practice of rehabilitation exercises at home is the key to successful recovery of motor functions, there is no home-program out there which can monitor a patient's exercise-related activities and provide corrective feedback in real time. To this end, we designed a Learning from Demonstration (LfD) based home-rehabilitation framework that combines advanced robot learning algorithms with commercially available wearable technologies. The proposed system uses exercise-related motion information and electromyography signals (EMG) of a patient to train a Markov Decision Process (MDP). The trained MDP model can enable an agent to serve as a coach for a patient. On a system level, this is the first initiative, to the best of our knowledge, to employ LfD in an health-care application to enable lay users to program an intelligent system. From a rehabilitation research perspective, this is a completely novel initiative to employ machine learning to provide interactive corrective feedback to a patient in home settings.

An intelligent virtual human system for providing healthcare information and support.

PubMed

Rizzo, Albert A; Lange, Belinda; Buckwalter, John G; Forbell, Eric; Kim, Julia; Sagae, Kenji; Williams, Josh; Rothbaum, Barbara O; Difede, JoAnn; Reger, Greg; Parsons, Thomas; Kenny, Patrick

2011-01-01

Over the last 15 years, a virtual revolution has taken place in the use of Virtual Reality simulation technology for clinical purposes. Shifts in the social and scientific landscape have now set the stage for the next major movement in Clinical Virtual Reality with the "birth" of intelligent virtual humans. Seminal research and development has appeared in the creation of highly interactive, artificially intelligent and natural language capable virtual human agents that can engage real human users in a credible fashion. No longer at the level of a prop to add context or minimal faux interaction in a virtual world, virtual humans can be designed to perceive and act in a 3D virtual world, engage in spoken dialogues with real users and can be capable of exhibiting human-like emotional reactions. This paper will present an overview of the SimCoach project that aims to develop virtual human support agents to serve as online guides for promoting access to psychological healthcare information and for assisting military personnel and family members in breaking down barriers to initiating care. The SimCoach experience is being designed to attract and engage military Service Members, Veterans and their significant others who might not otherwise seek help with a live healthcare provider. It is expected that this experience will motivate users to take the first step--to empower themselves to seek advice and information regarding their healthcare and general personal welfare and encourage them to take the next step towards seeking more formal resources if needed.

A Reasoning Agent for Credit Card Fraud on the Internet Using the Event Calculus

NASA Astrophysics Data System (ADS)

Blackwell, Clive

We illustrate the design of an intelligent agent to aid a merchant to limit fraudulent payment card purchases over the Internet. This is important because increasing fraud may limit the rise of e-commerce, and difficult because of the uncertainty in identifying and authenticating people remotely. The agent can advise the merchant what actions to take to reduce risk without complete knowledge of the circumstances. It can also negotiate flexibly to conclude transactions successfully that would otherwise be rejected. We use the Event Calculus to model the transaction system including the participants and their actions. The idea has applications in other distributed systems where incomplete knowledge of a system may be exploited by adversaries to their advantage.

Learning Agents for Autonomous Space Asset Management (LAASAM)

NASA Astrophysics Data System (ADS)

Scally, L.; Bonato, M.; Crowder, J.

2011-09-01

Current and future space systems will continue to grow in complexity and capabilities, creating a formidable challenge to monitor, maintain, and utilize these systems and manage their growing network of space and related ground-based assets. Integrated System Health Management (ISHM), and in particular, Condition-Based System Health Management (CBHM), is the ability to manage and maintain a system using dynamic real-time data to prioritize, optimize, maintain, and allocate resources. CBHM entails the maintenance of systems and equipment based on an assessment of current and projected conditions (situational and health related conditions). A complete, modern CBHM system comprises a number of functional capabilities: sensing and data acquisition; signal processing; conditioning and health assessment; diagnostics and prognostics; and decision reasoning. In addition, an intelligent Human System Interface (HSI) is required to provide the user/analyst with relevant context-sensitive information, the system condition, and its effect on overall situational awareness of space (and related) assets. Colorado Engineering, Inc. (CEI) and Raytheon are investigating and designing an Intelligent Information Agent Architecture that will provide a complete range of CBHM and HSI functionality from data collection through recommendations for specific actions. The research leverages CEI’s expertise with provisioning management network architectures and Raytheon’s extensive experience with learning agents to define a system to autonomously manage a complex network of current and future space-based assets to optimize their utilization.

Criticality triggers the emergence of collective intelligence in groups.

PubMed

De Vincenzo, Ilario; Giannoccaro, Ilaria; Carbone, Giuseppe; Grigolini, Paolo

2017-08-01

A spinlike model mimicking human behavior in groups is employed to investigate the dynamics of the decision-making process. Within the model, the temporal evolution of the state of systems is governed by a time-continuous Markov chain. The transition rates of the resulting master equation are defined in terms of the change of interaction energy between the neighboring agents (change of the level of conflict) and the change of a locally defined agent fitness. Three control parameters can be identified: (i) the social interaction strength βJ measured in units of social temperature, (ii) the level of confidence β^{'} that each individual has on his own expertise, and (iii) the level of knowledge p that identifies the expertise of each member. Based on these three parameters, the phase diagrams of the system show that a critical transition front exists where a sharp and concurrent change in fitness and consensus takes place. We show that at the critical front, the information leakage from the fitness landscape to the agents is maximized. This event triggers the emergence of the collective intelligence of the group, and in the end it leads to a dramatic improvement in the decision-making performance of the group. The effect of size M of the system is also investigated, showing that, depending on the value of the control parameters, increasing M may be either beneficial or detrimental.

Criticality triggers the emergence of collective intelligence in groups

NASA Astrophysics Data System (ADS)

De Vincenzo, Ilario; Giannoccaro, Ilaria; Carbone, Giuseppe; Grigolini, Paolo

2017-08-01

A spinlike model mimicking human behavior in groups is employed to investigate the dynamics of the decision-making process. Within the model, the temporal evolution of the state of systems is governed by a time-continuous Markov chain. The transition rates of the resulting master equation are defined in terms of the change of interaction energy between the neighboring agents (change of the level of conflict) and the change of a locally defined agent fitness. Three control parameters can be identified: (i) the social interaction strength β J measured in units of social temperature, (ii) the level of confidence β' that each individual has on his own expertise, and (iii) the level of knowledge p that identifies the expertise of each member. Based on these three parameters, the phase diagrams of the system show that a critical transition front exists where a sharp and concurrent change in fitness and consensus takes place. We show that at the critical front, the information leakage from the fitness landscape to the agents is maximized. This event triggers the emergence of the collective intelligence of the group, and in the end it leads to a dramatic improvement in the decision-making performance of the group. The effect of size M of the system is also investigated, showing that, depending on the value of the control parameters, increasing M may be either beneficial or detrimental.

Cognitive architectures and autonomy: Commentary and Response

NASA Astrophysics Data System (ADS)

2012-11-01

Editors: Włodzisław Duch / Ah-Hwee Tan / Stan Franklin Autonomy for AGI Cristiano Castelfranchi 31 Are Disembodied Agents Really Autonomous? Antonio Chella 33 The Perception-…-Action Cycle Cognitive Architecture and Autonomy: the View from the Brain Vassilis Cutsuridis 36 Autonomy Requires Creativity and Meta-Learning Włodzisław Duch 39 Meta Learning, Change of Internal Workings, and LIDA Ryan McCall / Stan Franklin 42 An Appeal for Declaring Research Goals Brandon Rohrer 45 The Development of Cognition as the Basis for Autonomy Frank van der Velde 47 Autonomy and Intelligence Pei Wang 49 Autonomy, Isolation, and Collective Intelligence Nikolaos Mavridis 51 Response to Comments Kristinn R. Thórisson / Helgi Páll Helgasson 56

Genetic mechanism for designing new generation of buildings from data obtained by sensor agent robots

NASA Astrophysics Data System (ADS)

Ono, Chihiro; Mita, Akira

2012-04-01

Due to an increase in an elderly-people household, and global warming, the design of building spaces requires delicate consideration of the needs of elderly-people. Studies of intelligent spaces that can control suitable devices for residents may provide some of functions needed. However, these intelligent spaces are based on predefined scenarios so that it is difficult to handle unexpected circumstances and adapt to the needs of people. This study aims to suggest a Genetic adaption algorithm for building spaces. The feasibility of the algorithm is tested by simulation. The algorithm extend the existing design methodology by reflecting ongoing living information quickly in the variety of patterns.

Incorporating time and spatial-temporal reasoning into situation management

NASA Astrophysics Data System (ADS)

Jakobson, Gabriel

2010-04-01

Spatio-temporal reasoning plays a significant role in situation management that is performed by intelligent agents (human or machine) by affecting how the situations are recognized, interpreted, acted upon or predicted. Many definitions and formalisms for the notion of spatio-temporal reasoning have emerged in various research fields including psychology, economics and computer science (computational linguistics, data management, control theory, artificial intelligence and others). In this paper we examine the role of spatio-temporal reasoning in situation management, particularly how to resolve situations that are described by using spatio-temporal relations among events and situations. We discuss a model for describing context sensitive temporal relations and show have the model can be extended for spatial relations.

An Intelligent Automation Platform for Rapid Bioprocess Design.

PubMed

Wu, Tianyi; Zhou, Yuhong

2014-08-01

Bioprocess development is very labor intensive, requiring many experiments to characterize each unit operation in the process sequence to achieve product safety and process efficiency. Recent advances in microscale biochemical engineering have led to automated experimentation. A process design workflow is implemented sequentially in which (1) a liquid-handling system performs high-throughput wet lab experiments, (2) standalone analysis devices detect the data, and (3) specific software is used for data analysis and experiment design given the user's inputs. We report an intelligent automation platform that integrates these three activities to enhance the efficiency of such a workflow. A multiagent intelligent architecture has been developed incorporating agent communication to perform the tasks automatically. The key contribution of this work is the automation of data analysis and experiment design and also the ability to generate scripts to run the experiments automatically, allowing the elimination of human involvement. A first-generation prototype has been established and demonstrated through lysozyme precipitation process design. All procedures in the case study have been fully automated through an intelligent automation platform. The realization of automated data analysis and experiment design, and automated script programming for experimental procedures has the potential to increase lab productivity. © 2013 Society for Laboratory Automation and Screening.

An Intelligent Automation Platform for Rapid Bioprocess Design

PubMed Central

Wu, Tianyi

2014-01-01

Bioprocess development is very labor intensive, requiring many experiments to characterize each unit operation in the process sequence to achieve product safety and process efficiency. Recent advances in microscale biochemical engineering have led to automated experimentation. A process design workflow is implemented sequentially in which (1) a liquid-handling system performs high-throughput wet lab experiments, (2) standalone analysis devices detect the data, and (3) specific software is used for data analysis and experiment design given the user’s inputs. We report an intelligent automation platform that integrates these three activities to enhance the efficiency of such a workflow. A multiagent intelligent architecture has been developed incorporating agent communication to perform the tasks automatically. The key contribution of this work is the automation of data analysis and experiment design and also the ability to generate scripts to run the experiments automatically, allowing the elimination of human involvement. A first-generation prototype has been established and demonstrated through lysozyme precipitation process design. All procedures in the case study have been fully automated through an intelligent automation platform. The realization of automated data analysis and experiment design, and automated script programming for experimental procedures has the potential to increase lab productivity. PMID:24088579

Emerging CAE technologies and their role in Future Ambient Intelligence Environments

NASA Astrophysics Data System (ADS)

Noor, Ahmed K.

2011-03-01

Dramatic improvements are on the horizon in Computer Aided Engineering (CAE) and various simulation technologies. The improvements are due, in part, to the developments in a number of leading-edge technologies and their synergistic combinations/convergence. The technologies include ubiquitous, cloud, and petascale computing; ultra high-bandwidth networks, pervasive wireless communication; knowledge based engineering; networked immersive virtual environments and virtual worlds; novel human-computer interfaces; and powerful game engines and facilities. This paper describes the frontiers and emerging simulation technologies, and their role in the future virtual product creation and learning/training environments. The environments will be ambient intelligence environments, incorporating a synergistic combination of novel agent-supported visual simulations (with cognitive learning and understanding abilities); immersive 3D virtual world facilities; development chain management systems and facilities (incorporating a synergistic combination of intelligent engineering and management tools); nontraditional methods; intelligent, multimodal and human-like interfaces; and mobile wireless devices. The Virtual product creation environment will significantly enhance the productivity and will stimulate creativity and innovation in future global virtual collaborative enterprises. The facilities in the learning/training environment will provide timely, engaging, personalized/collaborative and tailored visual learning.

Current topics in active and intelligent food packaging for preservation of fresh foods.

PubMed

Lee, Seung Yuan; Lee, Seung Jae; Choi, Dong Soo; Hur, Sun Jin

2015-11-01

The purpose of this review is to provide an overview of current packaging systems, e.g. active packaging and intelligent packaging, for various foods. Active packaging, such as modified atmosphere packaging (MAP), extends the shelf life of fresh produce, provides a high-quality product, reduces economic losses, including those caused by delay of ripening, and improves appearance. However, in active packaging, several variables must be considered, such as temperature control and different gas formulations with different product types and microorganisms. Active packaging refers to the incorporation of additive agents into packaging materials with the purpose of maintaining or extending food product quality and shelf life. Intelligent packaging is emerging as a potential advantage in food processing and is an especially useful tool for tracking product information and monitoring product conditions. Moreover, intelligent packaging facilitates data access and information exchange by altering conditions inside or outside the packaging and product. In spite of these advantages, few of these packaging systems are commercialized because of high cost, strict safety and hygiene regulations or limited consumer acceptance. Therefore more research is needed to develop cheaper, more easily applicable and effective packaging systems for various foods. © 2015 Society of Chemical Industry.

Pb Neurotoxicity: Neuropsychological Effects of Lead Toxicity

PubMed Central

Mason, Lisa H.; Harp, Jordan P.; Han, Dong Y.

2014-01-01

Neurotoxicity is a term used to describe neurophysiological changes caused by exposure to toxic agents. Such exposure can result in neurocognitive symptoms and/or psychiatric disturbances. Common toxic agents include heavy metals, drugs, organophosphates, bacterial, and animal neurotoxins. Among heavy metal exposures, lead exposure is one of the most common exposures that can lead to significant neuropsychological and functional decline in humans. In this review, neurotoxic lead exposure's pathophysiology, etiology, and epidemiology are explored. In addition, commonly associated neuropsychological difficulties in intelligence, memory, executive functioning, attention, processing speed, language, visuospatial skills, motor skills, and affect/mood are explored. PMID:24516855

A Prussian Blue-Based Core-Shell Hollow-Structured Mesoporous Nanoparticle as a Smart Theranostic Agent with Ultrahigh pH-Responsive Longitudinal Relaxivity.

PubMed

Cai, Xiaojun; Gao, Wei; Ma, Ming; Wu, Meiying; Zhang, Linlin; Zheng, Yuanyi; Chen, Hangrong; Shi, Jianlin

2015-11-04

Novel core-shell hollow mesoporous Prussian blue @ Mn-containing Prussian blue analogue (HMPB@MnPBA) nanoparticles, designated as HMPB-Mn) as an intelligent theranostic nanoagent, are successfully constructed by coating a similarly crystal-structured MnPBA onto HMPB. This can be used as a pH-responsive T1 -weighted magnetic resonance imaging contrast agent with ultrahigh longitudinal relaxivity (r1 = 7.43 m m(-1) s(-1) ), and achieves the real-time monitoring of drug release. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support

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

Hohimer, Ryan E.; Greitzer, Frank L.; Noonan, Christine F.

2011-11-15

We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.

Net-Centric Information and Knowledge Management and Dissemination for Data-to-Decision C2 Applications Using Intelligent Agents and Service-Oriented Architectures

DTIC Science & Technology

2011-11-01

data. s to make time rations. TITA lish and Subs ge messages i y FBCB2 and y gathering an rt tactical deci ontinuous asse s, including ions through...well as one ad from data-t y spans multip and control command (M red, Fused, a eports. (BCW) tric agent-bas y from TITA sts to dismoun...new ong all TITA current state of nit, and proces emination Sup ge transport s echelons a ort mechanis mentation of X le dynamic n alized or a pur

Risk-Seeking Versus Risk-Avoiding Investments in Noisy Periodic Environments

NASA Astrophysics Data System (ADS)

Navarro-Barrientos, J. Emeterio; Walter, Frank E.; Schweitzer, Frank

We study the performance of various agent strategies in an artificial investment scenario. Agents are equipped with a budget, x(t), and at each time step invest a particular fraction, q(t), of their budget. The return on investment (RoI), r(t), is characterized by a periodic function with different types and levels of noise. Risk-avoiding agents choose their fraction q(t) proportional to the expected positive RoI, while risk-seeking agents always choose a maximum value qmax if they predict the RoI to be positive ("everything on red"). In addition to these different strategies, agents have different capabilities to predict the future r(t), dependent on their internal complexity. Here, we compare "zero-intelligent" agents using technical analysis (such as moving least squares) with agents using reinforcement learning or genetic algorithms to predict r(t). The performance of agents is measured by their average budget growth after a certain number of time steps. We present results of extensive computer simulations, which show that, for our given artificial environment, (i) the risk-seeking strategy outperforms the risk-avoiding one, and (ii) the genetic algorithm was able to find this optimal strategy itself, and thus outperforms other prediction approaches considered.

Effective Team Support: From Modeling to Software Agents

NASA Technical Reports Server (NTRS)

Remington, Roger W. (Technical Monitor); John, Bonnie; Sycara, Katia

2003-01-01

The purpose of this research contract was to perform multidisciplinary research between CMU psychologists, computer scientists and engineers and NASA researchers to design a next generation collaborative system to support a team of human experts and intelligent agents. To achieve robust performance enhancement of such a system, we had proposed to perform task and cognitive modeling to thoroughly understand the impact technology makes on the organization and on key individual personnel. Guided by cognitively-inspired requirements, we would then develop software agents that support the human team in decision making, information filtering, information distribution and integration to enhance team situational awareness. During the period covered by this final report, we made substantial progress in modeling infrastructure and task infrastructure. Work is continuing under a different contract to complete empirical data collection, cognitive modeling, and the building of software agents to support the teams task.

Monte-Carlo Tree Search in Settlers of Catan

NASA Astrophysics Data System (ADS)

Szita, István; Chaslot, Guillaume; Spronck, Pieter

Games are considered important benchmark opportunities for artificial intelligence research. Modern strategic board games can typically be played by three or more people, which makes them suitable test beds for investigating multi-player strategic decision making. Monte-Carlo Tree Search (MCTS) is a recently published family of algorithms that achieved successful results with classical, two-player, perfect-information games such as Go. In this paper we apply MCTS to the multi-player, non-deterministic board game Settlers of Catan. We implemented an agent that is able to play against computer-controlled and human players. We show that MCTS can be adapted successfully to multi-agent environments, and present two approaches of providing the agent with a limited amount of domain knowledge. Our results show that the agent has a considerable playing strength when compared to game implementation with existing heuristics. So, we may conclude that MCTS is a suitable tool for achieving a strong Settlers of Catan player.

Social dilemma structure hidden behind traffic flow with route selection

NASA Astrophysics Data System (ADS)

Tanimoto, Jun; Nakamura, Kousuke

2016-10-01

Several traffic flows contain social dilemma structures. Herein, we explored a route-selection problem using a cellular automaton simulation dovetailed with evolutionary game theory. In our model, two classes of driver-agents coexist: D agents (defective strategy), which refer to traffic information for route selection to move fast, and C agents (cooperative strategy), which are insensitive to information and less inclined to move fast. Although no evidence suggests that the social dilemma structure in low density causes vehicles to move freely and that in high density causes traffic jams, we found a structure that corresponds to an n-person (multiplayer) Chicken (n-Chicken) game if the provided traffic information is inappropriate. If appropriate traffic information is given to the agents, the n-Chicken game can be solved. The information delivered to vehicles is crucial for easing the social dilemma due to urban traffic congestion when developing technologies to support the intelligent transportation system (ITS).

Effective Team Support: From Task and Cognitive Modeling to Software Agents for Time-Critical Complex Work Environments

NASA Technical Reports Server (NTRS)

Remington, Roger W. (Technical Monitor); John, Bonnie E.; Sycara, Katia

2005-01-01

The purpose of this research contract was to perform multidisciplinary research between CMU psychologists, computer scientists and NASA researchers to design a next generation collaborative system to support a team of human experts and intelligent agents. To achieve robust performance enhancement of such a system, we had proposed to perform task and cognitive modeling to thoroughly understand the impact technology makes on the organization and on key individual personnel. Guided by cognitively-inspired requirements, we would then develop software agents that support the human team in decision making, information filtering, information distribution and integration to enhance team situational awareness. During the period covered by this final report, we made substantial progress in completing a system for empirical data collection, cognitive modeling, and the building of software agents to support a team's tasks, and in running experiments for the collection of baseline data.

Multi-Agent Architecture with Support to Quality of Service and Quality of Control

NASA Astrophysics Data System (ADS)

Poza-Luján, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, Jose-Enrique

Multi Agent Systems (MAS) are one of the most suitable frameworks for the implementation of intelligent distributed control system. Agents provide suitable flexibility to give support to implied heterogeneity in cyber-physical systems. Quality of Service (QoS) and Quality of Control (QoC) parameters are commonly utilized to evaluate the efficiency of the communications and the control loop. Agents can use the quality measures to take a wide range of decisions, like suitable placement on the control node or to change the workload to save energy. This article describes the architecture of a multi agent system that provides support to QoS and QoC parameters to optimize de system. The architecture uses a Publish-Subscriber model, based on Data Distribution Service (DDS) to send the control messages. Due to the nature of the Publish-Subscribe model, the architecture is suitable to implement event-based control (EBC) systems. The architecture has been called FSACtrl.

A framework for learning and planning against switching strategies in repeated games

NASA Astrophysics Data System (ADS)

Hernandez-Leal, Pablo; Munoz de Cote, Enrique; Sucar, L. Enrique

2014-04-01

Intelligent agents, human or artificial, often change their behaviour as they interact with other agents. For an agent to optimise its performance when interacting with such agents, it must be capable of detecting and adapting according to such changes. This work presents an approach on how to effectively deal with non-stationary switching opponents in a repeated game context. Our main contribution is a framework for online learning and planning against opponents that switch strategies. We present how two opponent modelling techniques work within the framework and prove the usefulness of the approach experimentally in the iterated prisoner's dilemma, when the opponent is modelled as an agent that switches between different strategies (e.g. TFT, Pavlov and Bully). The results of both models were compared against each other and against a state-of-the-art non-stationary reinforcement learning technique. Results reflect that our approach obtains competitive results without needing an offline training phase, as opposed to the state-of-the-art techniques.

Designing Agent Collectives For Systems With Markovian Dynamics

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Lawson, John W.

2004-01-01

The Collective Intelligence (COIN) framework concerns the design of collectives of agents so that as those agents strive to maximize their individual utility functions, their interaction causes a provided world utility function concerning the entire collective to be also maximized. Here we show how to extend that framework to scenarios having Markovian dynamics when no re-evolution of the system from counter-factual initial conditions (an often expensive calculation) is permitted. Our approach transforms the (time-extended) argument of each agent's utility function before evaluating that function. This transformation has benefits in scenarios not involving Markovian dynamics of an agent's utility function are observable. We investigate this transformation in simulations involving both hear and quadratic (nonlinear) dynamics. In addition, we find that a certain subset of these transformations, which result in utilities that have low opacity (analogous to having high signal to noise) but are not factored (analogous to not being incentive compatible), reliably improve performance over that arising with factored utilities. We also present a Taylor Series method for the fully general nonlinear case.

Information Professionals as Intelligent Agents--Or When Is a Knowbot Only a Robot?

ERIC Educational Resources Information Center

Hey, Jessie

With the explosion in information resources being developed by computer scientists, subject specialists, librarians, and commercial companies, the challenge for the information professional is to keep abreast of the most significant developments and to distill the information for a wide range of users. This paper looks at some of the developments…

Community-Organizing Agent: An Artificial Intelligent System for Building Learning Communities among Large Numbers of Learners

ERIC Educational Resources Information Center

Yang, Fan; Wang, Minjuan; Shen, Ruimin; Han, Peng

2007-01-01

Web-based (or online) learning provides an unprecedented flexibility and convenience to both learners and instructors. However, large online classes relying on instructor-centered presentations could tend to isolate many learners. The size of these classes and the wide dispersion of the learners make it challenging for instructors to interact with…

Human Factors in Industrial and Consumer Products and Services

DTIC Science & Technology

2006-03-24

modeling; simulation and intelligent agents; Transportation ; Space and aviation; Telecommunication and web applications; Consumer products; and Customer...the user feedback throughout the product development. Self-explaining and forgiving roads to improve safety Karel Brookhuis, Dick de Waard...in a simulated ambulance dispatcher’s task Ben Mulder, Anje Kruizinga & Dick de Waard University of Groningen, Experimental and Work Psychology

Implementation of an Intelligent Tutorial System for Socioenvironmental Management Projects

ERIC Educational Resources Information Center

Vera, Gil; Daniel, Víctor; Awad, Gabriel

2015-01-01

The agents responsible of execution of physical infrastructure projects of the Government of Antioquia must know the theories and concepts related to the socio-environmental management of physical infrastructure projects. In the absence of tools and the little information on the subject, it is necessary to build a m-learning tool to facilitate to…

Parallel Logic Programming Architecture

DTIC Science & Technology

1990-04-01

Section 3.1. 3.1. A STATIC ALLOCATION SCHEME (SAS) Methods that have been used for decomposing distributed problems in artificial intelligence...multiple agents, knowledge organization and allocation, and cooperative parallel execution. These difficulties are common to distributed artificial ...for the following reasons. First, intellegent backtracking requires much more bookkeeping and is therefore more costly during consult-time and during

Cognitive Support Embedded in Self-Regulated E-Learning Systems for Students with Special Learning Needs

ERIC Educational Resources Information Center

Chatzara, K.; Karagiannidis, C.; Stamatis, D.

2016-01-01

This paper presents an anthropocentric approach in human-machine interaction in the area of self-regulated e-learning. In an attempt to enhance communication mediated through computers for pedagogical use we propose the incorporation of an intelligent emotional agent that is represented by a synthetic character with multimedia capabilities,…

Toward a Theory-Based Natural Language Capability in Robots and Other Embodied Agents: Evaluating Hausser's SLIM Theory and Database Semantics

ERIC Educational Resources Information Center

Burk, Robin K.

2010-01-01

Computational natural language understanding and generation have been a goal of artificial intelligence since McCarthy, Minsky, Rochester and Shannon first proposed to spend the summer of 1956 studying this and related problems. Although statistical approaches dominate current natural language applications, two current research trends bring…

Pedagogical Agent Gestures to Improve Learner Comprehension of Abstract Concepts in Hints

ERIC Educational Resources Information Center

Martins, Igor; de Morais, Felipe; Schaab, Bruno; Jaques, Patricia

2016-01-01

In most Intelligent Tutoring Systems, the help messages (hints) are not very clear for students as they are only presented textually and have little connection with the task elements. This can lead to students' undesired behaviors, like gaming the system, associated with low performance. In this paper, the authors aim at evaluating if the gestures…

Evaluating Social Causality and Responsibility Models: An Initial Report

DTIC Science & Technology

2005-01-01

ICT Technical Report ICT-TR-03-2005 Evaluating Social Causality and Responsibility ... social intelligent agents. In this report, we present a general computational model of social causality and responsibility , and empirical results of...2005 to 00-00-2005 4. TITLE AND SUBTITLE Evaluating Social Causality and Responsibility Models: An Initial Report 5a. CONTRACT NUMBER 5b. GRANT

Mobile robot navigation modulated by artificial emotions.

PubMed

Lee-Johnson, C P; Carnegie, D A

2010-04-01

For artificial intelligence research to progress beyond the highly specialized task-dependent implementations achievable today, researchers may need to incorporate aspects of biological behavior that have not traditionally been associated with intelligence. Affective processes such as emotions may be crucial to the generalized intelligence possessed by humans and animals. A number of robots and autonomous agents have been created that can emulate human emotions, but the majority of this research focuses on the social domain. In contrast, we have developed a hybrid reactive/deliberative architecture that incorporates artificial emotions to improve the general adaptive performance of a mobile robot for a navigation task. Emotions are active on multiple architectural levels, modulating the robot's decisions and actions to suit the context of its situation. Reactive emotions interact with the robot's control system, altering its parameters in response to appraisals from short-term sensor data. Deliberative emotions are learned associations that bias path planning in response to eliciting objects or events. Quantitative results are presented that demonstrate situations in which each artificial emotion can be beneficial to performance.

Detection of the Deformation of an Intelligent Textile in a Specific Point

PubMed Central

Alsina, Maria; Escudero, Francesc; Margalef, Jordi; Cambra, Vicente; Gisbert, José

2007-01-01

An intelligent textile is a textile structure that measures and reacts in front of external agents or stimulus with or without integrated electronic equipment. The finality of the present textile is to take one more step towards intelligent textile, considering the integration of electronics and textile needs, to be industrially viable and to keep up the necessary competitiveness, raising the final price as little as possible. The finality of these experiments is to develop a textile that varies in conductivity and resistance in relation to the elongation of the textile, detecting changes caused by the alteration of a piece of clothing, from the pressure of a finger on the material, for example. One of the most important characteristics of textile is the capacity of reproducing measures, of varying the response in different tests. Two lines of research were opened: the study of the most adequate structure to achieve a response that can be reproduced and the study of the best way of taking measures without altering the behavior of the textile.

Emergency Response Virtual Environment for Safe Schools

NASA Technical Reports Server (NTRS)

Wasfy, Ayman; Walker, Teresa

2008-01-01

An intelligent emergency response virtual environment (ERVE) that provides emergency first responders, response planners, and managers with situational awareness as well as training and support for safe schools is presented. ERVE incorporates an intelligent agent facility for guiding and assisting the user in the context of the emergency response operations. Response information folders capture key information about the school. The system enables interactive 3D visualization of schools and academic campuses, including the terrain and the buildings' exteriors and interiors in an easy to use Web..based interface. ERVE incorporates live camera and sensors feeds and can be integrated with other simulations such as chemical plume simulation. The system is integrated with a Geographical Information System (GIS) to enable situational awareness of emergency events and assessment of their effect on schools in a geographic area. ERVE can also be integrated with emergency text messaging notification systems. Using ERVE, it is now possible to address safe schools' emergency management needs with a scaleable, seamlessly integrated and fully interactive intelligent and visually compelling solution.

An intelligent re-shieldable targeting system for enhanced tumor accumulation.

PubMed

Hu, Zhenpeng; Ma, Jinlong; Fu, Fei; Cui, Chen; Li, Xiaomin; Wang, Xinyu; Wang, Wei; Wan, Yeda; Yuan, Zhi

2017-12-28

Programmed ligand targeting strategy promotes the blood circulation stability of nanoparticles by shielding the ligand. However, the irreversible shielding causes the deshielded nanoparticles to be easily recognized and cleared by the reticuloendothelial system (RES), impeding their further retention in the tumor. Here, we for the first time prove the superiority of the intelligent re-shieldable targeting system that is based on the pH-responsive self-assembly/disassembly of gold nanoparticles. The system can enhance the stability of gold nanoparticles in the blood circulation (2.6-fold at 24h), reduce uptake by the RES (35% lower) and improve tumor accumulation (41% higher by analysis of gold content in tumor) effectively compared with the conventional irreversible system. Furthermore, preliminary study indicates that the system could be applied as computed tomography contrast agent in tumor imaging. The in vivo validity of the intelligent re-shieldable targeting system provides inspiration for the design of nanomaterials for cancer diagnosis and treatment. Copyright © 2017. Published by Elsevier B.V.

Designing a holistic end-to-end intelligent network analysis and security platform

NASA Astrophysics Data System (ADS)

Alzahrani, M.

2018-03-01

Firewall protects a network from outside attacks, however, once an attack entering a network, it is difficult to detect. Recent significance accidents happened. i.e.: millions of Yahoo email account were stolen and crucial data from institutions are held for ransom. Within two year Yahoo’s system administrators were not aware that there are intruder inside the network. This happened due to the lack of intelligent tools to monitor user behaviour in internal network. This paper discusses a design of an intelligent anomaly/malware detection system with proper proactive actions. The aim is to equip the system administrator with a proper tool to battle the insider attackers. The proposed system adopts machine learning to analyse user’s behaviour through the runtime behaviour of each node in the network. The machine learning techniques include: deep learning, evolving machine learning perceptron, hybrid of Neural Network and Fuzzy, as well as predictive memory techniques. The proposed system is expanded to deal with larger network using agent techniques.

Increasing Physical Activity Amongst Overweight and Obese Cancer Survivors Using an Alexa-Based Intelligent Agent for Patient Coaching: Protocol for the Physical Activity by Technology Help (PATH) Trial.

PubMed

Hassoon, Ahmed; Schrack, Jennifer; Naiman, Daniel; Lansey, Dina; Baig, Yasmin; Stearns, Vered; Celentano, David; Martin, Seth; Appel, Lawrence

2018-02-12

Physical activity has established health benefits, but motivation and adherence remain challenging. We designed and launched a three-arm randomized trial to test artificial intelligence technology solutions to increase daily physical activity in cancer survivors. A single-center, three-arm randomized clinical trial with an allocation ration of 1:1:1: (A) control, in which participants are provided written materials about the benefits of physical activity; (B) text intervention, where participants receive daily motivation from a fully automated, data-driven algorithmic text message via mobile phone (Coachtext); and (C) Voice Assist intervention, where participants are provided with an in-home on demand autonomous Intelligent Agent using data driven Interactive Digital Voice Assist on the Amazon Alexa/Echo (MyCoach). The study runs for 5 weeks: a one-week run-in to establish baseline, followed by 4 weeks of intervention. Data for study outcomes is collected automatically through a wearable sensor, and data are transferred in real-time to the study server. The recruitment goal is 42 participants, 14 in each arm. Electronic health records are used to prescreen candidates, with 39 participants recruited to date. This study aims to investigate the effects of different types of intelligent technology solutions on promoting physical activity in cancer survivors. This innovative approach can easily be expanded and customized to other interventions. Early lessons from our initial participants are helping us develop additional advanced solutions to improve health outcomes. Retrospectively registered on July 10, 2017 at ClinicalTrials.gov: NCT03212079; https://clinicaltrials.gov/ct2/show/NCT03212079 (Archived by WebCite at http://www.webcitation.org/6wgvqjTji). ©Ahmed Hassoon, Jennifer Schrack, Daniel Naiman, Dina Lansey, Yasmin Baig, Vered Stearns, David Celentano, Seth Martin, Lawrence Appel. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 12.02.2018.

Adaptive Neuro-Fuzzy Determination of the Effect of Experimental Parameters on Vehicle Agent Speed Relative to Vehicle Intruder.

PubMed

Shamshirband, Shahaboddin; Banjanovic-Mehmedovic, Lejla; Bosankic, Ivan; Kasapovic, Suad; Abdul Wahab, Ainuddin Wahid Bin

2016-01-01

Intelligent Transportation Systems rely on understanding, predicting and affecting the interactions between vehicles. The goal of this paper is to choose a small subset from the larger set so that the resulting regression model is simple, yet have good predictive ability for Vehicle agent speed relative to Vehicle intruder. The method of ANFIS (adaptive neuro fuzzy inference system) was applied to the data resulting from these measurements. The ANFIS process for variable selection was implemented in order to detect the predominant variables affecting the prediction of agent speed relative to intruder. This process includes several ways to discover a subset of the total set of recorded parameters, showing good predictive capability. The ANFIS network was used to perform a variable search. Then, it was used to determine how 9 parameters (Intruder Front sensors active (boolean), Intruder Rear sensors active (boolean), Agent Front sensors active (boolean), Agent Rear sensors active (boolean), RSSI signal intensity/strength (integer), Elapsed time (in seconds), Distance between Agent and Intruder (m), Angle of Agent relative to Intruder (angle between vehicles °), Altitude difference between Agent and Intruder (m)) influence prediction of agent speed relative to intruder. The results indicated that distance between Vehicle agent and Vehicle intruder (m) and angle of Vehicle agent relative to Vehicle Intruder (angle between vehicles °) is the most influential parameters to Vehicle agent speed relative to Vehicle intruder.

Mother ship and physical agents collaboration

NASA Astrophysics Data System (ADS)

Young, Stuart H.; Budulas, Peter P.; Emmerman, Philip J.

1999-07-01

This paper discusses ongoing research at the U.S. Army Research Laboratory that investigates the feasibility of developing a collaboration architecture between small physical agents and a mother ship. This incudes the distribution of planning, perception, mobility, processing and communications requirements between the mother ship and the agents. Small physical agents of the future will be virtually everywhere on the battlefield of the 21st century. A mother ship that is coupled to a team of small collaborating physical agents (conducting tasks such as Reconnaissance, Surveillance, and Target Acquisition (RSTA); logistics; sentry; and communications relay) will be used to build a completely effective and mission capable intelligent system. The mother ship must have long-range mobility to deploy the small, highly maneuverable agents that will operate in urban environments and more localized areas, and act as a logistics base for the smaller agents. The mother ship also establishes a robust communications network between the agents and is the primary information disseminating and receiving point to the external world. Because of its global knowledge and processing power, the mother ship does the high-level control and planning for the collaborative physical agents. This high level control and interaction between the mother ship and its agents (including inter agent collaboration) will be software agent architecture based. The mother ship incorporates multi-resolution battlefield visualization and analysis technology, which aids in mission planning and sensor fusion.

Cooperation and Coordination Between Fuzzy Reinforcement Learning Agents in Continuous State Partially Observable Markov Decision Processes

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.; Vengerov, David

1999-01-01

Successful operations of future multi-agent intelligent systems require efficient cooperation schemes between agents sharing learning experiences. We consider a pseudo-realistic world in which one or more opportunities appear and disappear in random locations. Agents use fuzzy reinforcement learning to learn which opportunities are most worthy of pursuing based on their promise rewards, expected lifetimes, path lengths and expected path costs. We show that this world is partially observable because the history of an agent influences the distribution of its future states. We consider a cooperation mechanism in which agents share experience by using and-updating one joint behavior policy. We also implement a coordination mechanism for allocating opportunities to different agents in the same world. Our results demonstrate that K cooperative agents each learning in a separate world over N time steps outperform K independent agents each learning in a separate world over K*N time steps, with this result becoming more pronounced as the degree of partial observability in the environment increases. We also show that cooperation between agents learning in the same world decreases performance with respect to independent agents. Since cooperation reduces diversity between agents, we conclude that diversity is a key parameter in the trade off between maximizing utility from cooperation when diversity is low and maximizing utility from competitive coordination when diversity is high.

IMAGE: A Design Integration Framework Applied to the High Speed Civil Transport

NASA Technical Reports Server (NTRS)

Hale, Mark A.; Craig, James I.

1993-01-01

Effective design of the High Speed Civil Transport requires the systematic application of design resources throughout a product's life-cycle. Information obtained from the use of these resources is used for the decision-making processes of Concurrent Engineering. Integrated computing environments facilitate the acquisition, organization, and use of required information. State-of-the-art computing technologies provide the basis for the Intelligent Multi-disciplinary Aircraft Generation Environment (IMAGE) described in this paper. IMAGE builds upon existing agent technologies by adding a new component called a model. With the addition of a model, the agent can provide accountable resource utilization in the presence of increasing design fidelity. The development of a zeroth-order agent is used to illustrate agent fundamentals. Using a CATIA(TM)-based agent from previous work, a High Speed Civil Transport visualization system linking CATIA, FLOPS, and ASTROS will be shown. These examples illustrate the important role of the agent technologies used to implement IMAGE, and together they demonstrate that IMAGE can provide an integrated computing environment for the design of the High Speed Civil Transport.

Intelligent layered nanoflare: ``lab-on-a-nanoparticle'' for multiple DNA logic gate operations and efficient intracellular delivery

NASA Astrophysics Data System (ADS)

Yang, Bin; Zhang, Xiao-Bing; Kang, Li-Ping; Huang, Zhi-Mei; Shen, Guo-Li; Yu, Ru-Qin; Tan, Weihong

2014-07-01

DNA strand displacement cascades have been engineered to construct various fascinating DNA circuits. However, biological applications are limited by the insufficient cellular internalization of naked DNA structures, as well as the separated multicomponent feature. In this work, these problems are addressed by the development of a novel DNA nanodevice, termed intelligent layered nanoflare, which integrates DNA computing at the nanoscale, via the self-assembly of DNA flares on a single gold nanoparticle. As a ``lab-on-a-nanoparticle'', the intelligent layered nanoflare could be engineered to perform a variety of Boolean logic gate operations, including three basic logic gates, one three-input AND gate, and two complex logic operations, in a digital non-leaky way. In addition, the layered nanoflare can serve as a programmable strategy to sequentially tune the size of nanoparticles, as well as a new fingerprint spectrum technique for intelligent multiplex biosensing. More importantly, the nanoflare developed here can also act as a single entity for intracellular DNA logic gate delivery, without the need of commercial transfection agents or other auxiliary carriers. By incorporating DNA circuits on nanoparticles, the presented layered nanoflare will broaden the applications of DNA circuits in biological systems, and facilitate the development of DNA nanotechnology.DNA strand displacement cascades have been engineered to construct various fascinating DNA circuits. However, biological applications are limited by the insufficient cellular internalization of naked DNA structures, as well as the separated multicomponent feature. In this work, these problems are addressed by the development of a novel DNA nanodevice, termed intelligent layered nanoflare, which integrates DNA computing at the nanoscale, via the self-assembly of DNA flares on a single gold nanoparticle. As a ``lab-on-a-nanoparticle'', the intelligent layered nanoflare could be engineered to perform a variety of Boolean logic gate operations, including three basic logic gates, one three-input AND gate, and two complex logic operations, in a digital non-leaky way. In addition, the layered nanoflare can serve as a programmable strategy to sequentially tune the size of nanoparticles, as well as a new fingerprint spectrum technique for intelligent multiplex biosensing. More importantly, the nanoflare developed here can also act as a single entity for intracellular DNA logic gate delivery, without the need of commercial transfection agents or other auxiliary carriers. By incorporating DNA circuits on nanoparticles, the presented layered nanoflare will broaden the applications of DNA circuits in biological systems, and facilitate the development of DNA nanotechnology. Electronic supplementary information (ESI) available: Additional figures (Table S1, Fig. S1-S5). See DOI: 10.1039/c4nr01676a

Developing Dynamic Field Theory Architectures for Embodied Cognitive Systems with cedar.

PubMed

Lomp, Oliver; Richter, Mathis; Zibner, Stephan K U; Schöner, Gregor

2016-01-01

Embodied artificial cognitive systems, such as autonomous robots or intelligent observers, connect cognitive processes to sensory and effector systems in real time. Prime candidates for such embodied intelligence are neurally inspired architectures. While components such as forward neural networks are well established, designing pervasively autonomous neural architectures remains a challenge. This includes the problem of tuning the parameters of such architectures so that they deliver specified functionality under variable environmental conditions and retain these functions as the architectures are expanded. The scaling and autonomy problems are solved, in part, by dynamic field theory (DFT), a theoretical framework for the neural grounding of sensorimotor and cognitive processes. In this paper, we address how to efficiently build DFT architectures that control embodied agents and how to tune their parameters so that the desired cognitive functions emerge while such agents are situated in real environments. In DFT architectures, dynamic neural fields or nodes are assigned dynamic regimes, that is, attractor states and their instabilities, from which cognitive function emerges. Tuning thus amounts to determining values of the dynamic parameters for which the components of a DFT architecture are in the specified dynamic regime under the appropriate environmental conditions. The process of tuning is facilitated by the software framework cedar , which provides a graphical interface to build and execute DFT architectures. It enables to change dynamic parameters online and visualize the activation states of any component while the agent is receiving sensory inputs in real time. Using a simple example, we take the reader through the workflow of conceiving of DFT architectures, implementing them on embodied agents, tuning their parameters, and assessing performance while the system is coupled to real sensory inputs.

Developing Dynamic Field Theory Architectures for Embodied Cognitive Systems with cedar

PubMed Central

Lomp, Oliver; Richter, Mathis; Zibner, Stephan K. U.; Schöner, Gregor

2016-01-01

Embodied artificial cognitive systems, such as autonomous robots or intelligent observers, connect cognitive processes to sensory and effector systems in real time. Prime candidates for such embodied intelligence are neurally inspired architectures. While components such as forward neural networks are well established, designing pervasively autonomous neural architectures remains a challenge. This includes the problem of tuning the parameters of such architectures so that they deliver specified functionality under variable environmental conditions and retain these functions as the architectures are expanded. The scaling and autonomy problems are solved, in part, by dynamic field theory (DFT), a theoretical framework for the neural grounding of sensorimotor and cognitive processes. In this paper, we address how to efficiently build DFT architectures that control embodied agents and how to tune their parameters so that the desired cognitive functions emerge while such agents are situated in real environments. In DFT architectures, dynamic neural fields or nodes are assigned dynamic regimes, that is, attractor states and their instabilities, from which cognitive function emerges. Tuning thus amounts to determining values of the dynamic parameters for which the components of a DFT architecture are in the specified dynamic regime under the appropriate environmental conditions. The process of tuning is facilitated by the software framework cedar, which provides a graphical interface to build and execute DFT architectures. It enables to change dynamic parameters online and visualize the activation states of any component while the agent is receiving sensory inputs in real time. Using a simple example, we take the reader through the workflow of conceiving of DFT architectures, implementing them on embodied agents, tuning their parameters, and assessing performance while the system is coupled to real sensory inputs. PMID:27853431

Collected notes from the Benchmarks and Metrics Workshop

NASA Technical Reports Server (NTRS)

Drummond, Mark E.; Kaelbling, Leslie P.; Rosenschein, Stanley J.

1991-01-01

In recent years there has been a proliferation of proposals in the artificial intelligence (AI) literature for integrated agent architectures. Each architecture offers an approach to the general problem of constructing an integrated agent. Unfortunately, the ways in which one architecture might be considered better than another are not always clear. There has been a growing realization that many of the positive and negative aspects of an architecture become apparent only when experimental evaluation is performed and that to progress as a discipline, we must develop rigorous experimental methods. In addition to the intrinsic intellectual interest of experimentation, rigorous performance evaluation of systems is also a crucial practical concern to our research sponsors. DARPA, NASA, and AFOSR (among others) are actively searching for better ways of experimentally evaluating alternative approaches to building intelligent agents. One tool for experimental evaluation involves testing systems on benchmark tasks in order to assess their relative performance. As part of a joint DARPA and NASA funded project, NASA-Ames and Teleos Research are carrying out a research effort to establish a set of benchmark tasks and evaluation metrics by which the performance of agent architectures may be determined. As part of this project, we held a workshop on Benchmarks and Metrics at the NASA Ames Research Center on June 25, 1990. The objective of the workshop was to foster early discussion on this important topic. We did not achieve a consensus, nor did we expect to. Collected here is some of the information that was exchanged at the workshop. Given here is an outline of the workshop, a list of the participants, notes taken on the white-board during open discussions, position papers/notes from some participants, and copies of slides used in the presentations.

Modelling of robotic work cells using agent based-approach

NASA Astrophysics Data System (ADS)

Sękala, A.; Banaś, W.; Gwiazda, A.; Monica, Z.; Kost, G.; Hryniewicz, P.

2016-08-01

In the case of modern manufacturing systems the requirements, both according the scope and according characteristics of technical procedures are dynamically changing. This results in production system organization inability to keep up with changes in a market demand. Accordingly, there is a need for new design methods, characterized, on the one hand with a high efficiency and on the other with the adequate level of the generated organizational solutions. One of the tools that could be used for this purpose is the concept of agent systems. These systems are the tools of artificial intelligence. They allow assigning to agents the proper domains of procedures and knowledge so that they represent in a self-organizing system of an agent environment, components of a real system. The agent-based system for modelling robotic work cell should be designed taking into consideration many limitations considered with the characteristic of this production unit. It is possible to distinguish some grouped of structural components that constitute such a system. This confirms the structural complexity of a work cell as a specific production system. So it is necessary to develop agents depicting various aspects of the work cell structure. The main groups of agents that are used to model a robotic work cell should at least include next pattern representatives: machine tool agents, auxiliary equipment agents, robots agents, transport equipment agents, organizational agents as well as data and knowledge bases agents. In this way it is possible to create the holarchy of the agent-based system.

Integrating deliberative planning in a robot architecture

NASA Technical Reports Server (NTRS)

Elsaesser, Chris; Slack, Marc G.

1994-01-01

The role of planning and reactive control in an architecture for autonomous agents is discussed. The postulated architecture seperates the general robot intelligence problem into three interacting pieces: (1) robot reactive skills, i.e., grasping, object tracking, etc.; (2) a sequencing capability to differentially ativate the reactive skills; and (3) a delibrative planning capability to reason in depth about goals, preconditions, resources, and timing constraints. Within the sequencing module, caching techniques are used for handling routine activities. The planning system then builds on these cached solutions to routine tasks to build larger grain sized primitives. This eliminates large numbers of essentially linear planning problems. The architecture will be used in the future to incorporate in robots cognitive capabilites normally associated with intelligent behavior.

Resilient control of cyber-physical systems against intelligent attacker: a hierarchal stackelberg game approach

NASA Astrophysics Data System (ADS)

Yuan, Yuan; Sun, Fuchun; Liu, Huaping

2016-07-01

This paper is concerned with the resilient control under denial-of-service attack launched by the intelligent attacker. The resilient control system is modelled as a multi-stage hierarchical game with a corresponding hierarchy of decisions made at cyber and physical layer, respectively. Specifically, the interaction in the cyber layer between different security agents is modelled as a static infinite Stackelberg game, while in the underlying physical layer the full-information H∞ minimax control with package drops is modelled as a different Stackelberg game. Both games are solved sequentially, which is consistent with the actual situations. Finally, the proposed method is applied to the load frequency control of the power system, which demonstrates its effectiveness.

Emergent sensing of complex environments by mobile animal groups.

PubMed

Berdahl, Andrew; Torney, Colin J; Ioannou, Christos C; Faria, Jolyon J; Couzin, Iain D

2013-02-01

The capacity for groups to exhibit collective intelligence is an often-cited advantage of group living. Previous studies have shown that social organisms frequently benefit from pooling imperfect individual estimates. However, in principle, collective intelligence may also emerge from interactions between individuals, rather than from the enhancement of personal estimates. Here, we reveal that this emergent problem solving is the predominant mechanism by which a mobile animal group responds to complex environmental gradients. Robust collective sensing arises at the group level from individuals modulating their speed in response to local, scalar, measurements of light and through social interaction with others. This distributed sensing requires only rudimentary cognition and thus could be widespread across biological taxa, in addition to being appropriate and cost-effective for robotic agents.

Questioning the social intelligence hypothesis.

PubMed

Holekamp, Kay E

2007-02-01

The social intelligence hypothesis posits that complex cognition and enlarged "executive brains" evolved in response to challenges that are associated with social complexity. This hypothesis has been well supported, but some recent data are inconsistent with its predictions. It is becoming increasingly clear that multiple selective agents, and non-selective constraints, must have acted to shape cognitive abilities in humans and other animals. The task now is to develop a larger theoretical framework that takes into account both inter-specific differences and similarities in cognition. This new framework should facilitate consideration of how selection pressures that are associated with sociality interact with those that are imposed by non-social forms of environmental complexity, and how both types of functional demands interact with phylogenetic and developmental constraints.

Geosimulation of urban growth and demographic decline in the Ruhr: a case study for 2025 using the artificial intelligence of cells and agents

NASA Astrophysics Data System (ADS)

Rienow, Andreas; Stenger, Dirk

2014-07-01

The Ruhr is an "old acquaintance" in the discourse of urban decline in old industrialized cities. The agglomeration has to struggle with archetypical problems of former monofunctional manufacturing cities. Surprisingly, the image of a shrinking city has to be refuted if you shift the focus from socioeconomic wealth to its morphological extension. Thus, it is the objective of this study to meet the challenge of modeling urban sprawl and demographic decline by combining two artificial intelligent solutions: The popular urban cellular automaton SLEUTH simulates urban growth using four simple but effective growth rules. In order to improve its performance, SLEUTH has been modified among others by combining it with a robust probability map based on support vector machines. Additionally, a complex multi-agent system is developed to simulate residential mobility in a shrinking city agglomeration: residential mobility and the housing market of shrinking city systems focuses on the dynamic of interregional housing markets implying the development of potential dwelling areas. The multi-agent system comprises the simulation of population patterns, housing prices, and housing demand in shrinking city agglomerations. Both models are calibrated and validated regarding their localization and quantification performance. Subsequently, the urban landscape configuration and composition of the Ruhr 2025 are simulated. A simple spatial join is used to combine the results serving as valuable inputs for future regional planning in the context of multifarious demographic change and preceding urban growth.

The Scientific Search for Extraterrestrial Intelligence: a Sociological Analysis.

NASA Astrophysics Data System (ADS)

Romesberg, Daniel Ray

1992-01-01

This study examines the search for extraterrestrial intelligence, as it has been conducted by scientists over the past century. The following questions are explored: (1) What are the historical patterns of American scientific interest in extraterrestrial intelligence? From a sociology of science perspective, how can these patterns of interest be explained? (2) Who are the most prominent scientists involved in SETI? What are their academic backgrounds? (3) How has the rather exotic idea of extraterrestrial intelligence managed to penetrate the realm of respectable science?. In order to measure the historical fluctuations of scientific interest in extraterrestrial intelligence, a frequency distribution of relevant articles published in American scientific journals over the past century has been constructed. The core scholars of the "extraterrestrial" field have been determined via citation analysis, in a selected portion of the scientific literature. An analysis of recent scientific literature on the Search for Extraterrestrial Intelligence (SETI) has revealed a number of tactics of legitimation and de-legitimation used by SETI proponents, as well as opponents. This study has generated the following findings: (1) Historically, there are three factors which tend to stimulate general scientific interest in extraterrestrial intelligence: First, the strong demonstration of the plausibility of extraterrestrial intelligence, or life, especially in a tangible, and therefore studiable location. Scientific laboratories are primary agents of plausibility here. Second, the organized political activity of SETI scientists. Third, the availability of government funding for searches for extraterrestrial intelligence, or life. (2) Statistically, the leading scholars of modern SETI are Sagan, Drake and Morrison. The field itself tends to be dominated by astronomers and physicists. (3) Because SETI has no concrete data, and is easily stigmatized as an illegitimate scientific activity, it must engage in an intense campaign of scientific legitimation. Most importantly, SETI scientists must try to resemble scientists who are engaged in "normal," respectable scientific activities. (4) The sociological study of SETI's history demonstrates the strengths and limits of the constructivist and realist approaches to the sociology of science. It suggests that sociological analyses of science should attempt to incorporate both analytical perspectives.

SURVIVABILITY THROUGH OPTIMIZING RESILIENT MECHANISMS (STORM)

DTIC Science & Technology

2017-04-01

STATEMENT Approved for Public Release; Distribution Unlimited. PA# 88ABW-2017-0894 Date Cleared: 07 Mar 2017 13. SUPPLEMENTARY NOTES 14. ABSTRACT Game ...quantitatively about cyber-attacks. Game theory is the branch of applied mathematics that formalizes strategic interaction among intelligent rational agents...mechanism based on game theory. This work has applied game theory to numerous cyber security problems: cloud security, cyber threat information sharing

A Framework System for Intelligent Support in Open Distributed Learning Environments--A Look Back from 16 Years Later

ERIC Educational Resources Information Center

Hoppe, H. Ulrich

2016-01-01

The 1998 paper by Martin Mühlenbrock, Frank Tewissen, and myself introduced a multi-agent architecture and a component engineering approach for building open distributed learning environments to support group learning in different types of classroom settings. It took up prior work on "multiple student modeling" as a method to configure…

Shifting the Load: A Peer Dialogue Agent That Encourages Its Human Collaborator to Contribute More to Problem Solving

ERIC Educational Resources Information Center

Howard, Cynthia; Jordan, Pamela; Di Eugenio, Barbara; Katz, Sandra

2017-01-01

Despite a growing need for educational tools that support students at the earliest phases of undergraduate Computer Science (CS) curricula, relatively few such tools exist--the majority being Intelligent Tutoring Systems. Since peer interactions more readily give rise to challenges and negotiations, another way in which students can become more…

Knowledge Management for Distributed Tracking

DTIC Science & Technology

2008-11-01

PACIFIC San Diego, California 92152-5001 M. T. Kohlheim, CAPT, USN Commanding Officer C. A. Keeney Technical Director ADMINISTRATIVE INFORMATION ...bearing cross-fix algorithm. Modeling and simulation was used to generate test data that intelligent agents ingested to search for information that...potential of this approach to reduce information overload for the operator. The KMDT approach demonstrates how knowledge management technologies can be

Distributed topology control algorithm for multihop wireless netoworks

NASA Technical Reports Server (NTRS)

Borbash, S. A.; Jennings, E. H.

2002-01-01

We present a network initialization algorithmfor wireless networks with distributed intelligence. Each node (agent) has only local, incomplete knowledge and it must make local decisions to meet a predefined global objective. Our objective is to use power control to establish a topology based onthe relative neighborhood graph which has good overall performance in terms of power usage, low interference, and reliability.

Activity Recognition for Agent Teams

DTIC Science & Technology

2007-07-01

Uncertainty in Artifcial Intelligence (UAI), 1994. [47] S. Intille and A. Bobick. Visual tracking using closed-worlds. Technical Report 294, MIT Media Lab...information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and...maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other

Using Artificial Physics to Control Agents

DTIC Science & Technology

1999-11-01

unlimited 13. SUPPLEMENTARY NOTES IEEE International Conference on Information, Intelligence, and Systems, Oct 31 -Nov 3,1999. Bethesda, MD 14. ABSTRACT...distributed control can also perform distributed computation. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same...1995. [9] H. Pattee. Artificial life needs a real epistemology. In Moran, Moreno, Merelo, and Chacon , editors, Advances in Artificial Life, pages

An Agent-Based Model for Navigation Simulation in a Heterogeneous Environment

ERIC Educational Resources Information Center

Shanklin, Teresa A.

2012-01-01

Complex navigation (e.g. indoor and outdoor environments) can be studied as a system-of-systems problem. The model is made up of disparate systems that can aid a user in navigating from one location to another, utilizing whatever sensor system or information is available. By using intelligent navigation sensors and techniques (e.g. RFID, Wifi,…

Constructing Virtual Training Demonstrations

DTIC Science & Technology

2008-12-01

virtual environments have been shown to be effective for training, and distributed game -based architectures contribute an added benefit of wide...investigation of how a demonstration authoring toolset can be constructed from existing virtual training environments using 3-D multiplayer gaming ...intelligent agents project to create AI middleware for simulations and videogames . The result was SimBionic®, which enables users to graphically author

Intelligent Processing of Ferroelectric Thin Films

DTIC Science & Technology

1993-09-03

the acetate precursors. The results from these experiments involving coprecipitation, hydrothermal , spray pyrolysis and freeze drying have shown that...Spray Pyrolysis (SP) D. Hydrothermal Processing (HP) The powder produced by each process was characterized by X-ray diffraction (XRD) and scanning...precursors were used as described above. Instead of ammonia solution, an oxalic acid solution was used as the3 precipitating agent. The precipitants

Integrating planning, execution, and learning

NASA Technical Reports Server (NTRS)

Kuokka, Daniel R.

1989-01-01

To achieve the goal of building an autonomous agent, the usually disjoint capabilities of planning, execution, and learning must be used together. An architecture, called MAX, within which cognitive capabilities can be purposefully and intelligently integrated is described. The architecture supports the codification of capabilities as explicit knowledge that can be reasoned about. In addition, specific problem solving, learning, and integration knowledge is developed.

Ship to Shore Data Communication and Prioritization

DTIC Science & Technology

2011-12-01

First Out FTP File Transfer Protocol GCCS-M Global Command and Control System Maritime HAIPE High Assurance Internet Protocol Encryptor HTTP Hypertext...Transfer Protocol (world wide web protocol ) IBS Integrated Bar Code System IDEF0 Integration Definition IER Information Exchange Requirements...INTEL Intelligence IP Internet Protocol IPT Integrated Product Team ISEA In-Service Engineering Agent ISNS Integrated Shipboard Network System IT

Learning Perfectly Secure Cryptography to Protect Communications with Adversarial Neural Cryptography

PubMed Central

2018-01-01

Researches in Artificial Intelligence (AI) have achieved many important breakthroughs, especially in recent years. In some cases, AI learns alone from scratch and performs human tasks faster and better than humans. With the recent advances in AI, it is natural to wonder whether Artificial Neural Networks will be used to successfully create or break cryptographic algorithms. Bibliographic review shows the main approach to this problem have been addressed throughout complex Neural Networks, but without understanding or proving the security of the generated model. This paper presents an analysis of the security of cryptographic algorithms generated by a new technique called Adversarial Neural Cryptography (ANC). Using the proposed network, we show limitations and directions to improve the current approach of ANC. Training the proposed Artificial Neural Network with the improved model of ANC, we show that artificially intelligent agents can learn the unbreakable One-Time Pad (OTP) algorithm, without human knowledge, to communicate securely through an insecure communication channel. This paper shows in which conditions an AI agent can learn a secure encryption scheme. However, it also shows that, without a stronger adversary, it is more likely to obtain an insecure one. PMID:29695066

Learning Perfectly Secure Cryptography to Protect Communications with Adversarial Neural Cryptography.

PubMed

Coutinho, Murilo; de Oliveira Albuquerque, Robson; Borges, Fábio; García Villalba, Luis Javier; Kim, Tai-Hoon

2018-04-24

Researches in Artificial Intelligence (AI) have achieved many important breakthroughs, especially in recent years. In some cases, AI learns alone from scratch and performs human tasks faster and better than humans. With the recent advances in AI, it is natural to wonder whether Artificial Neural Networks will be used to successfully create or break cryptographic algorithms. Bibliographic review shows the main approach to this problem have been addressed throughout complex Neural Networks, but without understanding or proving the security of the generated model. This paper presents an analysis of the security of cryptographic algorithms generated by a new technique called Adversarial Neural Cryptography (ANC). Using the proposed network, we show limitations and directions to improve the current approach of ANC. Training the proposed Artificial Neural Network with the improved model of ANC, we show that artificially intelligent agents can learn the unbreakable One-Time Pad (OTP) algorithm, without human knowledge, to communicate securely through an insecure communication channel. This paper shows in which conditions an AI agent can learn a secure encryption scheme. However, it also shows that, without a stronger adversary, it is more likely to obtain an insecure one.

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.

Wireless structural monitoring for homeland security applications

NASA Astrophysics Data System (ADS)

Kiremidjian, Garo K.; Kiremidjian, Anne S.; Lynch, Jerome P.

2004-07-01

This paper addresses the development of a robust, low-cost, low power, and high performance autonomous wireless monitoring system for civil assets such as large facilities, new construction, bridges, dams, commercial buildings, etc. The role of the system is to identify the onset, development, location and severity of structural vulnerability and damage. The proposed system represents an enabling infrastructure for addressing structural vulnerabilities specifically associated with homeland security. The system concept is based on dense networks of "intelligent" wireless sensing units. The fundamental properties of a wireless sensing unit include: (a) interfaces to multiple sensors for measuring structural and environmental data (such as acceleration, displacements, pressure, strain, material degradation, temperature, gas agents, biological agents, humidity, corrosion, etc.); (b) processing of sensor data with embedded algorithms for assessing damage and environmental conditions; (c) peer-to-peer wireless communications for information exchange among units(thus enabling joint "intelligent" processing coordination) and storage of data and processed information in servers for information fusion; (d) ultra low power operation; (e) cost-effectiveness and compact size through the use of low-cost small-size off-the-shelf components. An integral component of the overall system concept is a decision support environment for interpretation and dissemination of information to various decision makers.

Hydrophilic MoSe2 Nanosheets as Effective Photothermal Therapy Agents and Their Application in Smart Devices.

PubMed

Lei, Zhouyue; Zhu, Wencheng; Xu, Shengjie; Ding, Jian; Wan, Jiaxun; Wu, Peiyi

2016-08-17

A facile poly(vinylpyrrolidone) (PVP)-assisted exfoliation method is utilized to simultaneously exfoliate and noncovalently modify MoSe2 nanosheets. The resultant hydrophilic nanosheets are shown to be promising candidates for biocompatible photothermal therapy (PTT) agents, and they could also be encapsulated into a hydrogel matrix for some intelligent devices. This work not only provides novel insights into exfoliation and modification of transition metal dichalcogenide (TMD) nanosheets but also might spark more research into engineering multifunctional TMD-related nanocomposites, which is in favor of further exploiting the attractive properties of these emerging layered two-dimensional (2D) nanomaterials.

Fuzzy-based decision strategy in real-time strategic games

NASA Astrophysics Data System (ADS)

Volna, Eva

2017-11-01

The aim of this article is to describe our own gaming artificial intelligence for OpenTTD, which is a real-time building strategy game. A multi-agent system with fuzzy decision-making was used for the proposal itself. The multiagent system was chosen because real-time strategy games achieve great complexity and require decomposition of the problem into individual problems, which are then solved by individual cooperating agents. The system becomes then more stable and easily expandable. The fuzzy approach makes the decision-making process of strategies easier thanks to the use of uncertainty. In the conclusion, own experimental results were compared with other approaches.

Cooperating systems: Layered MAS

NASA Technical Reports Server (NTRS)

Rochowiak, Daniel

1990-01-01

Distributed intelligent systems can be distinguished by the models that they use. The model developed focuses on layered multiagent system conceived of as a bureaucracy in which a distributed data base serves as a central means of communication. The various generic bureaus of such a system is described and a basic vocabulary for such systems is presented. In presenting the bureaus and vocabularies, special attention is given to the sorts of reasonings that are appropriate. A bureaucratic model has a hierarchy of master system and work group that organizes E agents and B agents. The master system provides the administrative services and support facilities for the work groups.

Mobile agent location in distributed environments

NASA Astrophysics Data System (ADS)

Fountoukis, S. G.; Argyropoulos, I. P.

2012-12-01

An agent is a small program acting on behalf of a user or an application which plays the role of a user. Artificial intelligence can be encapsulated in agents so that they can be capable of both behaving autonomously and showing an elementary decision ability regarding movement and some specific actions. Therefore they are often called autonomous mobile agents. In a distributed system, they can move themselves from one processing node to another through the interconnecting network infrastructure. Their purpose is to collect useful information and to carry it back to their user. Also, agents are used to start, monitor and stop processes running on the individual interconnected processing nodes of computer cluster systems. An agent has a unique id to discriminate itself from other agents and a current position. The position can be expressed as the address of the processing node which currently hosts the agent. Very often, it is necessary for a user, a processing node or another agent to know the current position of an agent in a distributed system. Several procedures and algorithms have been proposed for the purpose of position location of mobile agents. The most basic of all employs a fixed computing node, which acts as agent position repository, receiving messages from all the moving agents and keeping records of their current positions. The fixed node, responds to position queries and informs users, other nodes and other agents about the position of an agent. Herein, a model is proposed that considers pairs and triples of agents instead of single ones. A location method, which is investigated in this paper, attempts to exploit this model.

Dynamic electronic institutions in agent oriented cloud robotic systems.

PubMed

Nagrath, Vineet; Morel, Olivier; Malik, Aamir; Saad, Naufal; Meriaudeau, Fabrice

2015-01-01

The dot-com bubble bursted in the year 2000 followed by a swift movement towards resource virtualization and cloud computing business model. Cloud computing emerged not as new form of computing or network technology but a mere remoulding of existing technologies to suit a new business model. Cloud robotics is understood as adaptation of cloud computing ideas for robotic applications. Current efforts in cloud robotics stress upon developing robots that utilize computing and service infrastructure of the cloud, without debating on the underlying business model. HTM5 is an OMG's MDA based Meta-model for agent oriented development of cloud robotic systems. The trade-view of HTM5 promotes peer-to-peer trade amongst software agents. HTM5 agents represent various cloud entities and implement their business logic on cloud interactions. Trade in a peer-to-peer cloud robotic system is based on relationships and contracts amongst several agent subsets. Electronic Institutions are associations of heterogeneous intelligent agents which interact with each other following predefined norms. In Dynamic Electronic Institutions, the process of formation, reformation and dissolution of institutions is automated leading to run time adaptations in groups of agents. DEIs in agent oriented cloud robotic ecosystems bring order and group intellect. This article presents DEI implementations through HTM5 methodology.

Intelligent layered nanoflare: "lab-on-a-nanoparticle" for multiple DNA logic gate operations and efficient intracellular delivery.

PubMed

Yang, Bin; Zhang, Xiao-Bing; Kang, Li-Ping; Huang, Zhi-Mei; Shen, Guo-Li; Yu, Ru-Qin; Tan, Weihong

2014-08-07

DNA strand displacement cascades have been engineered to construct various fascinating DNA circuits. However, biological applications are limited by the insufficient cellular internalization of naked DNA structures, as well as the separated multicomponent feature. In this work, these problems are addressed by the development of a novel DNA nanodevice, termed intelligent layered nanoflare, which integrates DNA computing at the nanoscale, via the self-assembly of DNA flares on a single gold nanoparticle. As a "lab-on-a-nanoparticle", the intelligent layered nanoflare could be engineered to perform a variety of Boolean logic gate operations, including three basic logic gates, one three-input AND gate, and two complex logic operations, in a digital non-leaky way. In addition, the layered nanoflare can serve as a programmable strategy to sequentially tune the size of nanoparticles, as well as a new fingerprint spectrum technique for intelligent multiplex biosensing. More importantly, the nanoflare developed here can also act as a single entity for intracellular DNA logic gate delivery, without the need of commercial transfection agents or other auxiliary carriers. By incorporating DNA circuits on nanoparticles, the presented layered nanoflare will broaden the applications of DNA circuits in biological systems, and facilitate the development of DNA nanotechnology.

A Natural Component-Based Oxygen Indicator with In-Pack Activation for Intelligent Food Packaging.

PubMed

Won, Keehoon; Jang, Nan Young; Jeon, Junsu

2016-12-28

Intelligent food packaging can provide consumers with reliable and correct information on the quality and safety of packaged foods. One of the key constituents in intelligent packaging is a colorimetric oxygen indicator, which is widely used to detect oxygen gas involved in food spoilage by means of a color change. Traditional oxygen indicators consisting of redox dyes and strong reducing agents have two major problems: they must be manufactured and stored under anaerobic conditions because air depletes the reductant, and their components are synthetic and toxic. To address both of these serious problems, we have developed a natural component-based oxygen indicator characterized by in-pack activation. The conventional oxygen indicator composed of synthetic and artificial components was redesigned using naturally occurring compounds (laccase, guaiacol, and cysteine). These natural components were physically separated into two compartments by a fragile barrier. Only when the barrier was broken were all of the components mixed and the function as an oxygen indicator was begun (i.e., in-pack activation). Depending on the component concentrations, the natural component-based oxygen indicator exhibited different response times and color differences. The rate of the color change was proportional to the oxygen concentration. This novel colorimetric oxygen indicator will contribute greatly to intelligent packaging for healthier and safer foods.

Project X: competitive intelligence data mining and analysis

NASA Astrophysics Data System (ADS)

Gilmore, John F.; Pagels, Michael A.; Palk, Justin

2001-03-01

Competitive Intelligence (CI) is a systematic and ethical program for gathering and analyzing information about your competitors' activities and general business trends to further your own company's goals. CI allows companies to gather extensive information on their competitors and to analyze what the competition is doing in order to maintain or gain a competitive edge. In commercial business this potentially translates into millions of dollars in annual savings or losses. The Internet provides an overwhelming portal of information for CI analysis. The problem is how a company can automate the translation of voluminous information into valuable and actionable knowledge. This paper describes Project X, an agent-based data mining system specifically developed for extracting and analyzing competitive information from the Internet. Project X gathers CI information from a variety of sources including online newspapers, corporate websites, industry sector reporting sites, speech archiving sites, video news casts, stock news sites, weather sites, and rumor sites. It uses individual industry specific (e.g., pharmaceutical, financial, aerospace, etc.) commercial sector ontologies to form the knowledge filtering and discovery structures/content required to filter and identify valuable competitive knowledge. Project X is described in detail and an example competitive intelligence case is shown demonstrating the system's performance and utility for business intelligence.