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Agents271-sq2010
Agents271-sq2010

... (all-knowing with infinite knowledge) • Agents can perform actions in order to modify future percepts so as to obtain useful information (information gathering, exploration) • An agent is autonomous if its behavior is determined by its own percepts & experience (with ability to learn and adapt) with ...
myworld: an agent-oriented testbed for distributed artificial intelligence
myworld: an agent-oriented testbed for distributed artificial intelligence

... e-mail: mikew@sun.com.mmu.ac.uk, tel: (+44 61) 247 1531, fax: (+44 61) 247 1483. ...
Problem - Cognitive Tutor Authoring Tools
Problem - Cognitive Tutor Authoring Tools

... The first step in building a cognitive model is to understand what the task is that the humans are trying to solve. The Cognitive Task Analysis methodology is a useful place to start. In order to do the task analysis we need an interface in which the human can perform the task. Though cognitive task ...
Intelligent Agents - University of Washington
Intelligent Agents - University of Washington

... Environment types • There are different ways to characterize what an agents environment will consist of. • These “constraints” significantly effect how we implement an agent (i.e., we are being fairly abstract on purpose right now). • In future chapters, we will see how different environment types ...
Distributed case-based reasoning
Distributed case-based reasoning

... cooperative agents whereby individual agents are responsible for a particular sub-part of the design task. Agents cooperate to resolve design conflicts as each new design is constructed from the contribution of the distributed agents. However, the negotiated retrieval approach assumes that groups of ...
Cognitive Medical Multiagent Systems
Cognitive Medical Multiagent Systems

... elaborated by physicians (an agent may help a human medical specialist in medical decisions elaborations, also he may verify medical hypothesis elaborated by the human medical specialists) and may improve the solving of medical tasks that must be fulfilled in healthcare processes. As examples of app ...
Policy Communication for Coordination with Unknown Teammates
Policy Communication for Coordination with Unknown Teammates

... limited to sharing observations or direct state information (Roth, Simmons, and Veloso 2007). As agents in such systems have complete information regarding the planning capacities of their teammates, they can simply use the shared information to compute precisely how all agents will act. Since the p ...
From Reaction To Cognition: 5th European Workshop On Modelling
From Reaction To Cognition: 5th European Workshop On Modelling

... A. Cerri, S., Gouard res, G., & Paragua u, F Jul 23, 2015 Biswas, G., Bull, S., Kay, J., & Mitrovic, A. (2011). Artificial Intelligence in Education: 15th International Conference, AIED 2011, Auckland, New Zealand Imitation and Social Learning in Robots, Humans In C. L. Nehaniv (ed.), Computation fo ...
Congregating and Market Formation.
Congregating and Market Formation.

... Our past research (e.g. [4, 5]) has focused on how producers in an information economy can locate consumer niches and efficiently learn the preferences of consumers in these niches. It is this first problem, that of locating a niche, that is most relevant to congregating. In this problem, two or mor ...
Reports of the AAAI 2010 Conference Workshops
Reports of the AAAI 2010 Conference Workshops

... from one field to problems from the other, and to identify the key issues to be addressed in increasing the convergence between security and AI. This is a fertile area for research, and has been attracting an increasing amount of interest in both communities. Prior to this workshop there was a 2009 ...
CAD/CAPP/CAM INTEGRATION METHODOLOGY FOR THE
CAD/CAPP/CAM INTEGRATION METHODOLOGY FOR THE

The Liability Problem for Autonomous Artificial Agents
The Liability Problem for Autonomous Artificial Agents

... innovation coming from the hacking, open-source and DIY communities. The hacking, open-source and DIY communities, while a powerful source of innovation, will have limited means of compensating those who might be harmed from their products—not just those who chose to use them. Strict liability goes ...
IOSR Journal of Computer Engineering (IOSR-JCE)
IOSR Journal of Computer Engineering (IOSR-JCE)

... Fig. 3. Observation Result of hidden markov model 4.2 Add the Fuzzy Rules to Making Appropriate Angle for Avoiding Obstacle The agent encompasses a detector which will notice the gap from objects. Detector knowledge provides the indication of a distance from associate degree object, we are able to a ...
Intelligent Multimedia-A New Computing
Intelligent Multimedia-A New Computing

... Intelligent syntax languages are defined and their linguistics parsing theories outlined. A computational logic for intelligent languages is presented in brief with a soundness and completeness theorem. A brief overview to context abstraction shows how context free and context sensitive properties m ...
Autonomous Intelligent Agents in Cyber Offence
Autonomous Intelligent Agents in Cyber Offence

... rapid, especially in the technological arena, and artificial intelligence (AI) techniques are more and more at the heart of applications. The concept of agents has been known for some time and software with some agent characteristics is already present and deployed, but in the near future we will pr ...
3 Experiments
3 Experiments

... Each agent is generally inclined to move to occupy a role that is higher than its current role. It will improve its capabilities to qualify for the next higher role. Naturally, at some point in time all agents will qualify for the highest ranked role. Agents will not move up in ranks unless there th ...
Intelligent Agents
Intelligent Agents

... Utility-based Agents (2) • Add utility evaluation: not only how close does the action take me to the goal, but also how useful it is for the agent • Note: both goal and utility-based agents can plan with constructs other than rules • Other aspects to be considered: – uncertainty in perceptions and ...
Spring-99 Registration
Spring-99 Registration

... The symposium will consist of one or two invited talks, followed by short presentations and longer discussions, in an atmosphere that encourages the interaction of researchers with different back grounds. Further detailed information will be posted at www.isi.edu/ isd/zhang/SearchStrategies.html ...
Autonomous Intelligent Agents in Cyber Offence
Autonomous Intelligent Agents in Cyber Offence

... rapid, especially in the technological arena, and artificial intelligence (AI) techniques are more and more at the heart of applications. The concept of agents has been known for some time and software with some agent characteristics is already present and deployed, but in the near future we will pr ...
MCS 8100/CSC 2114 : Artificial Intelligence
MCS 8100/CSC 2114 : Artificial Intelligence

... - Programs that behave (externally) like humans • Computational models of human thought processes ? ...
Artificial Intelligence and Economic Theory
Artificial Intelligence and Economic Theory

... the relations between opportunity sets of individual agents and market outcomes. This points to the second important problem concerning economic models: the modeling of the agents' perceived opportunities, without turning economics into a psychology of perception. Basically, the problem is that econ ...
Multi-agent MDP and POMDP Models for Coordination
Multi-agent MDP and POMDP Models for Coordination

... Nair, R., Roth, M., Yokoo, M., Tambe, M. Communication for improving policy computation in distributed POMDPs. To appear in Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, 2004. ...
EVOLUTIONARY AUTONOMOUS AGENTS: A NEUROSCIENCE
EVOLUTIONARY AUTONOMOUS AGENTS: A NEUROSCIENCE

... can emerge in EAA models even when they are not modelled explicitly. The model of REF. 5 (described above) shows this potential, in which the agents’ emergent controller networks are analysed using conventional neuroscience methods of lesioning and receptive-field measurements. This analysis reveals ...
Learning from Observations
Learning from Observations

... – They’re navigati onal robots - i.e. they move around in t heir environment. (As contrasted w ith e.g. w ith manipulatory robots.) – They are tu rtles: they have a chassis w ith tw o separately controllable w heels at the front, and a pivot w heel at the back. – They have a light sensor underneath, ...
Interest-Matching Comparisons Using CP-nets Andrew W. Wicker
Interest-Matching Comparisons Using CP-nets Andrew W. Wicker

... in the Social Sciences. MIT Press. Wicker, A. W. 2006. Interest-matching comparisons using CP-nets. Master’s thesis, Department of Computer Science, North Carolina State University. ...
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Agent-based model

An agent-based model (ABM) is one of a class of computational models for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) with a view to assessing their effects on the system as a whole. It combines elements of game theory, complex systems, emergence, computational sociology, multi-agent systems, and evolutionary programming. Monte Carlo Methods are used to introduce randomness. Particularly within ecology, ABMs are also called individual-based models (IBMs), and individuals within IBMs may be simpler than fully autonomous agents within ABMs. A review of recent literature on individual-based models, agent-based models, and multiagent systems shows that ABMs are used on non-computing related scientific domains including biology, ecology and social science. Agent-based modeling is related to, but distinct from, the concept of multi-agent systems or multi-agent simulation in that the goal of ABM is to search for explanatory insight into the collective behavior of agents obeying simple rules, typically in natural systems, rather than in designing agents or solving specific practical or engineering problems.Agent-based models are a kind of microscale model that simulate the simultaneous operations and interactions of multiple agents in an attempt to re-create and predict the appearance of complex phenomena. The process is one of emergence from the lower (micro) level of systems to a higher (macro) level. As such, a key notion is that simple behavioral rules generate complex behavior. This principle, known as K.I.S.S. (""Keep it simple, stupid"") is extensively adopted in the modeling community. Another central tenet is that the whole is greater than the sum of the parts. Individual agents are typically characterized as boundedly rational, presumed to be acting in what they perceive as their own interests, such as reproduction, economic benefit, or social status, using heuristics or simple decision-making rules. ABM agents may experience ""learning"", adaptation, and reproduction.Most agent-based models are composed of: (1) numerous agents specified at various scales (typically referred to as agent-granularity); (2) decision-making heuristics; (3) learning rules or adaptive processes; (4) an interaction topology; and (5) a non-agent environment. ABMs are typically implemented as computer simulations, either as custom software, or via ABM toolkits, and this software can be then used to test how changes in individual behaviors will affect the system's emerging overall behavior.
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