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Cooperative Mobile Robotics
Cooperative Mobile Robotics

... other resources, and may be accompanied by studies of related issues such as correctness and fault-tolerance.1 Finally, definition (c) reflects a concern with quantified measures of cooperation, such as speedup in time to complete a task. Thus, in these definitions we see three fundamental seeds: th ...
Creativity, Cognitive Mechanisms, and Logic
Creativity, Cognitive Mechanisms, and Logic

... systems that are of practical use in application domains. Whereas in the beginnings of AI as a scientific discipline the focus was mainly based on higher cognitive abilities, like reasoning, solving puzzles, playing chess, or proving mathematical statements, this has been changed during the last dec ...
Author template for journal articles
Author template for journal articles

... explicit and definitive representation which it could manipulate in the manner of an imperative program, for example to plan or define an intention as a rule-based calculus. It is these interactions which enable it simply to ”survive” by preserving sensorimotor invariants. 2- Plasticity: The organis ...
Matching Conflicts:  Functional Validation  of  Agents
Matching Conflicts: Functional Validation of Agents

... computational grids, such as Globus (Foster and Kesselman 1998), Sciagents (Drashansky, Joshi and Rice, and 1995), Infospheres (see http://www.infospheres. caitech.edu/). Such "grids" will be populated by server agents and services that are available to user-defined simulations and applications (Kot ...
The theory of social functions
The theory of social functions

... hand’, of the ‘spontaneous social order’ but also of ‘social functions’) — will eventually be clarified thanks to the contribution of AI (and, in particular, of cognitive Agent modelling, learning, and MAS) and its entering the social simulation domain. After introducing Multi-Agent-Based Social Sim ...
Towards a Logic of Rational Agency
Towards a Logic of Rational Agency

... Rational agents are the central objects of study in many research disciplines, including economics [52], philosophy [17], cognitive science [73], and most recently, computer science and artificial intelligence [79]. Put crudely, an agent is an entity that is situated in some environment and is capab ...
Towards a Logic of Rational Agency
Towards a Logic of Rational Agency

... Rational agents are the central objects of study in many research disciplines, including economics [52], philosophy [17], cognitive science [73], and most recently, computer science and artificial intelligence [79]. Put crudely, an agent is an entity that is situated in some environment and is capab ...
- WestminsterResearch
- WestminsterResearch

... with open innovation strategies, processes and diffusion is proposed and discussed in this paper. In order to deal with the various facets or properties of the open innovation problem, we recommend and present a new paradigm and framework for integrating the strengths or advantages of intelligent so ...
Liability for Distributed Artificial Intelligences
Liability for Distributed Artificial Intelligences

... professions and personal work increasingly depend on the processing of computer data. The power of the digital machine allows an exponential increase in complexity, which in turn requires increasing computer power and in any event makes it impossible to turn back to manual processing.' The notion of ...
Searching Social Networks
Searching Social Networks

... finding the right people whom we may ask a specific question and who will answer that question for us. The right people are those who have the desired information or expertise. Finding them involves naturally depends on our social network: our friends, our friends’ friends, and so on. Clearly, build ...
The MADP Toolbox 0.3
The MADP Toolbox 0.3

... and includes several example applications using the provided functionality. For instance, applications that use JESP or brute-force search to solve problems (specified as .dpomdp files) for a particular planning horizon. In this way, Dec-POMDPs can be solved directly from the command line. Furthermo ...
An Oz-Centric Review of Interactive Drama and
An Oz-Centric Review of Interactive Drama and

... For many people, the phrase believable agent conjures up some notion of an agent that tells the truth, or an agent you can trust. But this is not what is meant at all. Believable is a term coming from the character arts. A believable character is one who seems lifelike, whose actions make sense, who ...
Paper - Christian Muise
Paper - Christian Muise

... intuition to complete goals in unplanned ways. Even without humans, the first-person perspective may be required; for example, if communication becomes unavailable but agents must continue operating. We therefore must consider computing conditional plans in settings where the environment is collabor ...
Rollout Sampling Policy Iteration for Decentralized POMDPs
Rollout Sampling Policy Iteration for Decentralized POMDPs

... own local observations when executing the policy. Therefore the policy must be completely decentralized, which means the policy of an agent must be guided by its own local observation history only. It is not clear how to maintain a sufficient statistic, such as a belief state in POMDPs, based only o ...
COSC343: Artificial Intelligence
COSC343: Artificial Intelligence

... Well-formed and ill-formed sentences Hierarchical structure in sentences Phrase structure grammars: how you can use them to build parse trees for sentences Agreement (between subjects and verbs; between determiners and nouns) Grammars using variables to capture agreement constraints Parsing as a kin ...
The Dynamical Hypothesis in Cognitive Science: A review essay of
The Dynamical Hypothesis in Cognitive Science: A review essay of

... intelligence for 25 years. We disagree. First, as pointed out by the authors themselves, the use of dynamics as a framework to comprehend the brain and cognition is not new. In the early 1950’s, for example, W. Ross Ashby wrote a wonderful little treatise called Design for a Brain (1952) based on th ...
Reasoning about Action and Cooperation
Reasoning about Action and Cooperation

... by a transition labeled with an action a, this means that s0 is a possible result of executing action a in state s. The sets of variables at each end of the transition tell us how the performance of the action changes the state of the environment, in terms of the propositions that change value. One ...
A Client-Server Interactive Tool for Integrated
A Client-Server Interactive Tool for Integrated

... taught methods of internally representing information about the external world. They also learn methods for problem solving by searching through large spaces containing possible environment states, and for generating plans to achieve desired goals. Natural language processing, uncertainty reasoning, ...
AAAI Proceedings Template - R3-COP
AAAI Proceedings Template - R3-COP

Get PDF - IOS Press
Get PDF - IOS Press

... think it is worth to them), removing any need for additional reasoning about its worth to others. Market simulations and economics can also be used to distribute large quantities of resources among agents [69,73,74]. For example, in [8] it is shown how costs and money are turned into a coordination ...
The Model-based Approach to Autonomous Behavior: A
The Model-based Approach to Autonomous Behavior: A

... locations, and the grid move between locations. This abstraction, however, is not adequate when the table has no space for all the blocks, or when the gripper cannot get past towers of a certain height. The open question is how to automatically compile detailed planning description into more abstrac ...
The challenge of complexity for cognitive systems
The challenge of complexity for cognitive systems

... In the context of AI planning, the complexity of the environment is typically characterized by the following dimensions (Ghallab, Nau, & Traverso, 2004, chap. 1.6): The number of states might be infinite, due to actions which can create new objects or due to numerical variables. States might be only ...
Blackwell Guide to the Philosophy of Computing and
Blackwell Guide to the Philosophy of Computing and

... phenomena. The simplest example of such a system is the so-called “game of life” devised by the mathematician John Conway (Berlekamp 1982) in the 1960s. Conway’s game of life can be thought of as a model at the physical or chemical level, embodying an extremely simple and unique form of “chemical” i ...
- University of Huddersfield Repository
- University of Huddersfield Repository

Decision-Theoretic Planning for Multi
Decision-Theoretic Planning for Multi

... 1. Guess a joint policy and write it down in exponential time. This is possible, because a joint policy consists of n mappings from observation histories to actions. Since h ≤ |S|, the number of possible histories is exponentially bounded by the problem description. 2. The DEC-POMDP together with th ...
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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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