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Multi-Agent Malicious Behaviour Detection
Multi-Agent Malicious Behaviour Detection

The Role of Subjectivity in Intelligent Systems Communication and
The Role of Subjectivity in Intelligent Systems Communication and

... In activity theory perspective agency is a negotiated relationship between the subject and the tools used by a subject to perform activities in a determinate context (Bernat 2011). Seen from the activity theory perspective Agency is in fact liable to change in response to new contextual development ...
Eliciting Single-Peaked Preferences Using Comparison Queries
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... Rather, the agents’ preferences, or at least the relevant parts thereof, need to be elicited. This is done by asking the agents a (hopefully small) number of simple queries about their preferences, such as comparison queries, which ask an agent to compare two of the alternatives. Prior work on prefe ...
Towards Smart User Models for Open Environments
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... to re-use user models acquired from a domain to another one. For example, if it is learn that the user prefers comfortable restaurants, it is quite hard to take advantages of such information in order to recommend to the user comfortable cinemas. Second, the influence that the context has in the use ...
PhD Thesis
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... (iii) that EPCs may reproduce stereotypes from everyday real life human-human interaction, as well as from traditional visual media – but that they simultaneously harbour a considerable potential to challenge stereotypes. As a tool for the research community, a framework of a visual graphical design ...
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...  Does this mean that the internal mechanisms are complex as well?  No, path results from the interaction between the ant and the beach  Internal mechanisms are simple ...
Multiagent Systems : A Modern Approach to Distributed Artificial
Multiagent Systems : A Modern Approach to Distributed Artificial

... needed is a book that offers a comprehensive and up-to-date introduction and is suitable as a textbook for the field. The purpose of this volume is to fulfill this need. Features — The book offers a number of features that make it especially useful to readers: ...
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Cooperative Heuristic Search with Software Agents - Aalto

... complex systems and processes in the natural world, and yet our computations must fit this parallel model of independence or minimized communication. It is true that at the hardware level instruction execution is linearized per functional unit, but at the same time more and more of these independent ...
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Artificial Societies of Intelligent Agents

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Software Performance Estimation Methods for System

... Embedded systems are ubiquitous in our everyday lives, spanning all aspects of modern life. They appear in small portable devices, such as MP3 players and cell phones, and also in large machines, such as cars, aircrafts and medical equipments. Driven by market needs, the demand for new features in e ...
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Chapter 1 THE INFORMATION AGE IN WHICH YOU LIVE …

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Pdf - Text of NPTEL IIT Video Lectures

... Then, if you look at the aspect of determinism again environments can be divided into two or three types. Deterministic environments: In deterministic environments the next state of the environment is completely described by the current state and the agent’s action. When we looked at diagram of agen ...
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CptS 440 / 540 Artificial Intelligence
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... Why Study AI? • AI makes computers more useful • Intelligent computer would have huge impact on civilization • AI cited as “field I would most like to be in” by scientists in all fields • Computer is a good metaphor for talking and thinking about intelligence ...
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... itself as a viable methodology for synthesizing and understanding cognition (e.g. Pfeifer & Bongard 2007; Pfeifer & Scheier 1999). Furthermore, embodied AI is now widely considered to avoid or successfully address many of the fundamental problems encountered by traditional “Good Old-Fashioned AI” (H ...
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... AI discovers computational complexity Neural network research almost disappears Early development of knowledge-based systems AI becomes an industry Neural networks return to popularity AI becomes a science The emergence of intelligent agents CS 331: Dr M M Awais (LUMS) ...
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types of anticipatory behaving agents in artificial life

... The first example is taken from work (Nadin 2003). Change in posture (standing up from a seated position for example) would cause changes in blood pressure. This is the physics of the body consisting from a liquid (blood), pipes (the various blood vessels), and a pump (the heart). We can understand ...
Automated Negotiations Among Autonomous Agents
Automated Negotiations Among Autonomous Agents

pre-print - School of Computer Science, University of Birmingham.
pre-print - School of Computer Science, University of Birmingham.

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... clasp is an answer set solver for (extended) normal logic programs. It combines the high-level modeling capacities of answer set programming (ASP) with state-of-the-art techniques from the area of Boolean constraint solving. The primary clasp algorithm relies on conflict-driven nogood learning, a te ...
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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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