Machine Learning for Agents and Multi-Agent Systems

Machine Learning for Agents and Multi-Agent Systems

Daniel Kudenko (University of York, UK), Dimitar Kazakov (University of York, UK) and Eduardo Alonso (City University, UK)
Copyright: © 2003 |Pages: 26
DOI: 10.4018/978-1-59140-046-2.ch001
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In order to be truly autonomous, agents need the ability to learn from and adapt to the environment and other agents. This chapter introduces key concepts of machine learning and how they apply to agent and multi-agent systems. Rather than present a comprehensive survey, we discuss a number of issues that we believe are important in the design of learning agents and multi-agent systems. Specifically, we focus on the challenges involved in adapting (originally disembodied) machine learning techniques to situated agents, the relationship between learning and communication, learning to collaborate and compete, learning of roles, evolution and natural selection, and distributed learning. In the second part of the chapter, we focus on some practicalities and present two case studies.

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Table of Contents
Valentina Plekhanova
Valentina Plekhanova
Chapter 1
Daniel Kudenko, Dimitar Kazakov, Eduardo Alonso
In order to be truly autonomous, agents need the ability to learn from and adapt to the environment and other agents. This chapter introduces key... Sample PDF
Machine Learning for Agents and Multi-Agent Systems
Chapter 2
Darryl N. Davis
In this chapter, research into the nature of drives and motivations in computational agents is visited from a perspective drawing on artificial life... Sample PDF
Architectures for Cognitive and A-Life Agents
Chapter 3
Luc Moreau, Norliza Zaini, Don Cruickshank, David De Roure
SoFAR, the Southampton Framework for Agent Research, is a versatile multiagent framework designed for Distributed Information Management tasks.... Sample PDF
SoFAR: An Agent Framework for Distributed Information Management
Chapter 4
P. Kefalas, M. Holcombe, G. Eleftherakis, M. Gheorghe
Recent advances in testing and verification of software based on formal specifications of the system to be built have reached a point where the... Sample PDF
A Formal Method for the Development of Agent-Based Systems
Chapter 5
Penny Baillie, Mark Toleman, Dickson Lukose
Interacting with intelligence in an ever-changing environment calls for exceptional performances from artificial beings. One mechanism explored to... Sample PDF
Engineering Emotionally Intelligent Agents
Chapter 6
Robert E. Smith, Claudio Bonacina
In the multi-agent system (MAS) context, the theories and practices of evolutionary computation (EC) have new implications, particularly with regard... Sample PDF
Evolutionary Computation as a Paradigm for Engineering Emergent Behaviour in Multi-Agent Systems
Chapter 7
Luis Brito, Paulo Novais, Jose Neves
The use of agents in Electronic Commerce environments leads to the necessity to introduce some formal analysis and definitions. A four-step method... Sample PDF
The Logic Behind Negotiation: From Pre-Argument Reasoning to Argument-Based Negotiation
Chapter 8
J. Debenham, B. Henderson-Sellers
Originally a development methodology targeted at object technology, the OPEN Process Framework (OPF) is found to be a successful basis for... Sample PDF
Designing Agent-Based Process Systems-Extending the OPEN Process Framework
Chapter 9
Virginia Dignum, Hans Weigand
In this chapter, we present a framework for the design of agent societies that considers the influence of social organizational aspects on the... Sample PDF
Toward an Organization-Oriented Design Methodology for Agent Societies
Chapter 10
Ricardo Aler, David Camacho, Alfredo Moscardini
In this paper, we present a multiagent system approach with the purpose of building computer programs. Each agent in the multiagent system will be... Sample PDF
Cooperation Between Agents to Evolve Complete Programs
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