Architectural Design of Multi-Agent Systems: Technologies and Techniques

by Lin, Hong

• ISBN13: 9781599041087
• ISBN10: 1599041081
• Format: Hardcover
• Copyright: 2007-05-30
• Publisher: Igi Global

Summary

Agent-oriented design has become on of the most active areas in the field of software engineering. Although great advances have been made in the study of the architectural design of agent systems, the complexity and multi-disciplinary approaches of this constantly growing field are currently of a premature nature compared to where they should be.Architectural Design of Multi-Agent Systems: Technologies and Techniques provides a compilation of advanced research results focusing on architecture and modeling issues of multi-agent systems. This study serves as a reference for further research on system models, architectural design languages, formal methods and reasoning, module interface design, and design issues. Architectural Design of Multi-Agent Systems: Technologies and Techniques presents high-level issues such as: modeling agent systems in cognitive sciences, knowledge management, in-depth exposure of agent theory, and state-of-the-art research on design quality of agent systems.

Table of Contents

Towards agent-oriented conceptualization and implementation	p. 1
Concurrent programming with multi-agents and the chemical abstract machine	p. 26
Coalition formation among agents in complex problems based on a combinatorial auction perspective	p. 48
A gentle introduction to fuzzy logic and its applications to intelligent agents design	p. 61
Component agent systems : building a mobile agent architecture that you can reuse	p. 95
Designing a foundation for mobile agents in peer-to-peer networks	p. 115
Dynamic scheduling of multi-agent in agent-based distributed network management	p. 125
Scalable fault tolerant agent grooming environment (SAGE)	p. 143
Toward agent-based grid computing	p. 173
MAITS : a multi-agent-based IT security approach	p. 189
A methodology for modeling expert knowledge for development of agent-based systems	p. 210
Three perspectives on multi-agent reinforcement learning	p. 234
Modeling knowledge and reasoning in conversational recommendation agents	p. 247
Task allocation in case-based recommender systems : a swarm intelligence approach	p. 268
A multi-agent system for optimal supply chain management	p. 281
Macroscopic modeling of information flow in an agent-based electronic health record system	p. 305
Robust intelligent control of mobile robots	p. 335
RiskMan : a multi-agent system for risk management	p. 356
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