Convergence and Knowledge Processing in Multi-Agent Systems - De Wilde, Philippe

. .

Résumé :
Agent systems are being used to model complex systems like societies, markets and biological systems. In this book we investigate issues of agent systems related to convergence and interactivity using techniques from agent based modelling to simulate complex systems, and demonstrate that interactivity/exchange and convergence in multi-agent systems are issues that are significantly interrelated. Topic and features: - Introduces the state of the art in multi-agent systems, with an emphasis on agent-based computational economics. - Sheds light on the fundamental concepts behind the stability of multi-agent systems. - Investigates knowledge exchange among agents, the rationale behind it and its effects on the ecosystem. - Explores how information provided through interaction with the system can be used to optimise its performance. - Describes a pricing strategy for a realistic large-scale distributed system. This book supplies a comprehensive resource and will be invaluable reading for researchers and postgraduates studying this topic.

Sommaire:
1. Introduction
1.1 Background to the research
1.2 Approach
1.3 Contributions
1.4 Reader's guide to the book 2. Research Issues
2.1 Multi-Agent Systems
2.2 Agent-Based Modelling
2.3 An Ecosystem Perspective of Multi-Agent Systems
2.4 Convergence Issues
2.5 Interaction and Knowledge Exchange 3. Stability of Multi-Agent Systems
3.1 Introduction
3.2 Background
3.3 Stability in Games
3.4 Experiments
3.5 Conclusion 4. The Emergence of Knowledge Exchange
4.1 Introduction
4.2 Digital Business Ecosystems
4.3 Background
4.4 An agent-based model of the DBE
4.5 Analysis of the model
4.6 Concluding remarks 5. Collaborative Query Expansion
5.1 Introduction
5.2 Term Value
5.3 Implementation
5.4 Evaluation
5.5 Introducing User Collaboration for Query Expansion
5.6 Limitations and Future Work
5.7 Conclusion 6. Micro-economic Control of Distributed Intelligent Personal Assistants
6.1 Stable Strategies
6.2 Network of Intelligent Personal Assistants
6.3 Finding a Stable Strategy
6.4 Conclusion 7. Conclusions and Future Work
7.1 Contributions
7.2 Future Directions
7.3 Concluding Remarks Appendices
A. The EEII project
B. Statistical Analysis
C. Methodology: Evolutionary Algorithms References