Agent-Based Hybrid Intelligent Systems : An Agent-Based Framework for Complex Problem Solving

Chengqi Zhang

ISBN 10: 3540209085 / ISBN 13: 9783540209089

Editore: Springer Berlin Heidelberg, 2004

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Druck auf Anfrage Neuware - Printed after ordering - Solving complex problems in real-world contexts, such as financial investment planning or mining large data collections, involves many different sub-tasks, each of which requires different techniques. To deal with such problems, a great diversity of intelligent techniques are available, including traditional techniques like expert systems approaches and soft computing techniques like fuzzy logic, neural networks, or genetic algorithms. These techniques are complementary approaches to intelligent information processing rather than competing ones, and thus better results in problem solving are achieved when these techniques are combined in hybrid intelligent systems. Multi-Agent Systems are ideally suited to model the manifold interactions among the many different components of hybrid intelligent systems.This book introduces agent-based hybrid intelligent systems and presents a framework and methodology allowing for the development of such systems for real-world applications. The authors focus on applications in financial investment planning and data mining.

Codice articolo 9783540209089

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• Titolo: Agent-Based Hybrid Intelligent Systems : An Agent-Based Framework for Complex Problem Solving
• Editore: Springer Berlin Heidelberg
• Data di pubblicazione: 2004
• Lingua: Inglese
• ISBN 10: 3540209085
• ISBN 13: 9783540209089
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 12 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 12 millimetri di profondità
• Peso: 335 grammi

Descrizione articolo

Riassunto

Solving complex problems in real-world contexts, such as financial investment planning or mining large data collections, involves many different sub-tasks, each of which requires different techniques. To deal with such problems, a great diversity of intelligent techniques are available, including traditional techniques like expert systems approaches and soft computing techniques like fuzzy logic, neural networks, or genetic algorithms. These techniques are complementary approaches to intelligent information processing rather than competing ones, and thus better results in problem solving are achieved when these techniques are combined in hybrid intelligent systems. Multi-Agent Systems are ideally suited to model the manifold interactions among the many different components of hybrid intelligent systems.

This book introduces agent-based hybrid intelligent systems and presents a framework and methodology allowing for the development of such systems for real-world applications. The authors focus on applications in financial investment planning and data mining.

Contenuti

Fundamentals of Hybrid Intelligent Systems and Agents.- 1 Introduction.- 2 Basics of Hybrid Intelligent Systems.- 3 Basics of Agents and Multi-agent Systems.- Methodology and Framework.- 4 Agent-Oriented Methodologies.- 5 Agent-Based Framework for Hybrid Intelligent Systems.- 6 Matchmaking in Middle Agents.- Application Systems.- 7 Agent-Based Hybrid Intelligent System for Financial Investment Planning.- 8 Agent-Based Hybrid Intelligent System for Data Mining.- Concluding Remarks.- 9 The Less the More.- Appendix: Sample Source Codes of the Agent-Based Financial Planning System.- References.