Agent-Based Hybrid Intelligent Systems: An Agent-Based Framework for Complex Problem Solving / Edition 1

by Zili Zhang, Chengqi Zhang

Overview

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.

Product Details

ISBN-13:	9783540209089
Publisher:	Springer Berlin Heidelberg
Publication date:	03/19/2004
Series:	Lecture Notes in Computer Science , #2938
Edition description:	2004
Pages:	194
Product dimensions:	6.10(w) x 9.17(h) x 0.36(d)

Table of Contents

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.