Agent-based hybrid intelligent systems : an agent-based fromework for complex problem solving /

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Bibliographic Details
Author / Creator:Zhang, Zili (Senior lecturer)
Imprint:Berlin ; New York : Springer, ©2004.
Description:1 online resource (xiv, 196 pages) : illustrations.
Language:English
Series:Lecture notes in computer science, 0302-9743 ; 2938. Lecture notes in artificial intelligence
Lecture notes in computer science ; 2938.
Lecture notes in computer science. Lecture notes in artificial intelligence.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11065242
Hidden Bibliographic Details
Other authors / contributors:Zhang, Chengqi, 1957-
ISBN:3540246231
9783540246237
1280306785
9781280306785
3540209085
9783540209089
Digital file characteristics:text file PDF
Notes:Includes bibliographical references (pages 183-191) and index.
English.
Summary: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.
Other form:Print version: Zhang, Zili, Ph. D. Agent-based hybrid intelligent systems. Berlin ; New York : Springer, ©2004 3540209085
Standard no.:10.1007/b95170

MARC

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245 1 0 |a Agent-based hybrid intelligent systems :  |b an agent-based fromework for complex problem solving /  |c Zili Zhang, Chengqi Zhang. 
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520 |a 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. 
505 0 |a 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. 
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