Agent-Based Hybrid Intelligent Systems : An Agent-Based Framework for Complex Problem Solving / edited by Zili Zhang, Chengqi Zhang.

Format:

Book

Contributor:

Zhang, Zili (Senior lecturer), editor.

Zhang, Chengqi, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 2938.

Lecture Notes in Artificial Intelligence ; 2938

Language:

English

Subjects (All):

Artificial intelligence.

Software engineering.

Computers.

Database management.

Application software.

Artificial Intelligence.

Software Engineering.

Computation by Abstract Devices.

Database Management.

Computer Appl. in Administrative Data Processing.

Local Subjects:

Artificial Intelligence.

Software Engineering.

Computation by Abstract Devices.

Database Management.

Computer Appl. in Administrative Data Processing.

Physical Description:

1 online resource (XV, 194 pages).

Edition:

First edition 2004.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2004.

System Details:

text file PDF

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.

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.

Other Format:

Printed edition:

ISBN:

978-3-540-24623-7

9783540246237

Access Restriction:

Restricted for use by site license.