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Agent intelligence through data mining

Author: Andreas L Symeonidis; Pericles A Mitkas
Publisher: New York : Springer, 2005.
Series: Multiagent systems, artificial societies, and simulated organizations, 14.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
"This book offers a self-contained overview of a relatively young but important area of research: the intersection of agent technology and data mining. This intersection leads to considerable advancements in the area of information technologies, drawing the increasing attention of both research and industrial communities. It can take two forms: a)the use of data mining for smarter, more efficient agents. The second  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Symeonidis, Andreas L.
Agent intelligence through data mining.
New York : Springer, 2005
(DLC) 2005044155
(OCoLC)58919872
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Andreas L Symeonidis; Pericles A Mitkas
ISBN: 0387243526 9780387243528 0387257578 9780387257570 6610263388 9786610263387
OCLC Number: 63147750
Reproduction Notes: Electronic reproduction. [S.l.] : HathiTrust Digital Library, 2011. MiAaHDL
Description: 1 online resource (xxiii, 200 pages) : illustrations.
Details: Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.
Contents: Cover --
Table of Contents --
List of Figures --
List of Tables --
Foreword --
Preface --
Acknowledgments --
Part I Concepts and Techniques --
1. INTRODUCTION --
1 The Quest for Knowledge --
2 Problem Description --
3 Related Bibliography --
4 Scope of the Book --
5 Contents of the Book --
6 How to Read this Book --
2. DATA MINING AND KNOWLEDGE DISCOVERY: A BRIEF OVERVIEW --
1 History and Motivation --
2 Data Preprocessing --
3 Classification and Prediction --
4 Clustering --
5 Association Rule Extraction --
6 Evolutionary Data Mining Algorithms --
7 Chapter review --
3. INTELLIGENT AGENTS AND MULTI-AGENT SYSTEMS --
1 Intelligent Agents --
2 Multi-Agent Systems --
Part II Methodology --
4. EXPLOITING DATA MINING ON MAS --
1 Introduction --
2 MAS Development Tools --
3 Agent Academy --
5. COUPLING DATA MINING WITH INTELLIGENT AGENTS --
1 The Unified Methodology --
2 Data Miner: A Tool for Training and Retraining Agents --
Part III Knowledge Diffusion: Three Representative Test Cases --
6. DATA MINING ON THE APPLICATION LEVEL OF A MAS --
1 Enterprise Resource Planning Systems --
2 The Generalized Framework --
3 An IRF Demonstrator --
4 Conclusions --
7. MINING AGENT BEHAVIORS --
1 Predicting Agent Behavior --
2 A Recommendation Engine Demonstrator --
3 Experimental Results --
4 Conclusions --
8. MINING KNOWLEDGE FOR AGENT COMMUNITIES --
1 Ecosystem Simulation --
2 An Overview of Biotope --
3 The Implemented Prototype --
4 Experimental Results --
5 Conclusions --
Part IV Extensions ... --
9. AGENT RETRAINING AND DYNAMICAL IMPROVEMENT OF AGENT INTELLIGENCE --
1 Formal Model --
2 Retraining in the Case of Classification Techniques --
3 Retraining in the Case of Clustering Techniques --
4 Retraining in the Case of Association Rule Extraction Techniques --
5 Retraining in the Case of Genetic Algorithms --
6 Experimental Results --
7 Conclusions --
10. AREAS OF APPLICATION & FUTURE DIRECTIONS --
1 Areas of Application --
2 Advanced AT-DM Symbiosis Architectures --
3 Summary and Conclusions --
4 Open Issues and Future Directions --
References --
Index.
Series Title: Multiagent systems, artificial societies, and simulated organizations, 14.
Responsibility: by Andreas L. Symeonidis, Pericles A. Mitkas.
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Abstract:

This book addresses the use of data mining for smarter, more efficient agents, as well as the challenge of generating intelligence from data while transferring it to a separate, possibly autonomous,  Read more...

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