Overview
- Authors prove utilization of data mining to support machine learning tasks in multi-agent systems research confirms the fact that these two technologies are capable of mutual enrichment
- This joint use results in information systems with emergent properties
Part of the book series: Multiagent Systems, Artificial Societies, and Simulated Organizations (MASA, volume 14)
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Table of contents (10 chapters)
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Front Matter
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Knowledge Diffusion: Three Representative Test Cases
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Back Matter
Keywords
About this book
Knowledge, hidden in voluminous data repositories routinely created and maintained by today’s applications, can be extracted by data mining. The next step is to transform this discovered knowledge into the inference mechanisms or simply the behavior of agents and multi-agent systems. Agent Intelligence Through Data Mining addresses this issue, as well as the arguable challenge of generating intelligence from data while transferring it to a separate, possibly autonomous, software entity. This book contains a methodology, tools and techniques, and several examples of agent-based applications developed with this approach. This volume focuses mainly on the use of data mining for smarter, more efficient agents.
Agent Intelligence Through Data Mining is designed for a professional audience of researchers and practitioners in industry. This book is also suitable for graduate-level students in computer science.
Authors and Affiliations
Bibliographic Information
Book Title: Agent Intelligence Through Data Mining
Authors: Andreas L. Symeonidis, Pericles A. Mitkas
Series Title: Multiagent Systems, Artificial Societies, and Simulated Organizations
DOI: https://doi.org/10.1007/b136000
Publisher: Springer New York, NY
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag US 2005
Hardcover ISBN: 978-0-387-24352-8Published: 15 July 2005
Softcover ISBN: 978-1-4419-3724-7Published: 04 October 2011
eBook ISBN: 978-0-387-25757-0Published: 06 May 2006
Series ISSN: 1568-2617
Edition Number: 1
Number of Pages: XXVI, 206
Number of Illustrations: 77 b/w illustrations
Topics: Artificial Intelligence, Data Mining and Knowledge Discovery, Database Management, Software Engineering/Programming and Operating Systems, Data Structures, Artificial Intelligence