Details

Agent Intelligence Through Data Mining


Agent Intelligence Through Data Mining


Multiagent Systems, Artificial Societies, and Simulated Organizations, Band 14

von: Andreas L. Symeonidis, Pericles A. Mitkas

96,29 €

Verlag: Springer
Format: PDF
Veröffentl.: 06.05.2006
ISBN/EAN: 9780387257570
Sprache: englisch
Anzahl Seiten: 206

Dieses eBook enthält ein Wasserzeichen.

Beschreibungen

<P>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.</P>
<P>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.</P>
Concepts and Techniques.- Data Mining and Knowledge Discovery: A Brief Overview.- Intelligent Agents and Multi-Agent Systems.- Methodology.- Exploiting Data Mining on Mas.- Coupling Data Mining with Intelligent Agents.- Knowledge Diffusion: Three Representative Test Cases.- Data Mining on the Application Level of a Mas.- Mining Agent Behaviors.- Mining Knowledge for Agent Communities.- Extensions….- Agent Retraining and Dynamical Improvement of Agent Intelligence.- Areas of Application & Future Directions.
<P><STRONG>AGENT INTELLIGENCE THROUGH DATA MINING</STRONG> 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 more mundane use of intelligent agents for improved data mining and; b) the use of data mining for smarter, more efficient agents. The second approach is the main focus of this volume.</P>
<P>Knowledge, routinely created and maintained by today’s applications, is hidden in voluminous data repositories that 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. <STRONG>AGENT INTELLIGENCE THROUGH DATA MINING</STRONG> addresses this issue, as well as the arguable challenge of generating intelligence from data while transferring it to a separate, possibly autonomous, software entity. Following a brief review of data mining and agent technology fields, this book presents a methodology for developing multi-agent systems, describes available open-source tools to support this process, and demonstrates the application of the methodology on three different cases.</P>
<P><STRONG>AGENT INTELLIGENCE THROUGH DATA MINING</STRONG> is designed for a professional audience composed of researchers and practitioners in industry. This volume is also suitable for graduate-level students in computer science.</P>
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
<P>Agent Intelligence Through Data Mining unifies and integrates methodology and provides the ability to infuse knowledge extracted by the use of data mining techniques into agents and Multi-Agent Systems (MAS). This book includes the investigation and application of a great number of data mining methods on MAS application. Due to the nature of the technologies involved, the authors present a number of generic multi-agent models, and a novel agent-oriented data mining algorithm to be applied to specific problems presented within this book. </P>

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