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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…mehr
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.
Andreas L. Symeonidis, Aristotle University of Thessaloniki, Greece / Pericles A. Mitkas, Aristotle University of Thessaloniki, Greece
Inhaltsangabe
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.
From the contents Part I. Concepts and Techniques. Introduction. Data Mining and Knowledge Discovery: A Brief Overview. Intelligent Agents and Multi-Agent Systems.- Part II. Methodology. Exploiting Data Mining on MAS. Coupling Data Mining with Intelligent Agents.- Part III. Knowledge Diffusion: Three Representative Test Cases. Data Mining on the Application Level of a MAS. Mining Agent Behaviors. Mining Knowledge for Agent Communities.- Part IV. Extensions. Agent Retraining and Dynamical Improvement of Agent Intelligence. Areas of Application and Future Directions.- Glossary. References. Index.
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.
From the contents Part I. Concepts and Techniques. Introduction. Data Mining and Knowledge Discovery: A Brief Overview. Intelligent Agents and Multi-Agent Systems.- Part II. Methodology. Exploiting Data Mining on MAS. Coupling Data Mining with Intelligent Agents.- Part III. Knowledge Diffusion: Three Representative Test Cases. Data Mining on the Application Level of a MAS. Mining Agent Behaviors. Mining Knowledge for Agent Communities.- Part IV. Extensions. Agent Retraining and Dynamical Improvement of Agent Intelligence. Areas of Application and Future Directions.- Glossary. References. Index.
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