• to Agents and Data Mining Interaction.- to Agent Mining Interaction and Integration.- Towards the Integration of Multiagent Applications and Data Mining.- Agent-Based Distributed Data Mining: A Survey.- Data Mining Driven Agents.- Exploiting Swarm Behaviour of Simple Agents for Clustering Web Users’ Session Data.- Mining Temporal Patterns to Improve Agents Behavior: Two Case Studies.- A Multi-Agent System for Extracting and Analysing Users’ Interaction in a Collaborative Knowledge Management System.- Towards Information Enrichment through Recommendation Sharing.- A Multiagent-based Intrusion Detection System with the Support of Multi-Class Supervised Classification.- Automatic Web Data Extraction Based on Genetic Algorithms and Regular Expressions.- Establishment and Maintenance of a Knowledge Network by Means of Agents and Implicit Data.- Equipping Intelligent Agents with Commonsense Knowledge acquired from Search Query Logs: Results from an Exploratory Story.- A Multi-Agent Learning Paradigm for Medical Data Mining Diagnostic Workbench.- Agent Driven Data Mining.- The EMADS Extendible Multi-Agent Data Mining Framework.- A Multiagent Approach to Adaptive Continuous Analysis of Streaming Data in Complex Uncertain Environments.- Multiagent Systems for Large Data Clustering.- A Multiagent, Multiobjective Clustering Algorithm.- Integration of Agents and Data Mining in Interactive Web Environment for Psychometric Diagnostics.- A Multi-Agent Framework for Anomalies Detection on Distributed Firewalls Using Data Mining Techniques.- Competitive-Cooperative Automated Reasoning from Distributed and Multiple Source of Data.- Normative Multi-Agent Enriched Data Mining to Support E-Citizens.- CV-Muzar - The Virtual Community Environment that Uses Multiagent Systems for Formationof Groups.- Agent based Video Contents Identification and Data Mining Using Watermark based Filtering.- Erratum.

From the reviews: "This book promotes the latest methodological, technical, and practical advancements in the use of agents in data mining applications. ... chapters include extensive bibliographies. ... The book is intended for students, researchers, engineers, and practitioners, in both agent and data mining areas, who are interested in the potential of integrating agents and mining. ... interested readers who are willing to make an effort to build on the book's material will benefit from reading it." (J. P. E. Hodgson, ACM Computing Reviews, December, 2009)