Autonomous Intelligent Systems: Agents and Data Mining

This volume contains the papers presented at the International Workshop Autonomous Intelligent Systems: Agents and Data Mining (AIS-ADM 2005) held in St. Petersburg, Russia, during June 6 8, 2005. The workshop was - ganized by the St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS) in cooperation with Binghamton U- versity (SUNY, USA) and the Web Intelligence Consortium. Autonomous Intelligent Systems (AIS) constitute an emerging class of int- ligent information systems integrating recent advances in various technologies of Arti?cial Intelligence. Modern AIS incorporate multi-agent and data mining systemsprovidinganewdimensionforfurtherprogressinintelligentinformation technology. AIS-ADM 2005 provided an international forum to multi-agent and data mining researchers. A total of 29 papers from 15 countries relating to various aspects of both theory and applications of multi-agent systems, data mining and their joint area were submitted to AIS-ADM 2005. Out of them 17 were selected as regular presentations. Three technical sessions were organized, namely: In- gration of Multi-agent and Data Mining Techniques; Ontology Issues and Web Mining; and Applications and Case Studies of the Integrated Technology. The panel discussion was devoted to the mutual enrichment and challenging pr- lems emerging in the joint area of research. The AIS-ADM 2005 program was enriched by six distinguished invited speakers: Nick Jennings, Chengqi Zhang, Mircea Negoita, Pericles Mitkas, Hai Zhuge and Leonid Perlovsky.

Autorentext
Dr. Jiming Liu is the Head of Computer Science Department at Hong Kong Baptist University (HKBU). He leads the AAMAS/AOC Research Group (i.e., Autonomous Agents and Multi-Agent Systems / Autonomy-Oriented Computing) at HKBU. He holds a B.Sc. degree in Physics from East China Normal University in Shanghai, an M.A. degree in Educational Technology from Concordia University in Montreal, and an M.Eng. and a Ph.D. degrees both in Electrical Engineering from McGill University in Montreal. In Feb.-July 1999, Dr. Liu was an invited Visiting Scholar in Computer Science Department, Stanford University, where he was associated with the AI & Robotics Laboratory and taught advanced graduate classes on topics related to Robot Learning, Neural Robots, and Evolutionary Robotics. He is Guest Professor at University of Science and Technology of China, East China Normal University (Software Engineering Institute), and Beijing University of Technology, as well as Adjunct Fellow at E-Business Technology Institute (ETI - a joint partnership institute between IBM and University of Hong Kong). Dr. Liu is the co-founder of Web Intelligence Consortium (WIC), an international organization dedicated to promoting world-wide scientific research and industrial development in the era of Web and agent Intelligence. He has founded andserved, or is serving, as Program, Conference, Workshop, and General Chairs for several international conferences and workshops, including The IEEE/WIC International Conference on Web Intelligence (WI) series and The IEEE/WIC International Conference on Intelligent Agent Technology (IAT) series, and is presently serving as the Senior Program Committee Member, Program Committee Member, and Steering/Planning Committee Member for many major international conferences.

Klappentext

This volume contains the papers presented at the International Workshop Autonomous Intelligent Systems: Agents and Data Mining (AIS-ADM 2005) held in St. Petersburg, Russia, during June 6 8, 2005. The workshop was - ganized by the St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS) in cooperation with Binghamton U- versity (SUNY, USA) and the Web Intelligence Consortium. Autonomous Intelligent Systems (AIS) constitute an emerging class of int- ligent information systems integrating recent advances in various technologies of Arti?cial Intelligence. Modern AIS incorporate multi-agent and data mining systemsprovidinganewdimensionforfurtherprogressinintelligentinformation technology. AIS-ADM 2005 provided an international forum to multi-agent and data mining researchers. A total of 29 papers from 15 countries relating to various aspects of both theory and applications of multi-agent systems, data mining and their joint area were submitted to AIS-ADM 2005. Out of them 17 were selected as regular presentations. Three technical sessions were organized, namely: In- gration of Multi-agent and Data Mining Techniques; Ontology Issues and Web Mining; and Applications and Case Studies of the Integrated Technology. The panel discussion was devoted to the mutual enrichment and challenging pr- lems emerging in the joint area of research. The AIS-ADM 2005 program was enriched by six distinguished invited speakers: Nick Jennings, Chengqi Zhang, Mircea Negoita, Pericles Mitkas, Hai Zhuge and Leonid Perlovsky.

Inhalt
Invited Papers.- Negotiation Technologies.- Knowledge Discovery for Training Intelligent Agents: Methodology, Tools and Applications.- Artificial Immune SystemsAn Emergent Technology for Autonomous Intelligent Systems and Data Mining.- Evolving Agents: Communication and Cognition.- Agents and Data Mining: Mutual Enhancement by Integration.- Soft-Device Inheritance in the Knowledge Grid.- Agent Based Data Mining Issues.- Towards the Adaptive Organization: Formation and Conservative Reconfiguration of Agents Coalitions.- A Cooperative Multi-agent Data Mining Model and Its Application to Medical Data on Diabetes.- Technology of Agent-Based Decision Making System Development.- An Architecture for Distributed Agent-Based Data Preprocessing.- Meta-reasoning Methods for Agent's Intention Modelling.- Execution Engine of Meta-learning System for KDD in Multi-agent Environment.- A Methodology for Predicting Agent Behavior by the Use of Data Mining Techniques.- Ontology and Web Mining.- Topic-Specific Text Filtering Based on Multiple Reducts.- Parallel Algorithm for Mining Frequent Closed Sequences.- Decision Trees Capacity and Probability of Misclassification.- Querying Dynamic and Context-Sensitive Metadata in Semantic Web.- Ontology Issue in Multi-agent Distributed Learning.- Ontology-Based Users and Requests Clustering in Customer Service Management System.- Multi-agent Approach for Community Clustering Based on Individual Ontology Annotations.- Applications and Case Studies.- Effective Discovery of Intrusion Protection Strategies.- Integrating Knowledge Through Cooperative Negotiation A Case Study in Bioinformatics.- Data Mining Techniques for RoboCup Soccer Agents.