Ebook: Advances in Machine Learning and Cybernetics: 4th International Conference, ICMLC 2005, Guangzhou, China, August 18-21, 2005, Revised Selected Papers

Machine learning and cybernetics play an important role in many modern electronic, computer and communications systems. Automated processing of information by these systems requires intelligent analysis of various types of data and optimal decision making. In recent years, we have witnessed a rapid expansion of research and development activities in machine learning and cybernetics. To provide opportunities for researchers in these areas to share their ideas and foster collaborations, the International Conference on Machines and Cybernetics (ICMLC) has been held annually since 2002. The conference series has achieved a great success in attracting a large number of paper submissions and participants and enabling fruitful exchanges among academic and industrial researchers and postgraduate students. In 2005, the conference (ICMLC 2005) received 2461 full paper submissions and the Program Committee selected 1050 of them for presentation. It is especially encouraging that the conference is attracting more and more international attention. This year, there are contributions from 21 countries and 211 universities worldwide. Out of the 1050 papers presented at the conference, we selected 114 papers to be published in this volume of Lecture Notes in Computer Science.

This book constitutes the thoroughly refereed post-proceedings of the 4th International Conference on Machine Learning and Cybernetics, ICMLC 2005, held in Guangzhou, China in August 2005.

The 114 revised full papers of this volume were carefully reviewed and selected from 2461 paper submissions and 1050 real conference presentations respectively during two rounds of reviewing and improvement. The papers are organized in topical sections on agents and distributed artificial intelligence, control, data mining and knowledge discovery, fuzzy information processing, learning and reasoning, machine learning applications, neural networks and statistical learning methods, pattern recognition, vision and image processing.