Many organizations have an urgent need of mining their multiple databases inherently distributed in branches (distributed data). In particular, as the Web is rapidly becoming an information flood, individuals and organizations can take into account low-cost information and knowledge on the Internet when making decisions. How to efficiently identify quality knowledge from different data sources has become a significant challenge. This challenge has attracted a great many researchers including the au- thors who have developed a local pattern analysis, a new strategy for dis- covering some kinds...

This book constitutes the refereed proceedings of the First Australian Workshop on Distributed Artificial Intelligence, held in Canberra, ACT, Australia, in November 1995.
The 16 full papers included in the book are revised versions of the contributions accepted for presentation at the workshop; they cover a wide range of current issues in the field of DAI, such as formal frameworks, methodology, theory, and architecture; various aspects of agents and multi-agent systems are addressed.

This book constitutes the strictly refereed post-workshop proceedings originating from the Second Australian Workshop on Distributed Artificial Intelligence, held in Cairns, QLD, Australia, in August 1996, as a satellite meeting of PRICAI'96.
The 13 revised full papers presented have been selected for inclusion in the book during a very careful and iterated process of reviewing and improvement. Among these papers are three invited ones, by leading scientists, solicited in order to round off the overall presentation and coverage of relevant topics. A wide range of multi-agent systems issues...