Autonomous Intelligent Systems: Multi-Agents and Data Mining

Second International Workshop, AIS-ADM 2007, St. Petersburg, Russia, June 3-5, 2007, Proceedings

326 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

Since early 1990, multi-agent systems (MAS), data mining, and knowledge d- covery (KDD) have remained areas of high interest in the research and - velopment of intelligent information technologies. Indeed, MAS o?ers powerful metaphors for information system conceptualization, a range of new techniques, and technologies speci?cally focused on the design and implementation of lar- scale open distributed intelligent systems. KDD also provides intelligent inf- mation technology with powerful ideas, algorithms, and software means to help cope with the main problem of arti?cial intelligence, formulated in the we- known question “Where does the knowledge come from?”, thus actually making modern applications intelligent and adaptive. The evident recent trend in both science and industry is to integrate and take advantage of both technologies. The existing experience with combined application of multi-agent technology to design architectures of distributed (- erarchical and peer-to-peer) data mining and KDD systems, as well as the u- lization of data mining and KDD achievements to provide enhanced intelligence of MAS, con?rms the fact that both technologies are capable of mutual enri- ment and their integrateduse may result in intelligent information systems with new emergent properties. The 1st International Workshop “Autonomous Int- ligent Systems: Agents and Data Mining” (AIS-ADM 2005, June 6–8, 2005, St. Petersburg, Russia) was a response to the aforementioned trend. It con?rmed the interest of academic and industry communities in advancing the e?orts to integrate achievements in MAS and KDD, thus resulting in a new dimension and further progress in intelligent information technology.

• Reihe: Lecture Notes in Artificial Intelligence
• ISBN: 9783540728382
• Sprache: Englisch
• Erscheinungsdatum: 25.05.2007
• Genre: Informatik, EDV/Informatik
• Verlag: Springer Berlin
• Herausgegeben von: Vladimir Gorodetsky, Chengqi Zhang, Victor Skormin, Longbing Cao