| 期刊全稱 | Autonomous Intelligent Systems: Multi-Agents and Data Mining | | 期刊簡(jiǎn)稱 | Second International | | 影響因子2023 | Vladimir Gorodetsky,Chengqi Zhang,Longbing Cao | | 視頻video | http://file.papertrans.cn/167/166779/166779.mp4 | | 學(xué)科分類 | Lecture Notes in Computer Science | | 圖書封面 |  | | 影響因子 | 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 | | Pindex | Conference proceedings 2007 |
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