By Max Bramer
This e-book constitutes the refereed complaints of the IFIP TC 12 synthetic Intelligence Stream held on the twentieth international laptop Congress in Milano, Italy, September 7-10, 2008.
The IFIP sequence publishes cutting-edge ends up in the sciences and applied sciences of data and conversation. The scope of the sequence contains: foundations of laptop technology; software program idea and perform; schooling; laptop functions in know-how; conversation structures; structures modeling and optimization; info structures; desktops and society; computers expertise; safety and safeguard in info processing structures; synthetic intelligence; and human-computer interplay. court cases and post-proceedings of refereed overseas meetings in machine technological know-how and interdisciplinary fields are featured. those effects frequently precede magazine book and characterize the most up-tp-date learn. The important target of the IFIP sequence is to motivate schooling and the dissemination and alternate of data approximately all points of computing.
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Extra info for Artificial Intelligence in Theory and Practice II: IFIP 20th World Computer Congress, TC 12: IFIP AI 2008 Stream, September 7-10, 2008, Milano, Italy (IFIP ... and Communication Technology) (No. II)
E. a system composed of a community of agents, capable of reaching goals that are difﬁcult to achieve by an individual system . In addition, a MAS can display self-organizational and complex behaviours, even when the capabilities of individual agents are relatively simple. The fundamental distinc- Agent Based Frequent Set Meta Mining: Introducing EMADS 25 tion between a distributed architecture and a MAS architecture is one of control. In a distributed system control is centralized; in a MAS control is decentralized in that agents are self motivating, and problem solving is achieved through intercommunication between agents.
The use of EMADS offers a number of advantages, includes: decentralised control, distribution of computational resources, interoperability, distribution of expertise, task and data matching, Result evaluation, simple extendibility and security. To illustrate some of the features of EMADS a Meta ARM (Association Rule Mining) scenario is considered in this paper. We deﬁne the term Meta Mining as the process of combining the individually obtained results of N applications of a data mining activity.
111-120, 1997. 2. Aggarwal, C. C. and Yu, P. , “A Condensation Approach to Privacy Preserving Data Mining”. Lecture Notes in Computer Science, Vol. 2992, pp. 183-199, 2004 3. , “An Introduction to Multi-Agent Systems”. John Wiley and Sons Ltd, paperback, 366 pages, ISBN 0-471-49691-X, 2002. 4. , Prodromidis, A. , Tselepis, S. , “JAM: Java Agents for Meta-Learning over Distributed Databases”. Proc. of the International Conference on Knowledge Discovery and Data Mining, pp. 74-81, 1997. 5. Xu, L.