By Sandip Sen (auth.), Longbing Cao, Ana L. C. Bazzan, Vladimir Gorodetsky, Pericles A. Mitkas, Gerhard Weiss, Philip S. Yu (eds.)
This publication constitutes the refereed complaints of the sixth foreign Workshop on brokers and information Mining interplay, ADMI 2010, held in Toronto, Canada, in could 2010. The 15 revised complete papers provided have been rigorously reviewed and chosen from 37 submissions. The papers are equipped in topical sections on brokers for facts mining; information mining for brokers; facts mining in brokers; and agent mining purposes.
Read or Download Agents and Data Mining Interaction: 6th International Workshop on Agents and Data Mining Interaction, ADMI 2010, Toronto, ON, Canada, May 11, 2010, Revised Selected Papers PDF
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Additional resources for Agents and Data Mining Interaction: 6th International Workshop on Agents and Data Mining Interaction, ADMI 2010, Toronto, ON, Canada, May 11, 2010, Revised Selected Papers
3 Integration of Theories in ABM Design In this pilot study, the operator has control over the various weights assigned to each influence attribute, and is thus able to alter the relative importance each has in determining agent similarity. This is analogous to our planned research design, in which the simulation acts as a testbed for deep and complex data analysis. In our proposed methodology, the operator will be able to set certain controls that input various theories of patient care. ” Consider one scenario, where a hospital implements a new information tracking system to confirm medication types and amounts.
In: 3rd International Symposium on Multi-Agent Systems, Large Complex Systems, and E-Businesses MALCEB 2002 (2002) 3. : An Intelligent Recommendation Framework for ERP Systems. ) IASTED International Conference on Artificial Intelligence and Applications, Innsbruck, pp. 715–720 (2005) 4. : A multi-agent system for meteorological radar data management and decision support. Environmental Modelling & Software 24(11), 1264–1273 (2009) 5. : Information retrieval on the semantic web. ) Proceedings of the Eleventh International Conference on Information and Knowledge Management, Virginia, pp.
To this end, the paper proposes an Obligation Norm Inference (ONI) algorithm which makes use of association rule mining approach to identify obligation norms. g. ). These works assume that the agent somehow knows (a priori) what the norms of a society are. For example, an agent may have obtained the norm from a leader  or through an institution that prescribes what the norms of the society should be . Only a few researchers have dealt with how an agent may infer what the norms of a newly joined society are .