Mining frequent agent action patterns for effective multi-agent-based web service composition
Wang, Xiaofeng, Niu, Wenjia, Li, Gang, Yang, Xinghua and Shi, Zhongzhi 2012, Mining frequent agent action patterns for effective multi-agent-based web service composition, in Agents and data mining interaction : 7th International Workshop on Agents and Data Mining Interation, ADMI 2011, Taipei, Taiwan, May 2-6 2011 : revised selected papers, Springer-Verlag, Berlin, Germany, pp.211-227.
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Title
Mining frequent agent action patterns for effective multi-agent-based web service composition
Agents and data mining interaction : 7th International Workshop on Agents and Data Mining Interation, ADMI 2011, Taipei, Taiwan, May 2-6 2011 : revised selected papers
Editor(s)
Cao, Longbing Bazzan, Ana L. C. Symeonidis, Andreas L. Gorodetsky, Vladimir I. Weiss, Gerhard Yu, Philip S.
The dynamic description logic (DDL) is utilized as one emerging AI planning-related solution for automatic Web service composition. However, reasoning utilization when facing the real world service applications in such DDL-related solutions is still an open problem. In this paper, we propose the cooperative reasoning-based multi-agent model (CREMA) which can systematically incorporate DDL action reasoning with data mining, together with a support-based planning method for task decomposition in order to improve the overall throughput of the Web service execution. The case study and experimental analysis demonstrates the capability of the proposed approach.
ISBN
9783642276088 9783642276095
ISSN
0302-9743 1611-3349
Language
eng
Field of Research
089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective
970108 Expanding Knowledge in the Information and Computing Sciences