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author:

Su, S.-X. (Su, S.-X..) [1] | Hu, S.-L. (Hu, S.-L..) [2] | Zheng, S.-F. (Zheng, S.-F..) [3] | Lin, C.-F. (Lin, C.-F..) [4] | Lai, X.-W. (Lai, X.-W..) [5]

Indexed by:

Scopus

Abstract:

Coalition formation is a key topic in multi-agent systems. One may prefer a coalition structure that maximizes the sum of the values of the coalitions, but often the number of coalition structures is too large to allow exhaustive search for the optimal one. Furthermore, finding the optimal coalition structure is NP-hard. Thus emerges the meaningful problem: when practical applications can present required real bound on the worst case, and how to attain this demand via partial search? This paper reports on a novel algorithm based on cardinality structure: the bound K≥2 can be attained with searching of those coalition structures whose cardinality structure is in the CCS(n, K). Finally, experiments indicates the new algorithm is obviously better than existing algorithms. ©2007 IEEE.

Keyword:

Cardinality structure; Coalition structure; Multiagent system

Community:

  • [ 1 ] [Su, S.-X.]Department of Computer Science and Technology, Fuzhou University, Fuzhou 350002, China
  • [ 2 ] [Hu, S.-L.]Department of Computer Science and Technology, Fuzhou University, Fuzhou 350002, China
  • [ 3 ] [Hu, S.-L.]Key Laboratory for Computer Science, Chinese Academy of Sciences, Beijing, 100080, China
  • [ 4 ] [Zheng, S.-F.]Department of Computer Science and Technology, Fuzhou University, Fuzhou 350002, China
  • [ 5 ] [Lin, C.-F.]Department of Computer Science and Technology, Fuzhou University, Fuzhou 350002, China
  • [ 6 ] [Lai, X.-W.]Department of Computer Science and Technology, Fuzhou University, Fuzhou 350002, China

Reprint 's Address:

  • [Su, S.-X.]Department of Computer Science and Technology, Fuzhou University, Fuzhou 350002, China

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Source :

Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007

Year: 2007

Volume: 5

Page: 2505-2510

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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