Extension of MC-net-based coalition structure generation: Handling negative rules and externalities

Ryo Ichimura, Takato Hasegawa, Suguru Ueda, Atsushi Iwasaki, Makoto Yokoo

Research output: Contribution to conferencePaperpeer-review

5 Citations (Scopus)

Abstract

Forming effective coalitions is a major research challenge in AI and multi-agent systems. A Coalition Structure Generation (CSG) problem involves partitioning a set of agents into coalitions so that the social surplus is maximized. Ohta et al introduce an innovative direction for solving CSG, i.e., by representing a characteristic function as a set of rules, a CSG problem can be formalized as the problem of finding a subset of rules that maximizes the sum of rule values under certain constraints. This paper considers two significant extensions of the formalization/algorithm of Ohta et al, i.e., (i) handling negative value rules and (ii) handling externalities among coalitions.

Original languageEnglish
Pages1105-1106
Number of pages2
Publication statusPublished - Jan 1 2011
Event10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011 - Taipei, Taiwan, Province of China
Duration: May 2 2011May 6 2011

Other

Other10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011
CountryTaiwan, Province of China
CityTaipei
Period5/2/115/6/11

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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