Concise characteristic function representations in coalitional games based on agent types

Suguru Ueda, Makoto Kitaki, Atsushi Iwasaki, Makoto Yokoo

Research output: Contribution to conferencePaperpeer-review

12 Citations (Scopus)

Abstract

Forming effective coalitions is a major research challenge in AI and multi-agent systems. Thus, coalitional games, including coalition structure generation, have been attracting considerable attention from the AI research community. Traditionally, the input of a coalitional game is a black-box function called a characteristic function. In this paper, we develop a new concise representation scheme for a characteristic function, which is based on the idea of agent types. This representation can be exponentially more concise than existing concise representation schemes. Furthermore, this idea can be used in conjunction with existing schemes to further reduce the representation size.

Original languageEnglish
Pages1201-1202
Number of pages2
Publication statusPublished - 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
Country/TerritoryTaiwan, Province of China
CityTaipei
Period5/2/115/6/11

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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