Computing a payoff division in the least core for MC-nets coalitional games

Katsutoshi Hirayama, Kenta Hanada, Suguru Ueda, Makoto Yokoo, Atsushi Iwasaki

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

1 被引用数 (Scopus)

抄録

MC-nets is a concise representation of the characteristic functions that exploits a set of rules to compute payoffs. Given aMC-nets instance, the problem of computing a payoff division in the least core, which is a generalization of the core-non-emptiness problem that is known to be coNP-complete, is definitely a hard computational problem. In fact, to the best of our knowledge, no algorithm can actually compute such a payoff division for MC-nets instances with dozens of agents. We propose a new algorithm for this problem, that exploits the constraint generation technique to solve the linear programming problem that potentially has a huge number of constraints. Our experimental results are striking since, using 8 GB memory, our proposed algorithm can successfully compute a payoff division in the least core for the instances with up to 100 agents, but the naive algorithm fails due to a lack of memory for instances with 30 or more agents.

本文言語英語
ホスト出版物のタイトルPRIMA 2014
ホスト出版物のサブタイトルPrinciples and Practice of Multi-Agent Systems - 17th International Conference, Proceedings
編集者Hoa Khanh Dam, Jeremy Pitt, Yang Xu, Guido Governatori, Takayuki Ito
出版社Springer Verlag
ページ319-332
ページ数14
ISBN(電子版)9783319131900
DOI
出版ステータス出版済み - 2014
イベント17th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2014 - Gold Coast, オーストラリア
継続期間: 12 1 201412 5 2014

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
8861
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

その他

その他17th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2014
Countryオーストラリア
CityGold Coast
Period12/1/1412/5/14

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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