Computational aspects of extending the shapley value to coalitional games with externalities

Tomasz Michalak, Talal Rahwan, Dorota Marciniak, Marcin Szamotulski, Nicholas R. Jennings

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Until recently, computational aspects of the Shapley value were only studied under the assumption that there are no externalities from coalition formation, i.e., that the value of any coalition is independent of other coalitions in the system. However, externalities play a key role in many real-life situations and have been extensively studied in the game-theoretic and economic literature. In this paper, we consider the issue of computing extensions of the Shapley value to coalitional games with externalities proposed by Myerson [21], Pham Do and Norde [23], and McQuillin [17]. To facilitate efficient computation of these extensions, we propose a new representation for coalitional games with externalities, which is based on weighted logical expressions. We demonstrate that this representation is fully expressive and, sometimes, exponentially more concise than the conventional partition function game model. Furthermore, it allows us to compute the aforementioned extensions of the Shapley value in time linear in the size of the input.

Original languageEnglish (US)
Title of host publicationECAI 2010
PublisherIOS Press
Pages197-202
Number of pages6
ISBN (Print)9781607506058
DOIs
StatePublished - 2010
Event2nd Workshop on Knowledge Representation for Health Care, KR4HC 2010, held in conjunction with the 19th European Conference in Artificial Intelligence, ECAI 2010 - Lisbon, Portugal
Duration: Aug 17 2010Aug 17 2010

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume215
ISSN (Print)0922-6389

Other

Other2nd Workshop on Knowledge Representation for Health Care, KR4HC 2010, held in conjunction with the 19th European Conference in Artificial Intelligence, ECAI 2010
Country/TerritoryPortugal
CityLisbon
Period8/17/108/17/10

ASJC Scopus subject areas

  • Artificial Intelligence

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