Published:
2018-02-08
Proceedings:
Proceedings of the AAAI Conference on Artificial Intelligence, 32
Volume
Issue:
Thirty-Second AAAI Conference on Artificial Intelligence 2018
Track:
AAAI Technical Track: Game Theory and Economic Paradigms
Downloads:
Abstract:
Cooperative games provide a framework to study cooperation among self-interested agents. They offer a number of solution concepts describing how the outcome of the cooperation should be shared among the players. Unfortunately, computational problems associated with many of these solution concepts tend to be intractable---NP-hard or worse. In this paper, we incorporate complexity measures recently proposed by Feige and Izsak (2013), called dependency degree and supermodular degree, into the complexity analysis of coopera- tive games. We show that many computational problems for cooperative games become tractable for games whose dependency degree or supermodular degree are bounded. In particular, we prove that simple games admit efficient algorithms for various solution concepts when the supermodular degree is small; further, we show that computing the Shapley value is always in FPT with respect to the dependency degree. Finally, we observe that, while determining the dependency among players is computationally hard, there are efficient algorithms for special classes of games.
DOI:
10.1609/aaai.v32i1.11475
AAAI
Thirty-Second AAAI Conference on Artificial Intelligence 2018
ISSN 2374-3468 (Online) ISSN 2159-5399 (Print)
Published by AAAI Press, Palo Alto, California USA Copyright © 2018, Association for the Advancement of Artificial Intelligence All Rights Reserved.