TY - GEN
T1 - The advantages of compromising in coalition formation with incomplete information
AU - Kraus, Sarit
AU - Shehory, Onn
AU - Taase, Gilad
PY - 2004
Y1 - 2004
N2 - This paper presents protocols and strategies for coalition formation with incomplete information under time constraints. It focuses on strategies for coalition members to distribute revenues amongst themselves. Such strategies should preferably be stable, lead to a fair distribution, and maximize the social welfare of the agents. These properties are only partially supported by existing coalition formation mechanisms. In particular, stability and the maximization of social welfare are supported only in the case of complete information, and only at a high computational complexity. Recent studies on coalition formation with incomplete and uncertain information address revenue distribution in a naïve manner. In this study we specifically refer to environments with limited computational resources and incomplete information. We propose a variety of strategies for revenue distribution, including the strategy in which the agents attempt to distribute the estimated net value of a coalition equally. A variation of the equal distribution strategy in which agents compromise and agree to a payoff lower than their estimated equal share, was specifically examined. Our experimental results show that, under time constraints, the compromise strategy is stable and increases the social welfare compared to non-compromise strategies.
AB - This paper presents protocols and strategies for coalition formation with incomplete information under time constraints. It focuses on strategies for coalition members to distribute revenues amongst themselves. Such strategies should preferably be stable, lead to a fair distribution, and maximize the social welfare of the agents. These properties are only partially supported by existing coalition formation mechanisms. In particular, stability and the maximization of social welfare are supported only in the case of complete information, and only at a high computational complexity. Recent studies on coalition formation with incomplete and uncertain information address revenue distribution in a naïve manner. In this study we specifically refer to environments with limited computational resources and incomplete information. We propose a variety of strategies for revenue distribution, including the strategy in which the agents attempt to distribute the estimated net value of a coalition equally. A variation of the equal distribution strategy in which agents compromise and agree to a payoff lower than their estimated equal share, was specifically examined. Our experimental results show that, under time constraints, the compromise strategy is stable and increases the social welfare compared to non-compromise strategies.
UR - http://www.scopus.com/inward/record.url?scp=4544279717&partnerID=8YFLogxK
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AN - SCOPUS:4544279717
SN - 1581138644
SN - 9781581138641
T3 - Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2004
SP - 588
EP - 595
BT - Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2004
A2 - Jennings, N.R.
A2 - Sierra, C.
A2 - Sonenberg, L.
A2 - Tambe, M.
T2 - Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2004
Y2 - 19 July 2004 through 23 July 2004
ER -