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Published Articles >> Table of Contents >> Abstract
Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2 (AAMAS'04)
pp. 588-595
The Advantages of Compromising in Coalition Formation with Incomplete Information
Sarit Kraus, Bar-Ilan University and University of Maryland at College Park
Onn Shehory, IBM Research Lab in Haifa
Gilad Taase, Bar-Ilan University
Full Article Text:
 
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AAMAS.2004.10113
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| Abstract |
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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.
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 Additional Information
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Citation:
Sarit Kraus, Onn Shehory, Gilad Taase,
"The Advantages of Compromising in Coalition Formation with Incomplete Information,"
aamas,
pp. 588-595,
Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2 (AAMAS'04),
2004
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