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Bargaining for coalition structure formation
conference contributionposted on 2015-02-13, 10:08 authored by Syeda FatimaSyeda Fatima, Tomasz Michalak, Michael Wooldridge
Many multiagent settings require a collection of agents to partition themselves into coalitions. In such cases, the agents may have conflicting preferences over the possible coalition structures that may form. We investigate a noncooperative bargaining game to allow the agents to resolve such conflicts and partition themselves into non-overlapping coalitions. The game has a finite horizon and is played over discrete time periods. The bargaining agenda is de- fined exogenously. An important element of the game is a parameter 0 ≤ δ ≤ 1 that represents the probability that bargaining ends in a given round. Thus, δ is a measure of the degree of democracy (ranging from democracy for δ = 0, through increasing levels of authoritarianism as δ approaches 1, to dictatorship for δ = 1). For this game, we focus on the question of how a player’s position on the agenda affects his power. We also analyse the relation between the distribution of the power of individual players, the level of democracy, and the welfare efficiency of the game. Surprisingly, we find that purely democratic games are welfare inefficient due to an uneven distribution of power among the individual players. Interestingly, introducing a degree of authoritarianism into the game makes the distribution of power more equitable and maximizes welfare.
Tomasz Michalak & Michael Wooldridge were supported by the European Research Council under Advanced Grant 291528 (“RACE”)
- Computer Science
Published inThe 21st European Conference on Artificial Intelligence (ECAI 2014)
Pages315 - 320
CitationFATIMA, S., MICHALAK, T. and WOOLDRIDGE, M., 2014. Bargaining for coalition structure formation IN: Schaub, T. et al. (eds.) The 21st European Conference on Artificial Intelligence (ECAI 2014), Prague Czech Republic, pp. 315 - 320.
Publisher© The Authors and IOS Press
- VoR (Version of Record)
Publisher statementThis work is made available according to the conditions of the Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by-nc/3.0/
NotesThis is a conference paper from ECAI 2014. It is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License.
Book seriesFrontiers in Artificial Intelligence and Applications;263