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Coalition Structure Generation and CS-core: Results on the Tractability Frontier for games represented by MC-nets

Abstract : The coalition structure generation (CSG) problem consists in partitioning a group of agents into coalitions to maximize the sum of their values. We consider here the case of coalitional games whose characteristic function is compactly represented by a set of weighted conjunctive formulae (an MC-net). In this context the CSG problem is known to be computationally hard in general. In this paper, we first study some key parameters of MC-nets that complicate solving the CSG problem. Then we consider a specific class of MC-nets, called bipolar MC-nets, and prove that the CSG problem is polynomial for this class. Finally, we show that the CS-core of a game represented by a bipolar MC-net is never empty, and that an imputation belonging to the CS-core can be computed in polynomial time.
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https://hal.sorbonne-universite.fr/hal-01520392
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Submitted on : Wednesday, May 10, 2017 - 2:45:08 PM
Last modification on : Thursday, November 18, 2021 - 4:06:08 AM
Long-term archiving on: : Friday, August 11, 2017 - 1:12:52 PM

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  • HAL Id : hal-01520392, version 1

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Julien Lesca, Patrice Perny, Makoto Yokoo. Coalition Structure Generation and CS-core: Results on the Tractability Frontier for games represented by MC-nets. International Conference on Autonomous Agents and Multiagent Systems, May 2017, Sao-Paulo, Brazil. ⟨hal-01520392⟩

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