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MaxSAT Encoding for MC-Net-Based Coalition Structure Generation Problem with Externalities

机译:带有外部性的基于MC-Net的联盟结构生成问题的MaxSAT编码

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Coalition Structure Generation (CSG) is a main research issue in the domain of coalition games. A majority of existing works assume that the value of a coalition is independent of others in the coalition structure. Recently, there has been interest in a more realistic settings, where the value of a coalition is affected by the formation of other coalitions. This effect is known as externality . The focus of this paper is to make use of Maximum Satisfiability (MaxSAT) to solve the CSG problem where externalities may exist. In order to reduce the exponentially growing number of possible solutions in the CSG problem, we follow the previous works by representing the CSG problem as sets of rules in MC-nets (without externalities) and embedded MC-nets (with externalities). Specifically, enlightened by the previous MC-net-based algorithms exploiting the constraints among rule relations to solve the CSG problem, we encode such constraints into weighted partial MaxSAT (WPM) formulas. Experimental results demonstrate that an off-the-shelf MaxSAT solver achieves significant improvements compared to the previous algorithm for the same set of problem instances.
机译:联盟结构生成(CSG)是联盟游戏领域的主要研究问题。现有的大多数工作都假定一个联盟的价值与联盟结构中的其他联盟无关。最近,人们对更现实的设置感兴趣,在该设置中,联盟的价值受其他联盟的形成影响。这种效应称为 externality。本文的重点是利用最大满意度(MaxSAT)解决可能存在外部性的CSG问题。为了减少CSG问题中可能的解决方案的数量呈指数增长,我们按照以前的工作,将CSG问题表示为MC-net(无外部性)和嵌入式MC-net(有外部性)中的一组规则。具体而言,受到先前基于MC-net的算法的启发,该算法利用规则关系之间的约束来解决CSG问题,我们将这些约束编码为加权部分MaxSAT(WPM)公式。实验结果表明,对于相同的问题实例集,与以前的算法相比,现成的MaxSAT求解器具有明显的改进。

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