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The Computational Difficulty of Bribery in Qualitative Coalitional Games

机译:质量联盟中贿赂犯罪的计算难点

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摘要

Qualitative coalitional games (QCG) are representations of coalitional games in which self interested agents, each with their own individual goals, group together in order to achieve a set of goals which satisfy all the agents within that group. In such a representation, it is the strategy of the agents to find the best coalition to join. Previous work into QCGs has investigated the computational complexity of determining which is the best coalition to join. We plan to expand on this work by investigating the computational complexity of computing agent power in QCGs as well as by showing that insincere strategies, particularly bribery, are possible when the envy-freeness assumption is removed but that it is computationally difficult to identify the best agents to bribe.
机译:定性联盟博弈(QCG)是联盟博弈的一种表示形式,在联盟博弈中,每个都有自己独立目标的自利代理会聚在一起,以实现满足该组中所有代理的一组目标。在这种表示形式中,代理商的策略是找到最佳的加盟联盟。 QCG的先前工作已经研究了确定哪种联盟最适合的计算复杂性。我们计划通过调查QCG中计算代理能力的计算复杂度,以及通过显示当羡慕自由性假设被删除时可能存在不真诚的策略(尤其是贿赂),但是在计算上难以确定最佳策略时,可以扩展这项工作代理商行贿。

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