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arXiv 2107.04679cs.GT
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不完全合作博弈的1-凸延拓与平均值

1-convex extensions of incomplete cooperative games and the average value

Jan Bok, Martin Černý

AI总结:

本文研究不完全1-凸合作博弈的延拓集合,并据此推广τ-value、Shapley value与nucleolus,证明最小不完全博弈下三者一致,从而提出并公理化average value。

摘要:

不完全合作博弈模型通过考虑部分特征函数,将不确定性纳入经典合作博弈模型。因此,某些联盟的价值是未知的。本文主要关注该框架下的1-凸合作博弈类别。我们关注两个紧密交织的问题。第一,给定一个不完全博弈,我们可以通过哪些方式填补缺失价值以获得经典的1-凸博弈?此类完全博弈被称为1-凸延拓。对于最小不完全博弈类别(其中恰好只有单元素联盟和大联盟的价值已知),我们通过描述1-凸延拓集合给出了答案。该描述利用了该集合的极点和极射线。第二,如何仅依据已知的联盟价值,以理性、公平且高效的方式确定参与者的支付?基于对1-凸延拓集合的描述,我们引入了完全博弈的三个解概念(价值)的推广,即τ-value、Shapley value和nucleolus。我们考虑两种变体:计算极端博弈的重心,或计算极端博弈与极射线组合的重心。我们证明,对于最小不完全博弈,所有这些推广价值都一致,从而可以引入average value。对于该价值,我们基于经典合作博弈中τ-value和Shapley value的公理化刻画,给出了三种不同的公理化。最后,我们将注意力转向具有已定义上向量的不完全博弈,提出相同的问题,而这次得到了不同的结论。这为检验我们关于average value的工具和认识提供了一个基准。

英文摘要:

The model of incomplete cooperative games incorporates uncertainty into the classical model of cooperative games by considering a partial characteristic function. Thus the values for some of the coalitions are not known. The main focus of this paper is the class of 1-convex cooperative games under this framework. We are interested in two heavily intertwined questions. First, given an incomplete game, in which ways can we fill in the missing values to obtain a classical 1-convex game? Such complete games are called \emph{1-convex extensions}. For the class of minimal incomplete games (in which precisely the values of singletons and grand coalitions are known), we provide an answer in terms of a description of the set of 1-convex extensions. The description employs extreme points and extreme rays of the set. Second, how to determine in a rational, fair, and efficient way the payoffs of players based only on the known values of coalitions? Based on the description of the set of 1-convex extensions, we introduce generalisations of three solution concepts (values) for complete games, namely the $τ$-value, the Shapley value and the nucleolus. We consider two variants where we compute the centre of gravity of either extreme games or of a combination of extreme games and extreme rays. We show that all of the generalised values coincide for minimal incomplete games which allows to introduce the \emph{average value}. For this value, we provide three different axiomatisations based on axiomatic characterisations of the $τ$-value and the Shapley value for classical cooperative games. Finally, we turn our attention to \emph{incomplete games with defined upper vector}, asking the same questions and this time arriving to different conclusions. This provides a benchmark to test our tools and knowledge of the average value.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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