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Matrix Representation of Solution Concepts in the Graph Model for Conflict Resolution with Probabilistic Preferences and Multiple Decision Makers

机译:利用概率偏好和多种决策者冲突解决方案概念的矩阵表示

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摘要

In this paper, matrix methods are developed to determine stable states in the graph model for conflict resolution (GMCR) with probabilistic preferences with n decision makers. The matrix methods are used to determine more easily the stable states according to five stability definitions proposed for this model, namely: alpha-Nash stability, (alpha, beta)-metarationality, (alpha, beta)-symmetric metarationality, (alpha, beta, gamma)-sequential stability and (alpha, beta, gamma)-symmetric sequential stability. With the help of such methods, we are able to analyze for which values of parameters alpha, beta and gamma the states satisfy each one of these stability notions. These parameters regions can be used to compare the equilibrium robustness of the states. As a byproduct of our method, we point out an existing problem in the literature regarding matrix representation of solution concepts in the GMCR.
机译:在本文中,开发了矩阵方法以确定与N决策者的概率偏好的冲突解决方案(GMCR)图模型中的稳定状态。 基质方法用于根据该模型提出的五个稳定性定义来确定更容易的稳定状态,即:α-纳什稳定性,(α,β) - (alpha,beta) - 对称的元,(alpha,beta ,γ) - 顺序稳定性和(α,β,伽马) - 对称顺序稳定性。 借助这些方法,我们能够分析参数α,β和伽马的值,各国满足这些稳定概念中的每一个。 这些参数区域可用于比较州的均衡稳健性。 作为我们方法的副产品,我们指出了关于GMCR中解决方案概念的矩阵表示的文献中的存在问题。

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