Robustness of Dynamics in Games: A Contraction Mapping Decomposition Approach

Sina Arefizadeh, Sadegh Arefizadeh, S. Etesami, Sadegh Bolouki
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引用次数: 1

Abstract

A systematic framework for analyzing dynamical attributes of games has not been well-studied except for the special class of potential or near-potential games. In particular, the existing results have shortcomings in determining the asymptotic behavior of a given dynamic in a designated game. Although there is a large body literature on developing convergent dynamics to the Nash equilibrium (NE) of a game, in general, the asymptotic behavior of an underlying dynamic may not be even close to a NE. In this paper, we initiate a new direction towards game dynamics by studying the fundamental properties of the map of dynamics in games. To this aim, we first decompose the map of a given dynamic into contractive and non-contractive parts and then explore the asymptotic behavior of those dynamics using the proximity of such decomposition to contraction mappings. In particular, we analyze the non-contractive behavior for better/best response dynamics in discrete-action space sequential/repeated games and show that the non-contractive part of those dynamics is well-behaved in a certain sense. That allows us to estimate the asymptotic behavior of such dynamics using a neighborhood around the fixed point of their contractive part proxy. Finally, we demonstrate the practicality of our framework via an example from duopoly Cournot games.
游戏动态的鲁棒性:一种收缩映射分解方法
除了潜在或近潜在博弈的特殊类别外,分析博弈动态属性的系统框架还没有得到很好的研究。特别是,现有的结果在确定给定博弈中给定动态的渐近行为方面存在缺陷。尽管有大量的文献将博弈的收敛动力学发展为纳什均衡(NE),但一般来说,潜在动力学的渐近行为可能甚至不接近NE。本文通过对博弈中动态映射的基本性质的研究,为博弈动力学研究开辟了一个新的方向。为此,我们首先将给定的动力学映射分解为压缩部分和非压缩部分,然后利用这种分解与压缩映射的接近性来探索这些动力学的渐近行为。特别地,我们分析了离散行动空间序列/重复对策的最佳/最佳反应动力学的非收缩行为,并证明了这些动力学的非收缩部分在一定意义上是表现良好的。这使得我们可以利用它们的收缩部分代理的不动点周围的邻域来估计这种动力学的渐近行为。最后,我们通过一个双寡头古诺博弈的例子来证明我们的框架的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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