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.
翻译:系统地分析游戏动力学特征的框架尚未深入研究,除了势或近势游戏等特殊类别。特别是,现有结果在确定指定游戏中给定动态的渐近行为方面存在缺陷。尽管有大量文献致力于发展收敛于游戏纳什均衡的动力学,但一般而言,潜在动态的渐近行为甚至可能与纳什均衡都无关。在本文中,我们通过研究游戏中动力学映射的基本属性来开始一条新的动态游戏研究方向。为此,我们首先将给定动态的映射分解为收缩和非收缩部分,然后使用这种分解接近收缩映射来探索这些动态的渐近行为。具体而言,我们分析了离散动作空间的最佳反应动态中的非收缩行为,并显示这些动态的非收缩部分在某种意义下是良好的。这使我们能够使用以其收缩部分为代理的固定点周围的邻域来估计这些动态的渐近行为。最后,我们通过一个来自二合一Cournot游戏的示例证明了我们框架的实用性。