论文标题
在接近潜力的游戏中，分散的虚拟游戏在NASH平衡附近收敛
Decentralized Fictitious Play Converges Near a Nash Equilibrium in Near-Potential Games
论文作者
论文摘要
我们研究了在接近潜力的游戏中分散虚拟游戏（DFP）的收敛性，其中代理的偏好几乎可以被潜在的功能捕获。在DFP代理中，代理商对其他代理的经验频率进行了本地估计，对这些估计值进行了最佳回答，并在随着时间的变化通信网络中接收信息。我们证明，DFP产生的作用的经验频率围绕单个NASH平衡（NE）收敛，假设只有有限的NASH平衡，并且单方面偏差所产生的效用函数差异足以与电位函数值的差异相差。该结果确保了DFP在近乎潜力的游戏中具有标准虚拟游戏（FP）相同的收敛属性。
We investigate convergence of decentralized fictitious play (DFP) in near-potential games, wherein agents preferences can almost be captured by a potential function. In DFP agents keep local estimates of other agents' empirical frequencies, best-respond against these estimates, and receive information over a time-varying communication network. We prove that empirical frequencies of actions generated by DFP converge around a single Nash Equilibrium (NE) assuming that there are only finitely many Nash equilibria, and the difference in utility functions resulting from unilateral deviations is close enough to the difference in the potential function values. This result assures that DFP has the same convergence properties of standard Fictitious play (FP) in near-potential games.
