论文标题

在部分决策信息下寻求随机广义的NASH平衡

Stochastic generalized Nash equilibrium seeking under partial-decision information

论文作者

Franci, Barbara, Grammatico, Sergio

论文摘要

我们首次考虑了随机通用的NASH平衡问题,即具有预期价值的成本功能和关节可行性限制,在部分决策信息下,这意味着代理人仅与一些受信任的邻居进行通信。我们为网络游戏和聚合游戏提出了几种分布式算法,这些算法是预处理前后分裂方法的特殊实例。我们证明,当通过使用降低方差的随机近似方案限制前向操作员受到限制的核能时,算法会收敛到广义的NASH平衡,以估计假差的预期值。

We consider for the first time a stochastic generalized Nash equilibrium problem, i.e., with expected-value cost functions and joint feasibility constraints, under partial-decision information, meaning that the agents communicate only with some trusted neighbours. We propose several distributed algorithms for network games and aggregative games that we show being special instances of a preconditioned forward-backward splitting method. We prove that the algorithms converge to a generalized Nash equilibrium when the forward operator is restricted cocoercive by using the stochastic approximation scheme with variance reduction to estimate the expected value of the pseudogradient.

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