游到沉没计算游戏的极限

Rashida Hakim, Jason Milionis, Christos Papadimitriou, Georgios Piliouras
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引用次数: 0

摘要

2023 年期间,有两个关于博弈动力学极限行为的有趣结果得到了证明:首先,证明了有一种博弈,其动力学不收敛于纳什均衡。第二,证明了博弈的汇均衡充分捕捉了自然博弈动力学的极限行为。给定任何正态博弈和任何博弈的先验分布,我们研究了计算一类自然动态的渐近行为的问题,这类自然动态被称为噪声复制动态,是博弈水槽均衡的极限分布。当先验分布具有纯策略支持时,我们证明可以高效地计算这个分布,计算时间与最佳响应图的大小接近线性。当分布可以采样时--例如,如果它是所有混合策略剖面的均匀分布--我们通过实验证明,通过采样和模拟,可以相当精确地估计出合理大型博弈的极限分布。
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Swim till You Sink: Computing the Limit of a Game
During 2023, two interesting results were proven about the limit behavior of game dynamics: First, it was shown that there is a game for which no dynamics converges to the Nash equilibria. Second, it was shown that the sink equilibria of a game adequately capture the limit behavior of natural game dynamics. These two results have created a need and opportunity to articulate a principled computational theory of the meaning of the game that is based on game dynamics. Given any game in normal form, and any prior distribution of play, we study the problem of computing the asymptotic behavior of a class of natural dynamics called the noisy replicator dynamics as a limit distribution over the sink equilibria of the game. When the prior distribution has pure strategy support, we prove this distribution can be computed efficiently, in near-linear time to the size of the best-response graph. When the distribution can be sampled -- for example, if it is the uniform distribution over all mixed strategy profiles -- we show through experiments that the limit distribution of reasonably large games can be estimated quite accurately through sampling and simulation.
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