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Approximate Pure Nash Equilibria in Weighted Congestion Games: Existence, Efficient Computation, and Structure

机译:加权拥塞博弈中的近似纯纳什均衡:存在性,有效计算和结构

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We consider structural and algorithmic questions related to the Nash dynamics of weighted congestion games. In weighted congestion games with linear latency functions, the existence of pure Nash equilibria is guaranteed by potential function arguments. Unfortunately, this proof of existence is inefficient and computing pure Nash equilibria in such games is a PLS-hard problem even when all players have unit weights. The situation gets worse when superlinear (e.g., quadratic) latency functions come into play; in this case, the Nash dynamics of the game may contain cycles and pure Nash equilibria may not even exist. Given these obstacles, we consider approximate pure Nash equilibria as alternative solution concepts. Do such equilibria exist? And if so, can we compute them efficiently? We provide positive answers to both questions for weighted congestion games with polynomial latency functions by exploiting an "approximation" of such games by a new class of potential games that we call Ψ-games. This allows us to show that these games have d!-approximate pure Nash equilibria, where d is the maximum degree of the latency functions. Our main technical contribution is an efficient algorithm for computing O(1)-approximate pure Nash equilibria when d is a constant. For games with linear latency functions, the approximation guarantee is 3+5~(1/2)/2 + O(γ) for arbitrarily small γ > 0; for latency functions with maximum degree d≥2, it is d~(2d+o(d)). The running time is polynomial in the number of bits in the representation of the game and 1/γ. As a byproduct of our techniques, we also show the following interesting structural statement for weighted congestion games with polynomial latency functions of maximum degree d ≥ 2: polynomially-long sequences of best-response moves from any initial state to a d~(O(d~2)-approximate pure Nash equilibrium exist and can be efficiently identified in such games as long as d is constant. To the best of our knowledge, these are the first positive algorithmic results for approximate pure Nash equilibria in weighted congestion games. Our techniques significantly extend our recent work on unweighted congestion games through the use of Ψ-games. The concept of approximating non-potential games by potential ones is interesting in itself and might have further applications.
机译:我们考虑与加权拥挤博弈的纳什动力学有关的结构和算法问题。在具有线性等待时间函数的加权拥塞游戏中,潜在函数参数可确保存在纯纳什均衡。不幸的是,这种存在的证明是无效的,并且即使在所有玩家都具有单位权重的情况下,在此类游戏中计算纯纳什均衡也是PLS难题。当超线性(例如,二次)等待时间函数起作用时,情况变得更糟。在这种情况下,游戏的纳什动力学可能包含周期,甚至可能不存在纯粹的纳什均衡。考虑到这些障碍,我们将近似纯纳什均衡作为替代解决方案的概念。这样的平衡存在吗?如果是这样,我们可以有效地计算它们吗?对于具有多项式等待时间函数的加权拥塞游戏,我们通过使用这类潜在游戏(称为“Ψ”游戏)的“近似值”,为这两个问题提供了肯定的答案。这使我们能够证明这些游戏具有d!-近似纯纳什均衡,其中d是等待时间函数的最大程度。我们的主要技术贡献是当d为常数时用于计算O(1)近似纯Nash平衡的有效算法。对于具有线性等待时间函数的游戏,对于任意小的γ> 0,近似保证为3 + 5〜(1/2)/ 2 + O(γ);对于最大度数d≥2的等待时间函数,它是d〜(2d + o(d))。运行时间是游戏表示形式的位数和1 /γ的多项式。作为我们技术的副产品,我们还显示了以下有趣的结构性陈述,用于加权拥塞游戏,其多项式潜伏函数的最大度为d≥2:最佳响应的多项式长序列从任何初始状态移动到ad〜(O(d 〜2)-近似纯Nash均衡存在并且只要d为常数就可以有效地识别出来,据我们所知,这是加权拥挤博弈中近似纯Nash均衡的第一个积极算法结果。通过使用Ψ游戏极大地扩展了我们最近在非加权拥塞游戏上的工作,用潜在游戏近似非潜在游戏的概念本身很有趣,并且可能会进一步应用。

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