arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2007.15520cs.GT
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拥塞博弈中近似纯纳什均衡的改进

Improving approximate pure Nash equilibria in congestion games

Alexander Skopalik, Vipin Ravindran Vijayalakshmi

摘要:

拥塞博弈是一类重要的博弈模型,它描述了不同用户之间的资源分配。由于计算精确甚至近似的纯纳什均衡通常是PLS完备的,Caragiannis等人(2011)提出了一种多项式时间算法,该算法计算具有线性成本函数的博弈的($2 + ε$)近似纯纳什均衡,并进一步计算多项式成本函数的结果。我们表明,这个因素可以改善到$(1.61+ε)$和进一步改善的结果多项式成本函数,通过一个看似简单的修改他们的算法,允许在最佳响应动态过程中使用的成本函数是不同的整体目标函数。有趣的是,我们的修改算法也扩展到有效地计算改进的近似纯纳什均衡在游戏中的任意非递减资源成本函数。此外,我们的分析展示了一个有趣的方法来最佳地计算普遍的负载依赖税,并使用线性规划对偶证明紧界PoA下普遍的税收,例如,2.012线性拥塞游戏和多项式成本函数的进一步结果。虽然我们的方法产生的结果比Bilechte和Vinci(2016)弱,但我们注意到我们的成本函数是局部可计算的,与Bilechte和Vinci(2016)相反,它独立于游戏的实际实例。

英文摘要:

Congestion games constitute an important class of games to model resource allocation by different users. As computing an exact or even an approximate pure Nash equilibrium is in general PLS-complete, Caragiannis et al. (2011) present a polynomial-time algorithm that computes a ($2 + ε$)-approximate pure Nash equilibria for games with linear cost functions and further results for polynomial cost functions. We show that this factor can be improved to $(1.61+ε)$ and further improved results for polynomial cost functions, by a seemingly simple modification to their algorithm by allowing for the cost functions used during the best response dynamics be different from the overall objective function. Interestingly, our modification to the algorithm also extends to efficiently computing improved approximate pure Nash equilibria in games with arbitrary non-decreasing resource cost functions. Additionally, our analysis exhibits an interesting method to optimally compute universal load dependent taxes and using linear programming duality prove tight bounds on PoA under universal taxation, e.g, 2.012 for linear congestion games and further results for polynomial cost functions. Although our approach yield weaker results than that in Bilò and Vinci (2016), we remark that our cost functions are locally computable and in contrast to Bilò and Vinci (2016) are independent of the actual instance of the game.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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