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arXiv 1806.04746cs.GT
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Fisher市场中分布式更新的动力学

Dynamics of Distributed Updating in Fisher Markets

Yun Kuen Cheung, Richard Cole, Yixin Tao

摘要:

算法博弈论的一个主要目标是从算法和复杂性的角度证明均衡概念的合理性。一个吸引人的方法是确定自然的分布式算法,快速收敛到一个平衡。本文建立了购买者具有CES效用函数的Fisher市场中比例反应的两种推广的新的收敛性结果。出发点分别是一个新的凸和一个新的凹凸制定这样的市场。这两个概括对应于适用于这些配方的镜像下降算法。我们的几个新的结果是一个后果的新概念的强Bregman凸性和强Bregman凹凸函数,以及相关的线性收敛速度,这可能是独立的利益。在其他结果中,我们分析了阻尼广义比例响应,并显示了一个线性收敛速度在费雪市场的买方,其效用函数涵盖了整个频谱的CES公用事业除了极端的线性和Leontief公用事业,当这些公用事业包括在内,我们得到了经验O(1/T)收敛速度。

英文摘要:

A major goal in Algorithmic Game Theory is to justify equilibrium concepts from an algorithmic and complexity perspective. One appealing approach is to identify natural distributed algorithms that converge quickly to an equilibrium. This paper established new convergence results for two generalizations of Proportional Response in Fisher markets with buyers having CES utility functions. The starting points are respectively a new convex and a new convex-concave formulation of such markets. The two generalizations correspond to suitable mirror descent algorithms applied to these formulations. Several of our new results are a consequence of new notions of strong Bregman convexity and of strong Bregman convex-concave functions, and associated linear rates of convergence, which may be of independent interest. Among other results, we analyze a damped generalized Proportional Response and show a linear rate of convergence in a Fisher market with buyers whose utility functions cover the full spectrum of CES utilities aside the extremes of linear and Leontief utilities; when these utilities are included, we obtain an empirical O(1/T) rate of convergence.

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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