arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1902.01754cs.GT
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求线性Arrow-Debreu市场均衡的交替算法

An Alternating Algorithm for Finding Linear Arrow-Debreu Market Equilibria

Po-An Chen, Chi-Jen Lu, Yu-Sin Lu

摘要:

受镜像下降算法收敛于线性Fisher市场均衡的结果的启发,人们自然会考虑为代理设计动态(特别是迭代算法)以达到线性Arrow-Debreu市场均衡。Jain将线性Arrow-Debreu市场的均衡计算简化为双射市场的均衡计算,在双射市场中,每个人都是一种商品的卖家和一捆商品的买家。在本文中,我们设计了一个算法来计算线性双射市场均衡,基于求解有理凸规划由Devanur等人制定。该算法反复交替的梯度下降式更新的一个步骤和分布式优化的一个步骤,利用这种凸规划的属性。收敛性可以通过不同于线性Fisher市场均衡分析的新分析来保证。

英文摘要:

Motivated by the convergence result of mirror-descent algorithms to market equilibria in linear Fisher markets, it is natural for one to consider designing dynamics (specifically, iterative algorithms) for agents to arrive at linear Arrow-Debreu market equilibria. Jain reduced equilibrium computation in linear Arrow-Debreu markets to the equilibrium computation in bijective markets, where everyone is a seller of only one good and a buyer for a bundle of goods. In this paper, we design an algorithm for computing linear bijective market equilibrium, based on solving the rational convex program formulated by Devanur et al. The algorithm repeatedly alternates between a step of gradient-descent-like updates and a distributed step of optimization exploiting the property of such convex program. Convergence can be ensured by a new analysis different from the analysis for linear Fisher market equilibria.

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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