An Algorithm for the Assignment Game Beyond Additive Valuations

Eric Balkanski, Christopher En, Yuri Faenza
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Abstract

The assignment game, introduced by Shapley and Shubik (1971), is a classic model for two-sided matching markets between buyers and sellers. In the original assignment game, it is assumed that payments lead to transferable utility and that buyers have unit-demand valuations for the items being sold. Two important and mostly independent lines of work have studied more general settings with imperfectly transferable utility and gross substitutes valuations. Multiple efficient algorithms have been proposed for computing a competitive equilibrium, the standard solution concept in assignment games, in these two settings. Our main result is an efficient algorithm for computing competitive equilibria in a setting with both imperfectly transferable utility and gross substitutes valuations. Our algorithm combines augmenting path techniques from maximum matching and algorithms for matroid intersection. We also show that, in a mild generalization of our model, computing a competitive equilibrium is NP-hard.
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超越加法估值的分配博弈算法
转让博弈由 Shapley 和 Shubik(1971 年)提出,是买卖双方匹配市场的经典模型。在最初的分配博弈中,假定支付会带来可转移效用,且买方对所售物品具有单位需求估值。有两个重要且大多独立的研究方向,研究了效用不完全可转移和总替代品估值的更一般情况。在这两种情况下,人们提出了多种高效算法来计算竞争性均衡,即分配博弈中的标准解概念。我们的主要成果是一种高效算法,可以在效用不完全可转移和总替代品估值两种情况下计算竞争性均衡。我们的算法结合了最大匹配中的增强路径技术和矩阵交集算法。我们还证明,在我们模型的温和广义化中,计算竞争性均衡是 NP 难的。
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