We consider the problem of fair allocation of indivisible goods to agents with submodular valuation functions, where agents may have either equal entitlements or arbitrary (possibly unequal) entitlements. We focus on share-based fairness notions, specifically, the maximin share (MMS) for equal entitlements and the anyprice share (APS) for arbitrary entitlements, and design allocation algorithms that give each agent a bundle of value at least some constant fraction of her share value. For the equal entitlement case (and submodular valuations), Ghodsi, Hajiaghayi, Seddighin, Seddighin, and Yami [EC 2018] designed a polynomial-time algorithm for $\frac{1}{3}$-maximin-fair allocation. We improve this result in two different ways. We consider the general case of arbitrary entitlements, and present a polynomial time algorithm that guarantees submodular agents $\frac{1}{3}$ of their APS. For the equal entitlement case, we improve the approximation ratio and obtain $\frac{10}{27}$-maximin-fair allocations. Our algorithms are based on designing strategies for a certain bidding game that was previously introduced by Babaioff, Ezra and Feige [EC 2021].
翻译:我们研究了将不可分割物品分配给拥有次模型估值函数的代理的公平性分配问题,其中代理可以拥有相等的配额,也可以有任意(可能不相等)的配额。我们聚焦于基于份额的公平性概念,特别是相等配额情况下的最小份额(MMS)和任意配额情况下的任意定价份额(APS),并设计了分配算法,使每个代理的价值至少达到其份额价值的某个常数比例。对于相等的配额情况(和次模型估值),Ghodsi,Hajiaghayi,Seddighin,Seddighin和Yami [EC 2018]设计了一种$\frac{1}{3}$-最大最小公平分配的多项式时间算法。我们以两种不同的方式改进了这个结果。我们考虑了任意配额的一般情况,并提出了一种多项式时间算法,保证次模型代理达到其APS的$\frac{1}{3}$。对于相等的配额情况,我们改进了逼近比率,并获得了$\frac{10}{27}$-最大最小公平分配。我们的算法是基于Babaioff,Ezra和Feige [EC 2021]先前引入的某个竞标博弈策略而设计的。