We study the problem of fairly allocating a set of indivisible goods among agents with bivalued submodular valuations -- each good provides a marginal gain of either $a$ or $b$ ($a < b$) and goods have decreasing marginal gains. This is a natural generalization of two well-studied valuation classes -- bivalued additive valuations and binary submodular valuations. We present a simple sequential algorithmic framework, based on the recently introduced Yankee Swap mechanism, that can be adapted to compute a variety of solution concepts, including leximin, max Nash welfare (MNW) and $p$-mean welfare maximizing allocations when $a$ divides $b$. This result is complemented by an existing result on the computational intractability of leximin and MNW allocations when $a$ does not divide $b$. We further examine leximin and MNW allocations with respect to two well-known properties -- envy freeness and the maximin share guarantee. On envy freeness, we show that neither the leximin nor the MNW allocation is guaranteed to be envy free up to one good (EF1). This is surprising since for the simpler classes of bivalued additive valuations and binary submodular valuations, MNW allocations are known to be envy free up to any good (EFX). On the maximin share guarantee, we show that MNW and leximin allocations guarantee each agent $\frac14$ and $\frac{a}{b+3a}$ of their maximin share respectively when $a$ divides $b$. This fraction improves to $\frac13$ and $\frac{a}{b+2a}$ respectively when agents have bivalued additive valuations.
翻译:-
将好和更好的物品分配给具有子模估值的代理