NeurIPS2023
Randomized and Deterministic Maximin-share Approximations for Fractionally Subadditive Valuations
Hannaneh Akrami, Kurt Mehlhorn, Masoud Seddighin, Golnoosh Shahkarami
被引用 23 次
摘要
We consider the problem of guaranteeing maximin-share (MMS) when allocating a set of indivisible items to a set of agents with fractionally subadditive (XOS) valuations. For XOS valuations, it has been previously shown that for some instances no allocation can guarantee a fraction better than of maximin-share to all the agents. Also, a deterministic allocation exists that guarantees of the maximin-share of each agent. Our results involve both deterministic and randomized allocations. On the deterministic side, we improve the best approximation guarantee for fractionally subadditive valuations to . We develop new ideas on allocating large items in our allocation algorithm which might be of independent interest. Furthermore, we investigate randomized algorithms and the Best-of-both-worlds fairness guarantees. We propose a randomized allocation that is -MMS ex-ante and -MMS ex-post for XOS valuations. Moreover, we prove an upper bound of on the ex-ante guarantee for this class of valuations.