Strategyproof and Approximately Maxmin Fair Share Allocation of Chores

TL;DR

This paper explores strategyproof algorithms for fair allocation of indivisible chores based on maxmin share fairness, analyzing different information models and revealing contrasts with goods allocation.

Contribution

It introduces new results on MMS approximation guarantees under strategyproofness for chores, contrasting with existing results for goods.

Findings

Strategyproof algorithms achieve certain MMS approximations for chores.

Differences in MMS approximation ratios between chores and goods.

Positive and negative results depending on information models.

Abstract

We initiate the work on fair and strategyproof allocation of indivisible chores. The fairness concept we consider in this paper is maxmin share (MMS) fairness. We consider three previously studied models of information elicited from the agents: the ordinal model, the cardinal model, and the public ranking model in which the ordinal preferences are publicly known. We present both positive and negative results on the level of MMS approximation that can be guaranteed if we require the algorithm to be strategyproof. Our results uncover some interesting contrasts between the approximation ratios achieved for chores versus goods.