Fairness Towards Groups of Agents in the Allocation of Indivisible Items

Abstract : In this paper, we study the problem of matching a set of items to a set of agents partitioned into types so as to balance fairness towards the types against overall utility/efficiency. We extend multiple desirable properties of indivisible goods allocation to our model and investigate the possibility and hardness of achieving combinations of these properties, e.g. we prove that maximizing utilitarian social welfare under constraints of typewise envy-freeness up to one item (TEF1) is computa-tionally intractable. We also define a new concept of waste for this setting, show experimentally that augmenting an existing algorithm with a marginal utility maximization heuristic can produce a TEF1 solution with reduced waste, and also provide a polynomial-time algorithm for computing a non-wasteful TEF1 allocation for binary agent-item utilities.
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Nawal Benabbou, Mithun Chakraborty, Edith Elkind, Yair Zick. Fairness Towards Groups of Agents in the Allocation of Indivisible Items. The 28th International Joint Conference on Artificial Intelligence (IJCAI'19), Aug 2019, MACAO, China. ⟨hal-02155024⟩

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