Fair division provides a rich computational and mathematical framework for the allocation of indivisible goods, which has given rise to numerous fairness concepts and their relaxations. In recent years, much attention has been given to theoretical and computational aspects of various fairness concepts. Nonetheless, the choice of which fairness concept is in practice perceived to be fairer by individuals is not well understood. We consider two conceptually different relaxations of envy-freeness and investigate how individuals perceive the induced allocations as fair. In particular, we examine a well-studied relaxation of envy-freeness up to one good (EF1) which is based on counterfactual thinking that any pairwise envy can be eliminated by the hypothetical removal of a single good from the envied agent's bundle. In contrast, a recently proposed epistemic notion, namely envy-freeness up to $k$ hidden goods (HEF-$k$), provides a relaxation by hiding information about a small subset of $k$ goods. Through various crowdsourcing experiments, we empirically demonstrate that allocations achieved by withholding information are perceived to be fairer compared to two variants of EF1.
翻译:公平分配为不可分割商品的分配提供了丰富的计算和数学框架,这引起了许多公平概念及其放松。近年来,人们非常注意各种公平概念的理论和计算方面。然而,人们并不十分理解在实际上认为公平概念在个人看来更为公平的理论和计算方面。我们认为,在概念上不同地放宽了嫉妒的自由度,并调查了个人如何认为诱发的分配是公平的。特别是,我们审视了经过深思熟虑的无妒忌至一种商品(EF1)的放松,这种放松是基于反现实的思维,即假设从诱饵剂的包里取出一种单一的商品可以消除任何配对的嫉妒。相比之下,最近提出的一个缩略论概念,即无妒忌可达1美元隐匿货物(HEF-k$),通过隐藏关于一小部分美元货物的信息而提供了放松。通过各种众包实验,我们从经验上证明,与EF1的两种变式相比,通过隐瞒信息而实现的分配被认为更为公平。