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A Simpler Approach to the EFX Problem Envy-freeness up to any item (EFX) has emerged as a compelling fairness notion in discrete fair division. However, its existence remains one of the biggest open problems in the field. In a breakthrough, Chaudhury et al. (2020) establish the existence of EFX allocations for three agents with additive valuations through intricate case analysis. The paper “EFX: A Simpler Approach and an (Almost) Optimal Guarantee via Rainbow Cycle Number” by Akrami, Alon, Chaudhury, Garg, Mehlhorn, and Mehta offers a simpler approach for improving the EFX guarantee. They demonstrate the existence of EFX allocations for three agents when at least one has additive valuations (whereas the other two have general monotone valuations). Additionally, they nearly resolve a conjecture regarding the rainbow cycle number, leading to an (almost) tight bound for the existence of approximate EFX allocations with few unallocated items achievable through this approach. 

We consider the problem of fairly allocating a set of indivisible goods among n agents with additive valuations, using the popular fairness notion of maximin share (MMS). Since MMS allocations do not always exist, a series of works provided existence and algorithms for approximate MMS allocations. The Garg-Taki algorithm gives the current best approximation factor of (3/4 + 1/12n). Most of these results are based on complicated analyses, especially those providing better than 2/3 factor. Moreover, since no tight example is known of the Garg-Taki algorithm, it is unclear if this is the best factor of this approach. In this paper, we significantly simplify the analysis of this algorithm and also improve the existence guarantee to a factor of (3/4 + min(1/36, 3/(16n-4))). For small n, this provides a noticeable improvement. Furthermore, we present a tight example of this algorithm, showing that this may be the best factor one can hope for with the current techniques. 

We study fair division of indivisible chores among n agents with additive disutility functions. Two well-studied fairness notions for indivisible items are envy-freeness up to one/any item (EF1/EFX) and the standard notion of economic efficiency is Pareto optimality (PO). There is a noticeable gap between the results known for both EF1 and EFX in the goods and chores settings. The case of chores turns out to be much more challenging. We reduce this gap by providing slightly relaxed versions of the known results on goods for the chores setting. Interestingly, our algorithms run in polynomial time, unlike their analogous versions in the goods setting.We introduce the concept of k surplus in the chores setting which means that up to k more chores are allocated to the agents and each of them is a copy of an original chore. We present a polynomial-time algorithm which gives EF1 and PO allocations with n-1 surplus.We relax the notion of EFX slightly and define tEFX which requires that the envy from agent i to agent j is removed upon the transfer of any chore from the i's bundle to j's bundle. We give a polynomial-time algorithm that in the chores case for 3 agents returns an allocation which is either proportional or tEFX. Note that proportionality is a very strong criterion in the case of indivisible items, and hence both notions we guarantee are desirable.