scholarly journals Almost Envy-Freeness in Group Resource Allocation

2019 ◽  
Author(s):  
Maria Kyropoulou ◽  
Warut Suksompong ◽  
Alexandros A. Voudouris
Keyword(s):  
Resource Allocation ◽  
Fair Allocation ◽  
Indivisible Goods ◽  
New Model

We study the problem of fairly allocating indivisible goods between groups of agents using the recently introduced relaxations of envy-freeness. We consider the existence of fair allocations under different assumptions on the valuations of the agents. In particular, our results cover cases of arbitrary monotonic, responsive, and additive valuations, while for the case of binary valuations we fully characterize the cardinalities of two groups of agents for which a fair allocation can be guaranteed with respect to both envy-freeness up to one good (EF1) and envy-freeness up to any good (EFX). Moreover, we introduce a new model where the agents are not partitioned into groups in advance, but instead the partition can be chosen in conjunction with the allocation of the goods. In this model, we show that for agents with arbitrary monotonic valuations, there is always a partition of the agents into two groups of any given sizes along with an EF1 allocation of the goods. We also provide an extension of this result to any number of groups.

scholarly journals Fair Division Under Cardinality Constraints

2018 ◽  
Author(s):  
Arpita Biswas ◽  
Siddharth Barman
Keyword(s):  
Resource Allocation ◽  
Fair Division ◽  
Division Problem ◽  
Fair Allocation ◽  
Indivisible Goods ◽  
Solution Concepts ◽  
Cardinality Constraints ◽  
The Given

We consider the problem of fairly allocating indivisible goods, among agents, under cardinality constraints and additive valuations. In this setting, we are given a partition of the entire set of goods---i.e., the goods are categorized---and a limit is specified on the number of goods that can be allocated from each category to any agent. The objective here is to find a fair allocation in which the subset of goods assigned to any agent satisfies the given cardinality constraints. This problem naturally captures a number of resource-allocation applications, and is a generalization of the well-studied unconstrained fair division problem.  The two central notions of fairness, in the context of fair division of indivisible goods, are envy freeness up to one good (EF1) and the (approximate) maximin share guarantee (MMS). We show that the existence and algorithmic guarantees established for these solution concepts in the unconstrained setting can essentially be achieved under cardinality constraints. Furthermore, focusing on the case wherein all the agents have the same additive valuation, we establish that EF1 allocations exist even under matroid constraints.

scholarly journals Almost Group Envy-free Allocation of Indivisible Goods and Chores

2020 ◽  
Author(s):  
Haris Aziz ◽  
Simon Rey
Keyword(s):  
Resource Allocation ◽  
Polynomial Time ◽  
Fair Allocation ◽  
Indivisible Goods ◽  
Preference Domain ◽  
Polynomial Time Algorithms ◽  
Multi Agent ◽  
Additive Utilities ◽  
Natural Classes ◽  
Allocation Of Indivisible Items

We consider a multi-agent resource allocation setting in which an agent's utility may decrease or increase when an item is allocated. We take the group envy-freeness concept that is well-established in the literature and present stronger and relaxed versions that are especially suitable for the allocation of indivisible items. Of particular interest is a concept called group envy-freeness up to one item (GEF1). We then present a clear taxonomy of the fairness concepts. We study which fairness concepts guarantee the existence of a fair allocation under which preference domain. For two natural classes of additive utilities, we design polynomial-time algorithms to compute a GEF1 allocation. We also prove that checking whether a given allocation satisfies GEF1 is coNP-complete when there are either only goods, only chores or both.

Fair Allocation of Indivisible Goods: Beyond Additive Valuations

2021 ◽  
pp. 103633
Author(s):  
Mohammad Ghodsi ◽  
MohammadTaghi HajiAghayi ◽  
Masoud Seddighin ◽  
Saeed Seddighin ◽  
Hadi Yami
Keyword(s):  
Fair Allocation ◽  
Indivisible Goods

scholarly journals Distributed fair allocation of indivisible goods

2017 ◽  
Vol 242 ◽  
pp. 1-22 ◽  
Author(s):  
Yann Chevaleyre ◽  
Ulle Endriss ◽  
Nicolas Maudet
Keyword(s):  
Fair Allocation ◽  
Indivisible Goods

scholarly journals Fair allocation in a general model with indivisible goods

1998 ◽  
Vol 3 (3) ◽  
pp. 195-213 ◽  
Author(s):  
Carmen Beviá
Keyword(s):  
General Model ◽  
Fair Allocation ◽  
Indivisible Goods

scholarly journals A new model for equitable and efficient resource allocation to schools: the Israeli case

2011 ◽  
Vol 19 (4) ◽  
pp. 341-362 ◽  
Author(s):  
Iris BenDavid-Hadar ◽  
Adrian Ziderman
Keyword(s):  
Resource Allocation ◽  
New Model ◽  
Efficient Resource

scholarly journals Maximin Share Allocations on Cycles

2020 ◽  
Vol 69 ◽  
pp. 613-655
Author(s):  
Miroslaw Truszczynski ◽  
Zbigniew Lonc
Keyword(s):  
Resource Allocation ◽  
Social Choice ◽  
Fundamental Problem ◽  
Fair Division ◽  
Connected Subgraph ◽  
Indivisible Goods ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Share Value

The problem of fair division of indivisible goods is a fundamental problem of resource allocation in multi-agent systems, also studied extensively in social choice. Recently, the problem was generalized to the case when goods form a graph and the goal is to allocate goods to agents so that each agent’s bundle forms a connected subgraph. For the maximin share fairness criterion, researchers proved that if goods form a tree, an allocation offering each agent a bundle of at least her maximin share value always exists. Moreover, it can be found in polynomial time. In this paper we consider the problem of maximin share allocations of goods on a cycle. Despite the simplicity of the graph, the problem turns out to be significantly harder than its tree version. We present cases when maximin share allocations of goods on cycles exist and provide in this case results on allocations guaranteeing each agent a certain fraction of her maximin share. We also study algorithms for computing maximin share allocations of goods on cycles.

scholarly journals Fair and Efficient Resource Allocation with Partial Information

2021 ◽  
Author(s):  
Daniel Halpern ◽  
Nisarg Shah
Keyword(s):  
Resource Allocation ◽  
Social Welfare ◽  
Partial Information ◽  
Fundamental Problem ◽  
Full Information ◽  
Indivisible Goods ◽  
Preference Information ◽  
Efficient Resource

We study the fundamental problem of allocating indivisible goods to agents with additive preferences. We consider eliciting from each agent only a ranking of her k most preferred goods instead of her full cardinal valuations. We characterize the amount of preference information that must be elicited in order to satisfy envy-freeness up to one good and approximate maximin share guarantee, two widely studied fairness notions. We also analyze the multiplicative loss in social welfare incurred due to the lack of full information with and without fairness requirements.

Fair Allocation of Indivisible Goods: Improvement

2021 ◽  
Author(s):  
Mohammad Ghodsi ◽  
Mohammad Taghi Hajiaghayi ◽  
Masoud Seddighin ◽  
Saeed Seddighin ◽  
Hadi Yami
Keyword(s):  
Assignment Problem ◽  
Competitive Equilibrium ◽  
Fundamental Problem ◽  
Impossibility Result ◽  
Utility Functions ◽  
Fair Allocation ◽  
Indivisible Goods ◽  
Approximation Result ◽  
Combinatorial Assignment

We study the problem of fair allocation for indivisible goods. We use the maximin share paradigm introduced by Budish [Budish E (2011) The combinatorial assignment problem: Approximate competitive equilibrium from equal incomes. J. Political Econom. 119(6):1061–1103.] as a measure of fairness. Kurokawa et al. [Kurokawa D, Procaccia AD, Wang J (2018) Fair enough: Guaranteeing approximate maximin shares. J. ACM 65(2):8.] were the first to investigate this fundamental problem in the additive setting. They showed that in delicately constructed examples, not everyone can obtain a utility of at least her maximin value. They mitigated this impossibility result with a beautiful observation: no matter how the utility functions are made, we always can allocate the items to the agents to guarantee each agent’s utility is at least 2/3 of her maximin value. They left open whether this bound can be improved. Our main contribution answers this question in the affirmative. We improve their approximation result to a 3/4 factor guarantee.

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