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Journal Articles Artificial Intelligence Year : 2017

Distributed Fair Allocation of Indivisible Goods

Yann Chevaleyre
Ulle Endriss
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Nicolas Maudet


Distributed mechanisms for allocating indivisible goods are mechanisms lacking central control, in which agents can locally agree on deals to exchange some of the goods in their possession. We study convergence properties for such distributed mechanisms when used as fair division procedures. Specifically, we identify sets of assumptions under which any sequence of deals meeting certain conditions will converge to a proportionally fair allocation and to an envy-free allocation, respectively. We also introduce an extension of the basic framework where agents are vertices of a graph representing a social network that constrains which agents can interact with which other agents, and we prove a similar convergence result for envy-freeness in this context. Finally, when not all assumptions guaranteeing envy-freeness are satisfied, we may want to minimise the degree of envy exhibited by an outcome. To this end, we introduce a generic framework for measuring the degree of envy in a society and establish the computational complexity of checking whether a given scenario allows for a deal that is beneficial to every agent involved and that will reduce overall envy.
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hal-01359645 , version 1 (27-09-2016)



Yann Chevaleyre, Ulle Endriss, Nicolas Maudet. Distributed Fair Allocation of Indivisible Goods. Artificial Intelligence, 2017, 242, pp.1--22. ⟨10.1016/j.artint.2016.09.005⟩. ⟨hal-01359645⟩
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