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Title: Improving Nash Social Welfare Approximations
We consider the problem of fairly allocating a set of indivisible goods among n agents. Various fairness notions have been proposed within the rapidly growing field of fair division, but the Nash social welfare (NSW) serves as a focal point. In part, this follows from the ‘unreasonable’ fairness guarantees provided, in the sense that a max NSW allocation meets multiple other fairness metrics simultaneously, all while satisfying a standard economic concept of efficiency, Pareto optimality. However, existing approximation algorithms fail to satisfy all of the remarkable fairness guarantees offered by a max NSW allocation, instead targeting only the specific NSW objective. We address this issue by presenting a 2 max NSW, Prop-1, 1/(2n) MMS, and Pareto optimal allocation in strongly polynomial time. Our techniques are based on a market interpretation of a fractional max NSW allocation. We present novel definitions of fairness concepts in terms of market prices, and design a new scheme to round a market equilibrium into an integral allocation in a way that provides most of the fairness properties of an integral max NSW allocation.  more » « less
Award ID(s):
1755619
NSF-PAR ID:
10156567
Author(s) / Creator(s):
;
Date Published:
Journal Name:
Journal of Artificial Intelligence Research
Volume:
68
ISSN:
1076-9757
Page Range / eLocation ID:
225 to 245
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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