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Estimating the Nash Social Welfare for coverage and other submodular valuations

Published 6 Jan 2021 in cs.GT and cs.DM | (2101.02278v1)

Abstract: We study the Nash Social Welfare problem: Given nn agents with valuation functions vi:2<sup>[m]</sup>Rv_i:2<sup>{[m]}</sup> \rightarrow {\mathbb R}, partition [m][m] into S1,,SnS_1,\ldots,S_n so as to maximize (i=1<sup>n</sup>vi(Si))<sup>1/n(\prod_{i=1}<sup>{n}</sup> v_i(S_i))<sup>{1/n}. The problem has been shown to admit a constant-factor approximation for additive, budget-additive, and piecewise linear concave separable valuations; the case of submodular valuations is open. We provide a 1e(11e)<sup>2\frac{1}{e} (1-\frac{1}{e})<sup>2-approximation of the {\em optimal value} for several classes of submodular valuations: coverage, sums of matroid rank functions, and certain matching-based valuations.

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