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Estimating the Nash Social Welfare for coverage and other submodular valuations (2101.02278v1)
Published 6 Jan 2021 in cs.GT and cs.DM
Abstract: We study the Nash Social Welfare problem: Given $n$ agents with valuation functions $v_i:2{[m]} \rightarrow {\mathbb R}$, partition $[m]$ into $S_1,\ldots,S_n$ so as to maximize $(\prod_{i=1}{n} v_i(S_i)){1/n}$. 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 $\frac{1}{e} (1-\frac{1}{e})2$-approximation of the {\em optimal value} for several classes of submodular valuations: coverage, sums of matroid rank functions, and certain matching-based valuations.