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- W3087254560 abstract "A two-sided market consists of two sets of agents, each of whom have preferences over the other (Airbnb, Upwork, Lyft, Uber, etc.). We propose and analyze a repeated matching problem, where some set of matches occur on each time step, and our goal is to ensure fairness with respect to the cumulative allocations over an infinite time horizon. Our main result is a polynomial-time algorithm for additive, symmetric (v_i(j) = v_j(i)), and binary (v_i(j) in {a,1}) valuations that both (1) guarantees up to a single match (EF1) and (2) selects a maximum weight matching on each time step. Thus for this class of fairness can be achieved without sacrificing economic efficiency. This result holds even for valuations, i.e., valuations that change over time. Although symmetry is a strong assumption, we show that this result cannot be extended to asymmetric binary valuations: (1) and (2) together are impossible even when valuations do not change over time, and for dynamic even (1) alone is impossible. To our knowledge, this is the first analysis of envy-freeness in a repeated matching setting." @default.
- W3087254560 created "2020-09-25" @default.
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- W3087254560 date "2020-09-20" @default.
- W3087254560 modified "2023-09-27" @default.
- W3087254560 title "Almost Envy-free Repeated Matching in Two-sided Markets." @default.
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