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The General Graph Matching Game: Approximate Core

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  • Vijay V. Vazirani

Abstract

The classic paper of Shapley and Shubik \cite{Shapley1971assignment} characterized the core of the assignment game using ideas from matching theory and LP-duality theory and their highly non-trivial interplay. Whereas the core of this game is always non-empty, that of the general graph matching game can be empty. This paper salvages the situation by giving an imputation in the $2/3$-approximate core for the latter. This bound is best possible, since it is the integrality gap of the natural underlying LP. Our profit allocation method goes further: the multiplier on the profit of an agent is often better than ${2 \over 3}$ and lies in the interval $[{2 \over 3}, 1]$, depending on how severely constrained the agent is. Next, we provide new insights showing how discerning core imputations of an assignment games are by studying them via the lens of complementary slackness. We present a relationship between the competitiveness of individuals and teams of agents and the amount of profit they accrue in imputations that lie in the core, where by {\em competitiveness} we mean whether an individual or a team is matched in every/some/no maximum matching. This also sheds light on the phenomenon of degeneracy in assignment games, i.e., when the maximum weight matching is not unique. The core is a quintessential solution concept in cooperative game theory. It contains all ways of distributing the total worth of a game among agents in such a way that no sub-coalition has incentive to secede from the grand coalition. Our imputation, in the $2/3$-approximate core, implies that a sub-coalition will gain at most a $3/2$ factor by seceding, and less in typical cases.

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  • Vijay V. Vazirani, 2021. "The General Graph Matching Game: Approximate Core," Papers 2101.07390, arXiv.org, revised Jul 2021.
  • Handle: RePEc:arx:papers:2101.07390
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    References listed on IDEAS

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    1. Johan Karlander & Kimmo Eriksson, 2001. "Stable outcomes of the roommate game with transferable utility," International Journal of Game Theory, Springer;Game Theory Society, vol. 29(4), pages 555-569.
    2. M. L. Balinski, 1965. "Integer Programming: Methods, Uses, Computations," Management Science, INFORMS, vol. 12(3), pages 253-313, November.
    3. Péter Biró & Walter Kern & Daniël Paulusma, 2012. "Computing solutions for matching games," International Journal of Game Theory, Springer;Game Theory Society, vol. 41(1), pages 75-90, February.
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    Cited by:

    1. Ioannis Panageas & Thorben Trobst & Vijay V. Vazirani, 2021. "Time-Efficient Algorithms for Nash-Bargaining-Based Matching Market Models," Papers 2106.02024, arXiv.org, revised Nov 2024.
    2. Han Xiao & Qizhi Fang, 2022. "Population monotonicity in matching games," Journal of Combinatorial Optimization, Springer, vol. 43(4), pages 699-709, May.
    3. Han Xiao & Tianhang Lu & Qizhi Fang, 2021. "Approximate Core Allocations for Multiple Partners Matching Games," Papers 2107.01442, arXiv.org, revised Oct 2021.

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