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Learning and Acyclicity in the Market Game

Author

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  • Arthur Dolgopolov

    (Department of Economics, European University Institute)

  • Cesar Martinelli

    (Interdisciplinary Center for Economic Science and Department of Economics, George Mason University)

Abstract

We show that strategic market games, the non-cooperative implementation of a matching with transfers or an assignment game, are weakly acyclic. This property ensures that many common learning algorithms will converge to Nash equilibria in these games, and that the allocation mechanism can therefore be de- centralized. Convergence hinges on the appropriate price clearing rule and has di erent properties for better- and best-response dynamics. We tightly characterize the robustness of this convergence in terms of so-called schedulers for both types of dynamics.

Suggested Citation

  • Arthur Dolgopolov & Cesar Martinelli, 2021. "Learning and Acyclicity in the Market Game," Working Papers 1084, George Mason University, Interdisciplinary Center for Economic Science.
    • Handle: RePEc:gms:wpaper:1084
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    References listed on IDEAS

    as
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