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Average testing and Pareto efficiency

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  • Arieli, Itai
  • Babichenko, Yakov

Abstract

We propose a simple adaptive procedure for playing strategic games: average testing. In this procedure each player sticks to her current strategy if it yields a payoff that exceeds her average payoff by at least some fixed ε>0; otherwise she chooses a strategy at random. We consider generic two-person games where both players play according to the average testing procedure on blocks of k-periods. We demonstrate that for all k large enough, the pair of time-average payoffs converges (almost surely) to the 3ε-Pareto efficient boundary.

Suggested Citation

  • Arieli, Itai & Babichenko, Yakov, 2012. "Average testing and Pareto efficiency," Journal of Economic Theory, Elsevier, vol. 147(6), pages 2376-2398.
    • Handle: RePEc:eee:jetheo:v:147:y:2012:i:6:p:2376-2398
    DOI: 10.1016/j.jet.2012.05.001
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    Cited by:

    1. Jindani, Sam, 2022. "Learning efficient equilibria in repeated games," Journal of Economic Theory, Elsevier, vol. 205(C).
    2. He, Zhongzhi (Lawrence), 2023. "A Gradient-based reinforcement learning model of market equilibration," Journal of Economic Dynamics and Control, Elsevier, vol. 152(C).

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    More about this item

    Keywords

    Pareto efficient boundary; Learning dynamic; Average testing;
    All these keywords.

    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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