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Minimax across a population of games

Author

Listed:
  • Ido Erev

    (The Technion)

  • Alvin E. Roth

    (Stanford University)

  • Robert Slonim

    () (The University of Sydney)

Abstract

Abstract Most economic experiments designed to test theories carefully choose specific games. This paper reports on an experimental design to evaluate how well the minimax hypothesis describes behavior across a population of games. Past studies suggest that the hypothesis is more accurate the closer the equilibrium is to equal probability play of all actions, but many differences between the designs makes direct comparison impossible. We examine the minimax hypothesis by randomly sampling constant sum games with two players and two actions with a unique equilibrium in mixed strategies. Only varying the games, we find behavior is more consistent with minimax play the closer the mixed strategy equilibrium is to equal probability play of each action. The results are robust over all iterations as well as early and final play. Experimental designs in which the game is a variable allow some conclusions to be drawn that cannot be drawn from more conventional experimental designs.

Suggested Citation

  • Ido Erev & Alvin E. Roth & Robert Slonim, 2016. "Minimax across a population of games," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 2(2), pages 144-156, November.
  • Handle: RePEc:spr:jesaex:v:2:y:2016:i:2:d:10.1007_s40881-016-0029-3 DOI: 10.1007/s40881-016-0029-3
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    References listed on IDEAS

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    2. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, pages 848-881.
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    More about this item

    Keywords

    Game theory; Experimental design; Equilibrium;

    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments

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