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Strategic teaching and learning in games

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  • Burkhard Schipper

    (Department of Economics, University of California Davis)

Abstract

It is known that there are uncoupled learning heuristics leading to Nash equilibrium in all finite games. Why should players use such learning heuristics and where could they come from? We show that there is no uncoupled learning heuristic leading to Nash equilibrium in all finite games that a player has an incentive to adopt, that would be "evolutionary stable" or that "could learn itself". Rather, a player has an incentive to strategically teach such a learning opponent in order secure at least the Stackelberg leader payoff. The impossibility result remains intact when restricted to the classes of generic games, two-player games, potential games, games with strategic complements or 2x2 games, in which learning is known to be "nice". More generally, it also applies to uncoupled learning heuristics leading to correlated equilibria, rationalizable outcomes, iterated admissible outcomes, or minimal curb sets. A possibility result restricted to "strategically trivial" games fails if some generic games outside this class are considered as well.

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  • Burkhard Schipper, 2015. "Strategic teaching and learning in games," Working Papers 152, University of California, Davis, Department of Economics.
  • Handle: RePEc:cda:wpaper:152
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    Cited by:

    1. Heller, Yuval & Mohlin, Erik, 2019. "Coevolution of deception and preferences: Darwin and Nash meet Machiavelli," Games and Economic Behavior, Elsevier, vol. 113(C), pages 223-247.
    2. Ioannis Kordonis & Alexandros C. Charalampidis & George P. Papavassilopoulos, 2018. "Pretending in Dynamic Games, Alternative Outcomes and Application to Electricity Markets," Dynamic Games and Applications, Springer, vol. 8(4), pages 844-873, December.
    3. Jindani, Sam, 2022. "Learning efficient equilibria in repeated games," Journal of Economic Theory, Elsevier, vol. 205(C).
    4. Burkhard C. Schipper, 2019. "Dynamic Exploitation of Myopic Best Response," Dynamic Games and Applications, Springer, vol. 9(4), pages 1143-1167, December.

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    More about this item

    Keywords

    Learning in games; learning heuristics; learning rules; interactive learning; uncoupled learning; meta-learning; reputation; Nash equilibrium; correlated equilibrium; rationalizability; iterated admissibility; minimal curb sets; dominance solvable games; common interest games;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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