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Learning in a Black Box: Trial-and-Error in Voluntary Contribuitons Games

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  • H Peyton Young
  • H.H. Nax
  • M.N. Burton-Chellew
  • S.A. West

Abstract

Many interactive environments can be represented as games, but they are so large and complex that individual players are in the dark about others' actions and the payoff structure. This paper analyzes learning behavior in such 'black box' environments, where players' only source of information is their own history of actions taken and payoffs received. Specifically we study voluntary contributions games. We identify two robust features of the players' learning dynamics: search volatility and trend-following. These features are clearly present when players have no information about the game; but also when players have full informaiton. Convergence to Nash equilibrium occurs at about the same rate in both situations.

Suggested Citation

  • H Peyton Young & H.H. Nax & M.N. Burton-Chellew & S.A. West, 2013. "Learning in a Black Box: Trial-and-Error in Voluntary Contribuitons Games," Economics Series Working Papers 653, University of Oxford, Department of Economics.
  • Handle: RePEc:oxf:wpaper:653
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    File URL: http://www.economics.ox.ac.uk/materials/papers/12706/paper653.pdf
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    References listed on IDEAS

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    1. Hart, Sergiu & Mas-Colell, Andreu, 2006. "Stochastic uncoupled dynamics and Nash equilibrium," Games and Economic Behavior, Elsevier, vol. 57(2), pages 286-303, November.
    2. R. Cookson, 2000. "Framing Effects in Public Goods Experiments," Experimental Economics, Springer;Economic Science Association, vol. 3(1), pages 55-79, June.
    3. Ralph-C. Bayer & Elke Renner & Rupert Sausgruber, 2013. "Confusion and learning in the voluntary contributions game," Experimental Economics, Springer;Economic Science Association, vol. 16(4), pages 478-496, December.
    4. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    5. Germano, Fabrizio & Lugosi, Gabor, 2007. "Global Nash convergence of Foster and Young's regret testing," Games and Economic Behavior, Elsevier, vol. 60(1), pages 135-154, July.
    6. Ananish Chaudhuri, 2011. "Sustaining cooperation in laboratory public goods experiments: a selective survey of the literature," Experimental Economics, Springer;Economic Science Association, vol. 14(1), pages 47-83, March.
    7. Sergiu Hart & Andreu Mas-Colell, 2003. "Uncoupled Dynamics Do Not Lead to Nash Equilibrium," American Economic Review, American Economic Association, vol. 93(5), pages 1830-1836, December.
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    More about this item

    Keywords

    learning; information; public goods games;

    JEL classification:

    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods

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