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

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

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    Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 653.

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    Date of creation: 23 Apr 2013
    Date of revision:
    Handle: RePEc:oxf:wpaper:653
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    1. R. Cookson, 2000. "Framing Effects in Public Goods Experiments," Experimental Economics, Springer, vol. 3(1), pages 55-79, June.
    2. Ananish Chaudhuri, 2011. "Sustaining cooperation in laboratory public goods experiments: a selective survey of the literature," Experimental Economics, Springer, vol. 14(1), pages 47-83, March.
    3. Ralph-C Bayer & Elke Renner & Rupert Sausbruber, 2012. "Confusion and Learning in the Voluntary Contributions Game," Discussion Papers 2012-18, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    4. Sergiu Hart & Andreu Mas-Colell, 2004. "Stochastic Uncoupled Dynamics and Nash Equilibrium," Discussion Paper Series dp371, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    5. 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.
    6. Fabrizio Germano & Gábor Lugosi, 2004. "Global Nash convergence of Foster and Young's regret testing," Economics Working Papers 788, Department of Economics and Business, Universitat Pompeu Fabra.
    7. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer, vol. 10(2), pages 171-178, June.
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