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Reinforcement learning in professional basketball players

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  • Tal Neiman
  • Yonatan Loewenstein
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    Abstract

    Reinforcement learning in complex natural environments is a challenging task because the agent should generalize from the outcomes of actions taken in one state of the world to future actions in different states of the world. The extent to which human experts find the proper level of generalization is unclear. Here we show, using the sequences of field goal attempts made by professional basketball players, that the outcome of even a single field goal attempt has a considerable effect on the rate of subsequent 3 point shot attempts, in line with standard models of reinforcement learning. However, this change in behaviour is associated with negative correlations between the outcomes of successive field goal attempts. These results indicate that despite years of experience and high motivation, professional players overgeneralize from the outcomes of their most recent actions, which leads to decreased performance.

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    File URL: http://ratio.huji.ac.il/sites/default/files/publications/dp593.pdf
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    Bibliographic Info

    Paper provided by The Center for the Study of Rationality, Hebrew University, Jerusalem in its series Discussion Paper Series with number dp593.

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    Length: 16 pages
    Date of creation: Dec 2011
    Date of revision:
    Publication status: Published in Nature Communications 2:569.
    Handle: RePEc:huj:dispap:dp593

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    1. Pavlo Blavatsky, 2003. "Note on "Small Feedback-based Decisions and Their Limited Correspondence to Description-based Decisions"," CERGE-EI Working Papers wp218, The Center for Economic Research and Graduate Education - Economic Institute, Prague.
    2. Ignacio Palacios-Huerta & Oscar Volij, 2006. "Experientia Docet: Professionals Play Minimax in Laboratory Experiments," NajEcon Working Paper Reviews 122247000000001050, www.najecon.org.
    3. Drew Fudenberg & Jean Tirole, 1991. "Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061414, December.
    4. P.-A. Chiappori, 2002. "Testing Mixed-Strategy Equilibria When Players Are Heterogeneous: The Case of Penalty Kicks in Soccer," American Economic Review, American Economic Association, vol. 92(4), pages 1138-1151, September.
    5. Mark Walker & John Wooders, 2001. "Minimax Play at Wimbledon," American Economic Review, American Economic Association, vol. 91(5), pages 1521-1538, December.
    6. 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, vol. 88(4), pages 848-81, September.
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    Cited by:
    1. Gianluigi Mongillo & Hanan Shteingart & Yonatan Loewenstein, 2014. "The Misbehavior of Reinforcement Learning," Discussion Paper Series dp661, The Center for the Study of Rationality, Hebrew University, Jerusalem.
    2. Ofri Raviv & Merav Ahissar & Yonatan Loewenstein, 2012. "How recent history affects perception: the normative approach and its heuristic approximation," Discussion Paper Series dp628, The Center for the Study of Rationality, Hebrew University, Jerusalem.

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