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Reinforcement learning in professional basketball players

Author

Listed:
  • Tal Neiman

    (The Interdisciplinary Center for Neural Computation and Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem)

  • Yonatan Loewenstein

    (The Interdisciplinary Center for Neural Computation and Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem
    Center for the Study of Rationality, The Hebrew University of Jerusalem)

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.

Suggested Citation

  • Tal Neiman & Yonatan Loewenstein, 2011. "Reinforcement learning in professional basketball players," Nature Communications, Nature, vol. 2(1), pages 1-8, September.
    • Handle: RePEc:nat:natcom:v:2:y:2011:i:1:d:10.1038_ncomms1580
    DOI: 10.1038/ncomms1580
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    Citations

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    Cited by:

    1. Ofri Raviv & Merav Ahissar & Yonatan Loewenstein, 2012. "How Recent History Affects Perception: The Normative Approach and Its Heuristic Approximation," PLOS Computational Biology, Public Library of Science, vol. 8(10), pages 1-10, October.
    2. Joshua B. Miller & Adam Sanjurjo, 2015. "Is it a Fallacy to Believe in the Hot Hand in the NBA Three-Point Contest?," Working Papers 548, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    3. Miller, Joshua Benjamin & Sanjurjo, Adam, 2018. "A Visible (Hot) Hand? Expert Players Bet on the Hot Hand and Win," OSF Preprints sd32u, Center for Open Science.
    4. Miller, Joshua Benjamin & Sanjurjo, Adam, 2018. "Is it a Fallacy to Believe in the Hot Hand in the NBA Three-Point Contest?," OSF Preprints dmksp, Center for Open Science.
    5. Tal Neiman & Yonatan Loewenstein, 2014. "Spatial Generalization in Operant Learning: Lessons from Professional Basketball," Discussion Paper Series dp665, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    6. Hanan Shteingart & Yonatan Loewenstein, 2014. "Reinforcement Learning and Human Behavior," Discussion Paper Series dp656, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    7. Chacoma, Andrés & Billoni, Orlando V., 2023. "Probabilistic model for Padel games dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    8. Aloys Prinz, 2019. "Learning (Not) to Evade Taxes," Games, MDPI, vol. 10(4), pages 1-18, September.
    9. Joshua B. Miller & Adam Sanjurjo, 2014. "A Cold Shower for the Hot Hand Fallacy," Working Papers 518, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    10. Hanan Shteingart & Tal Neiman & Yonatan Loewenstein, 2012. "The Role of First Impression in Operant Learning," Discussion Paper Series dp626, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    11. Miller, Joshua B. & Sanjurjo, Adam, 2021. "Is it a fallacy to believe in the hot hand in the NBA three-point contest?," European Economic Review, Elsevier, vol. 138(C).
    12. Ofri Raviv & Merav Ahissar & Yonatan Loewenstein, 2012. "How recent history affects perception: the normative approach and its heuristic approximation," Discussion Paper Series dp628, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    13. Brian Skinner, 2012. "The Problem of Shot Selection in Basketball," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-8, January.
    14. Gianluigi Mongillo & Hanan Shteingart & Yonatan Loewenstein, 2014. "The Misbehavior of Reinforcement Learning," Discussion Paper Series dp661, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    15. Tal Neiman & Yonatan Loewenstein, 2014. "Spatial Generalization in Operant Learning: Lessons from Professional Basketball," PLOS Computational Biology, Public Library of Science, vol. 10(5), pages 1-8, May.

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