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Predicting and Understanding Initial Play

Author

Listed:
  • Drew Fudenberg
  • Annie Liang

Abstract

We use machine learning to uncover regularities in the initial play of matrix games. We first train a prediction algorithm on data from past experiments. Examining the games where our algorithm predicts correctly, but existing economic models don't, leads us to add a parameter to the best performing model that improves predictive accuracy. We then observe play in a collection of new "algorithmically generated" games, and learn that we can obtain even better predictions with a hybrid model that uses a decision tree to decide game-by-game which of two economic models to use for prediction.

Suggested Citation

  • Drew Fudenberg & Annie Liang, 2019. "Predicting and Understanding Initial Play," American Economic Review, American Economic Association, vol. 109(12), pages 4112-4141, December.
    • Handle: RePEc:aea:aecrev:v:109:y:2019:i:12:p:4112-41
    Note: DOI: 10.1257/aer.20180654
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    Citations

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    Cited by:

    1. Daniel J. Benjamin, 2018. "Errors in Probabilistic Reasoning and Judgment Biases," GRU Working Paper Series GRU_2018_023, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    2. Shoshan, Vered & Hazan, Tamir & Plonsky, Ori, 2023. "BEAST-Net: Learning novel behavioral insights using a neural network adaptation of a behavioral model," OSF Preprints kaeny, Center for Open Science.
    3. Terje Lensberg & Klaus Reiner Schenk-Hoppe, 2019. "Evolutionary Stable Solution Concepts for the Initial Play," Economics Discussion Paper Series 1916, Economics, The University of Manchester.
    4. Noga Alon & Kirill Rudov & Leeat Yariv, 2021. "Dominance Solvability in Random Games," Papers 2105.10743, arXiv.org.
    5. Lensberg, Terje & Schenk-Hoppé, Klaus Reiner, 2021. "Cold play: Learning across bimatrix games," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 419-441.
    6. Gorny, Paul M. & Groos, Eva & Strobel, Christina, 2024. "Do Personalized AI Predictions Change Subsequent Decision-Outcomes? The Impact of Human Oversight," MPRA Paper 121065, University Library of Munich, Germany.
    7. Isaiah Andrews & Drew Fudenberg & Lihua Lei & Annie Liang & Chaofeng Wu, 2022. "The Transfer Performance of Economic Models," Papers 2202.04796, arXiv.org, revised Jul 2024.
    8. Christoph Kuzmics & Daniel Rodenburger, 2020. "A case of evolutionarily stable attainable equilibrium in the laboratory," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 70(3), pages 685-721, October.
    9. Jian-Qiao Zhu & Joshua C. Peterson & Benjamin Enke & Thomas L. Griffiths, 2024. "Capturing the Complexity of Human Strategic Decision-Making with Machine Learning," Papers 2408.07865, arXiv.org.
    10. Külpmann, Philipp & Kuzmics, Christoph, 2022. "Comparing theories of one-shot play out of treatment," Journal of Economic Theory, Elsevier, vol. 205(C).
    11. Nir Chemaya & Daniel Martin, 2023. "Perceptions and Detection of AI Use in Manuscript Preparation for Academic Journals," Papers 2311.14720, arXiv.org, revised Jan 2024.
    12. Drew Fudenberg & Wayne Gao & Annie Liang, 2020. "How Flexible is that Functional Form? Quantifying the Restrictiveness of Theories," Papers 2007.09213, arXiv.org, revised Aug 2023.
    13. Paul Feldman & John Rehbeck, 2022. "Revealing a preference for mixtures: An experimental study of risk," Quantitative Economics, Econometric Society, vol. 13(2), pages 761-786, May.
    14. Daniele Condorelli & Massimiliano Furlan, 2024. "Deep Learning to Play Games," Papers 2409.15197, arXiv.org.
    15. Fulin Guo, 2023. "Experience-weighted attraction learning in network coordination games," Papers 2310.18835, arXiv.org.
    16. Jian-Qiao Zhu & Joshua C. Peterson & Benjamin Enke & Thomas L. Griffiths, 2024. "Capturing the Complexity of Human Strategic Decision-Making with Machine Learning," CESifo Working Paper Series 11296, CESifo.
    17. Noga Alon & Kirill Rudov & Leeat Yariv, 2021. "Dominance Solvability in Random Games," Working Papers 2021-84, Princeton University. Economics Department..
    18. Drew Fudenberg & Jon Kleinberg & Annie Liang & Sendhil Mullainathan, 2019. "Measuring the Completeness of Theories," Papers 1910.07022, arXiv.org.

    More about this item

    JEL classification:

    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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