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Learning in a black box

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  • Nax, Heinrich H.
  • Burton-Chellew, Maxwell N.
  • West, Stuart A.
  • Young, H. Peyton

Abstract

We study behavior in repeated interactions when agents have no information about the structure of the underlying game and they cannot observe other agents’ actions or payoffs. Theory shows that even when players have no such information, there are simple payoff-based learning rules that lead to Nash equilibrium in many types of games. A key feature of these rules is that subjects search differently depending on whether their payoffs increase, stay constant or decrease. This paper analyzes learning behavior in a laboratory setting and finds strong confirmation for these asymmetric search behaviors in the context of voluntary contribution games. By varying the amount of information we show that these behaviors are also present even when subjects have full information about the game.

Suggested Citation

  • Nax, Heinrich H. & Burton-Chellew, Maxwell N. & West, Stuart A. & Young, H. Peyton, 2016. "Learning in a black box," Journal of Economic Behavior & Organization, Elsevier, vol. 127(C), pages 1-15.
    • Handle: RePEc:eee:jeborg:v:127:y:2016:i:c:p:1-15
    DOI: 10.1016/j.jebo.2016.04.006
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    References listed on IDEAS

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    1. Sergiu Hart & Andreu Mas-Colell, 2013. "Stochastic Uncoupled Dynamics And Nash Equilibrium," World Scientific Book Chapters, in: Simple Adaptive Strategies From Regret-Matching to Uncoupled Dynamics, chapter 8, pages 165-189, World Scientific Publishing Co. Pte. Ltd..
    2. Selten, Reinhard & Stoecker, Rolf, 1986. "End behavior in sequences of finite Prisoner's Dilemma supergames A learning theory approach," Journal of Economic Behavior & Organization, Elsevier, vol. 7(1), pages 47-70, March.
    3. Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
    4. Friedman, Daniel & Huck, Steffen & Oprea, Ryan & Weidenholzer, Simon, 2015. "From imitation to collusion: Long-run learning in a low-information environment," Journal of Economic Theory, Elsevier, vol. 155(C), pages 185-205.
    5. 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.
    6. Mark Isaac, R. & McCue, Kenneth F. & Plott, Charles R., 1985. "Public goods provision in an experimental environment," Journal of Public Economics, Elsevier, vol. 26(1), pages 51-74, February.
    7. R. M. Harstad & R. Selten, 2014. "Bounded-rationality models:tasks to become intellectually competitive," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 5.
    8. Pradelski, Bary S.R. & Young, H. Peyton, 2012. "Learning efficient Nash equilibria in distributed systems," Games and Economic Behavior, Elsevier, vol. 75(2), pages 882-897.
    9. R. Mark Isaac & James M. Walker, 1988. "Group Size Effects in Public Goods Provision: The Voluntary Contributions Mechanism," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 103(1), pages 179-199.
    10. 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.
    11. Young, H. Peyton, 2009. "Learning by trial and error," Games and Economic Behavior, Elsevier, vol. 65(2), pages 626-643, March.
    12. Andreoni, James, 1988. "Why free ride? : Strategies and learning in public goods experiments," Journal of Public Economics, Elsevier, vol. 37(3), pages 291-304, December.
    13. Zion, Uri Ben & Erev, Ido & Haruvy, Ernan & Shavit, Tal, 2010. "Adaptive behavior leads to under-diversification," Journal of Economic Psychology, Elsevier, vol. 31(6), pages 985-995, December.
    14. , P. & , Peyton, 2006. "Regret testing: learning to play Nash equilibrium without knowing you have an opponent," Theoretical Economics, Econometric Society, vol. 1(3), pages 341-367, September.
    15. Sergiu Hart & Andreu Mas-Colell, 2013. "Uncoupled Dynamics Do Not Lead To Nash Equilibrium," World Scientific Book Chapters, in: Simple Adaptive Strategies From Regret-Matching to Uncoupled Dynamics, chapter 7, pages 153-163, World Scientific Publishing Co. Pte. Ltd..
    16. Erev, Ido & Rapoport, Amnon, 1998. "Coordination, "Magic," and Reinforcement Learning in a Market Entry Game," Games and Economic Behavior, Elsevier, vol. 23(2), pages 146-175, May.
    17. 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.
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    Citations

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    Cited by:

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    2. Ennio Bilancini & Leonardo Boncinelli, 2020. "The evolution of conventions under condition-dependent mistakes," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 69(2), pages 497-521, March.
    3. Friedman, Daniel & Rabanal, Jean Paul & Rud, Olga A. & Zhao, Shuchen, 2022. "On the empirical relevance of correlated equilibrium," Journal of Economic Theory, Elsevier, vol. 205(C).
    4. Maxwell N. Burton-Chellew & Stuart A. West, 2022. "The Black Box as a Control for Payoff-Based Learning in Economic Games," Games, MDPI, vol. 13(6), pages 1-15, November.
    5. He, Zhongzhi (Lawrence), 2023. "A Gradient-based reinforcement learning model of market equilibration," Journal of Economic Dynamics and Control, Elsevier, vol. 152(C).
    6. Burton-Chellew, Maxwell & West, Stuart, 2022. "The black box as a control for payoff-based learning in economic games," SocArXiv 5k4ez, Center for Open Science.
    7. Hwang, Sung-Ha & Lim, Wooyoung & Neary, Philip & Newton, Jonathan, 2018. "Conventional contracts, intentional behavior and logit choice: Equality without symmetry," Games and Economic Behavior, Elsevier, vol. 110(C), pages 273-294.
    8. Nazaria Solferino & Viviana Solferino & Serena F. Taurino, 2018. "The economics analysis of a Q-learning model of cooperation with punishment and risk taking preferences," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(3), pages 601-613, October.
    9. Kimbrough, Erik O. & Robalino, Nikolaus & Robson, Arthur J., 2017. "Applying “theory of mind”: Theory and experiments," Games and Economic Behavior, Elsevier, vol. 106(C), pages 209-226.
    10. Heinrich H. Nax, 2023. "The “Black Box” Method for Experimental Economics," Games, MDPI, vol. 14(2), pages 1-2, March.
    11. Mohlin, Erik & Östling, Robert & Wang, Joseph Tao-yi, 2020. "Learning by similarity-weighted imitation in winner-takes-all games," Games and Economic Behavior, Elsevier, vol. 120(C), pages 225-245.
    12. Innocenti, Stefania & Cowan, Robin, 2016. "Mimetic behaviour and institutional persistence: A two-armed bandit experiment," MERIT Working Papers 2016-028, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    13. Arigapudi, Srinivas & Heller, Yuval & Milchtaich, Igal, 2020. "Instability of Defection in the Prisoner’s Dilemma: Best Experienced Payoff Dynamics Analysis," MPRA Paper 99594, University Library of Munich, Germany.
    14. Arigapudi, Srinivas & Heller, Yuval & Milchtaich, Igal, 2021. "Instability of defection in the prisoner's dilemma under best experienced payoff dynamics," Journal of Economic Theory, Elsevier, vol. 197(C).
    15. Masiliūnas, Aidas, 2023. "Learning in rent-seeking contests with payoff risk and foregone payoff information," Games and Economic Behavior, Elsevier, vol. 140(C), pages 50-72.
    16. Innocenti, Stefania & Cowan, Robin, 2019. "Self-efficacy beliefs and imitation: A two-armed bandit experiment," European Economic Review, Elsevier, vol. 113(C), pages 156-172.
    17. Bernergård, Axel & Mohlin, Erik, 2019. "Evolutionary selection against iteratively weakly dominated strategies," Games and Economic Behavior, Elsevier, vol. 117(C), pages 82-97.
    18. Maxwell N. Burton-Chellew & Victoire D’Amico & Claire Guérin, 2022. "The Strategy Method Risks Conflating Confusion with a Social Preference for Conditional Cooperation in Public Goods Games," Games, MDPI, vol. 13(6), pages 1-10, October.
    19. Kurt A. Ackermann & Ryan O. Murphy, 2019. "Explaining Cooperative Behavior in Public Goods Games: How Preferences and Beliefs Affect Contribution Levels," Games, MDPI, vol. 10(1), pages 1-34, March.
    20. Jonathan Newton, 2018. "Evolutionary Game Theory: A Renaissance," Games, MDPI, vol. 9(2), pages 1-67, May.
    21. Aleksejus Kononovicius & Julius Ruseckas, 2018. "Order book model with herd behavior exhibiting long-range memory," Papers 1809.02772, arXiv.org, revised Apr 2019.
    22. Srinivas Arigapudi & Yuval Heller & Igal Milchtaich, 2020. "Instability of Defection in the Prisoner's Dilemma Under Best Experienced Payoff Dynamics," Papers 2005.05779, arXiv.org, revised Jan 2021.

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