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An initial implementation of the Turing tournament to learning in repeated two-person games

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  • Arifovic, Jasmina
  • McKelvey, Richard D.
  • Pevnitskaya, Svetlana

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  • Arifovic, Jasmina & McKelvey, Richard D. & Pevnitskaya, Svetlana, 2006. "An initial implementation of the Turing tournament to learning in repeated two-person games," Games and Economic Behavior, Elsevier, vol. 57(1), pages 93-122, October.
    • Handle: RePEc:eee:gamebe:v:57:y:2006:i:1:p:93-122
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    References listed on IDEAS

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    1. Hanaki, Nobuyuki & Sethi, Rajiv & Erev, Ido & Peterhansl, Alexander, 2005. "Learning strategies," Journal of Economic Behavior & Organization, Elsevier, vol. 56(4), pages 523-542, April.
    2. Crawford, Vincent P, 1995. "Adaptive Dynamics in Coordination Games," Econometrica, Econometric Society, vol. 63(1), pages 103-143, January.
    3. 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 848-881, September.
    4. Boylan Richard T. & El-Gamal Mahmoud A., 1993. "Fictitious Play: A Statistical Study of Multiple Economic Experiments," Games and Economic Behavior, Elsevier, vol. 5(2), pages 205-222, April.
    5. McKelvey Richard D. & Palfrey Thomas R., 1995. "Quantal Response Equilibria for Normal Form Games," Games and Economic Behavior, Elsevier, vol. 10(1), pages 6-38, July.
    6. 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.
    7. F. M. O'Carroll, 1977. "Subjective Probabilities and Short‐Term Economic Forecasts: An Empirical Investigation," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 26(3), pages 269-278, November.
    8. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    9. Dale O. Stahl, 1999. "Evidence based rules and learning in symmetric normal-form games," International Journal of Game Theory, Springer;Game Theory Society, vol. 28(1), pages 111-130.
    10. Stahl, Dale O., 1996. "Boundedly Rational Rule Learning in a Guessing Game," Games and Economic Behavior, Elsevier, vol. 16(2), pages 303-330, October.
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    Cited by:

    1. Eric Guerci & Nobuyuki Hanaki & Naoki Watanabe, 2015. "Meaningful Learning in Weighted Voting Games: An Experiment," Working Papers halshs-01216244, HAL.
    2. Shu‐Heng Chen & Shu G. Wang, 2011. "Emergent Complexity In Agent‐Based Computational Economics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(3), pages 527-546, July.
    3. Ioannou, Christos A. & Romero, Julian, 2014. "A generalized approach to belief learning in repeated games," Games and Economic Behavior, Elsevier, vol. 87(C), pages 178-203.
    4. Eric Guerci & Nobuyuki Hanaki & Naoki Watanabe, 2017. "Meaningful learning in weighted voting games: an experiment," Theory and Decision, Springer, vol. 83(1), pages 131-153, June.
    5. Hanaki, Nobuyuki & Ishikawa, Ryuichiro & Akiyama, Eizo, 2009. "Learning games," Journal of Economic Dynamics and Control, Elsevier, vol. 33(10), pages 1739-1756, October.
    6. Hanaki, Nobuyuki & Sethi, Rajiv & Erev, Ido & Peterhansl, Alexander, 2005. "Learning strategies," Journal of Economic Behavior & Organization, Elsevier, vol. 56(4), pages 523-542, April.
    7. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.
    8. Ido Erev & Eyal Ert & Alvin E. Roth, 2010. "A Choice Prediction Competition for Market Entry Games: An Introduction," Games, MDPI, vol. 1(2), pages 1-20, May.
    9. Christos A. Ioannou & Julian Romero, 2012. "Strategic Learning With Finite Automata Via The EWA-Lite Model," Purdue University Economics Working Papers 1269, Purdue University, Department of Economics.
    10. Nobuyuki Hanaki, 2007. "Individual and Social Learning," Computational Economics, Springer;Society for Computational Economics, vol. 29(3), pages 421-421, May.
    11. Doğan, Gönül, 2018. "Collusion in a buyer–seller network formation game," Journal of Economic Behavior & Organization, Elsevier, vol. 155(C), pages 445-457.
    12. Roth, Alvin E. & Herzog, Stefan & Hau, Robin & Hertwig, Ralph & Erev, Ido & Ert, Eyal & Haruvy, Ernan & Stewart, Terrence & West, Robert & Lebiere, Christian, 2009. "A Choice Prediction Competition: Choices From Experience and From Description," Scholarly Articles 5343169, Harvard University Department of Economics.
    13. Naoki Watanabe, 2022. "Reconsidering Meaningful Learning in a Bandit Experiment on Weighted Voting: Subjects’ Search Behavior," The Review of Socionetwork Strategies, Springer, vol. 16(1), pages 81-107, April.
    14. Chernov, G. & Susin, I., 2019. "Models of learning in games: An overview," Journal of the New Economic Association, New Economic Association, vol. 44(4), pages 77-125.
    15. Jasmina Arifovic & John Ledyard, 2004. "Scaling Up Learning Models in Public Good Games," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 6(2), pages 203-238, May.
    16. Alan Mehlenbacher, 2007. "Multiagent System Platform for Auction Simulations," Department Discussion Papers 0706, Department of Economics, University of Victoria.
    17. Juan Camilo Cárdenas & César Mantilla & Rajiv Sethi, 2013. "Commons without Tragedy: Sampling Dynamics and Cooperative Resource Extraction," Documentos CEDE 11892, Universidad de los Andes, Facultad de Economía, CEDE.
    18. Alan Mehlenbacher, 2009. "Multiagent System Simulations of Signal Averaging in English Auctions with Two-Dimensional Value Signals," Computational Economics, Springer;Society for Computational Economics, vol. 34(2), pages 119-143, September.
    19. Shu-Heng Chan & Shu G. Wang, 2010. "Emergent Complexity in Agent-Based Computational Economics," ASSRU Discussion Papers 1017, ASSRU - Algorithmic Social Science Research Unit.

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