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Humans versus computer algorithms in repeated mixed strategy games

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  • Spiliopoulos, Leonidas

Abstract

This paper is concerned with the modeling of strategic change in humans’ behavior when facing different types of opponents. In order to implement this efficiently a mixed experimental setup was used where subjects played a game with a unique mixed strategy Nash equilibrium for 100 rounds against 3 preprogrammed computer algorithms (CAs) designed to exploit different modes of play. In this context, substituting human opponents with computer algorithms designed to exploit commonly occurring human behavior increases the experimental control of the researcher allowing for more powerful statistical tests. The results indicate that subjects significantly change their behavior conditional on the type of CA opponent, exhibiting within-sub jects heterogeneity, but that there exists comparatively little between-subjects heterogeneity since players seemed to follow very similar strategies against each algorithm. Simple heuristics, such as win-stay/lose-shift, were found to model subjects and make out of sample predictions as well as, if not better than, more complicated models such as individually estimated EWA learning models which suffered from overfitting. Subjects modified their strategies in the direction of better response as calculated from CA simulations of various learning models, albeit not perfectly. Examples include the observation that subjects randomized more effectively as the pattern recognition depth of the CAs increased, and the drastic reduction in the use of the win-stay/lose-shift heuristic when facing a CA designed to exploit this behavior.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 6672.

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Date of creation: 09 Jan 2008
Date of revision:
Handle: RePEc:pra:mprapa:6672

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Related research

Keywords: Behavioral game theory; Learning; Experimental economics; Simulations; Experience weighted attraction learning; Simulations; Repeated games; Mixed Strategy Nash equilibria; Economics and psychology;

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References

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  1. Jason Shachat & J. Todd Swarthout, 2003. "Learning about Learning in Games through Experimental Control of Strategic Interdependence," Experimental 0310003, EconWPA.
  2. Yaw Nyarko & Andrew Schotter, 2002. "An Experimental Study of Belief Learning Using Elicited Beliefs," Econometrica, Econometric Society, vol. 70(3), pages 971-1005, May.
  3. Peter Dürsch & Albert Kolb & Jörg Oechssler & Burkhard C. Schipper, 2005. "Rage Against the Machines: How Subjects Learn to Play Against Computers," Bonn Econ Discussion Papers bgse31_2005, University of Bonn, Germany.
  4. Atanasios Mitropoulos, 2001. "On the Measurement of the Predictive Success of Learning Theories in Repeated Games," Experimental 0110001, EconWPA.
  5. Smith, Vernon L & Walker, James M, 1993. "Rewards, Experience and Decision Costs in First Price Auctions," Economic Inquiry, Western Economic Association International, vol. 31(2), pages 237-45, April.
  6. Jason Shachat & J. Todd Swarthout, 2003. "Do We Detect and Exploit Mixed Strategy Play by Opponents?," Experimental 0310001, EconWPA.
  7. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
  8. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
  9. Harrison, Glenn W, 1989. "Theory and Misbehavior of First-Price Auctions," American Economic Review, American Economic Association, vol. 79(4), pages 749-62, September.
  10. Bonetti, Shane, 1998. "Experimental economics and deception," Journal of Economic Psychology, Elsevier, vol. 19(3), pages 377-395, June.
  11. Walker, James M. & Smith, Vernon L. & Cox, James C., 1987. "Bidding behavior in first price sealed bid auctions : Use of computerized Nash competitors," Economics Letters, Elsevier, vol. 23(3), pages 239-244.
  12. Spiliopoulos, Leonidas, 2008. "Do repeated game players detect patterns in opponents? Revisiting the Nyarko & Schotter belief elicitation experiment," MPRA Paper 6666, University Library of Munich, Germany.
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Cited by:
  1. Spiliopoulos, Leonidas, 2008. "Do repeated game players detect patterns in opponents? Revisiting the Nyarko & Schotter belief elicitation experiment," MPRA Paper 6666, University Library of Munich, Germany.
  2. repec:fee:wpaper:1101 is not listed on IDEAS
  3. repec:fee:wpaper:1103 is not listed on IDEAS
  4. repec:wyi:journl:002151 is not listed on IDEAS
  5. Shachat, Jason & Swarthout, J. Todd, 2012. "Learning about learning in games through experimental control of strategic interdependence," Journal of Economic Dynamics and Control, Elsevier, vol. 36(3), pages 383-402.
  6. repec:wyi:wpaper:002021 is not listed on IDEAS

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