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Paradox Lost: The Evolution of Strategies in Selten’s Chain Store Game
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Paradox Lost: The Evolution of Strategies in Selten’s Chain Store Game

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  • William Tracy

Abstract

The classical game theoretic resolutions to Selten’s Chain Store game are unsatisfactory; they either alter the game to avoid the paradox or struggle to organize the existing experimental data. This paper applies co-evolutionary algorithms to the Chain Store game and demonstrates that the resulting system’s dynamics are neither intuitively paradoxical nor contradicted by the existing experimental data. Specifically, some parameterizations of evolutionary algorithms promote genetic drift. Such drift can lead the system to transition among the game’s various Nash Equilibria. This has implications for policy makers as well as for computational modelers. Copyright Springer Science+Business Media New York 2014

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  • William Tracy, 2014. "Paradox Lost: The Evolution of Strategies in Selten’s Chain Store Game," Computational Economics, Springer;Society for Computational Economics, vol. 43(1), pages 83-103, January.
  • Handle: RePEc:kap:compec:v:43:y:2014:i:1:p:83-103
    DOI: 10.1007/s10614-013-9364-0
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    1. Haruvy, Ernan & Roth, Alvin E. & Unver, M. Utku, 2006. "The dynamics of law clerk matching: An experimental and computational investigation of proposals for reform of the market," Journal of Economic Dynamics and Control, Elsevier, vol. 30(3), pages 457-486, March.
    2. Canning, David, 1992. "Average behavior in learning models," Journal of Economic Theory, Elsevier, vol. 57(2), pages 442-472, August.
    3. Young, H Peyton, 1993. "The Evolution of Conventions," Econometrica, Econometric Society, vol. 61(1), pages 57-84, January.
    4. Bullard, James & Duffy, John, 1999. "Using Genetic Algorithms to Model the Evolution of Heterogeneous Beliefs," Computational Economics, Springer;Society for Computational Economics, vol. 13(1), pages 41-60, February.
    5. Kreps, David M. & Wilson, Robert, 1982. "Reputation and imperfect information," Journal of Economic Theory, Elsevier, vol. 27(2), pages 253-279, August.
    6. Kandori, Michihiro & Mailath, George J & Rob, Rafael, 1993. "Learning, Mutation, and Long Run Equilibria in Games," Econometrica, Econometric Society, vol. 61(1), pages 29-56, January.
    7. Yun Joo Jung & John H. Kagel & Dan Levin, 1994. "On the Existence of Predatory Pricing: An Experimental Study of Reputation and Entry Deterrence in the Chain-Store Game," RAND Journal of Economics, The RAND Corporation, vol. 25(1), pages 72-93, Spring.
    8. John H. Miller, 1998. "Active Nonlinear Tests (ANTs) of Complex Simulation Models," Management Science, INFORMS, vol. 44(6), pages 820-830, June.
    9. Unver, M. Utku, 2001. "Backward unraveling over time: The evolution of strategic behavior in the entry level British medical labor markets," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 1039-1080, June.
    10. Andreoni James & Miller John H., 1995. "Auctions with Artificial Adaptive Agents," Games and Economic Behavior, Elsevier, vol. 10(1), pages 39-64, July.
    11. Holland, John H & Miller, John H, 1991. "Artificial Adaptive Agents in Economic Theory," American Economic Review, American Economic Association, vol. 81(2), pages 365-371, May.
    12. Milgrom, Paul & Roberts, John, 1982. "Predation, reputation, and entry deterrence," Journal of Economic Theory, Elsevier, vol. 27(2), pages 280-312, August.
    13. Ken Binmore & Larry Samuelson, 1999. "Evolutionary Drift and Equilibrium Selection," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 66(2), pages 363-393.
    14. Ken Binmore & Larry Samuelson, "undated". "Evolutionary Drift And Equilibrium Selection," ELSE working papers 049, ESRC Centre on Economics Learning and Social Evolution.
    15. H. Peyton Young, 1996. "The Economics of Convention," Journal of Economic Perspectives, American Economic Association, vol. 10(2), pages 105-122, Spring.
    16. Marco Casari, 2004. "Can Genetic Algorithms Explain Experimental Anomalies?," Computational Economics, Springer;Society for Computational Economics, vol. 24(3), pages 257-275, March.
    17. Camerer, Colin & Weigelt, Keith, 1988. "Experimental Tests of a Sequential Equilibrium Reputation Model," Econometrica, Econometric Society, vol. 56(1), pages 1-36, January.
    18. Ken Binmore & Larry Samuelson, "undated". "Evolutionary Drift and Equilibrium Selection," ELSE working papers 011, ESRC Centre on Economics Learning and Social Evolution.
    19. Ian McCarthy, 2008. "Simulating Sequential Search Models with Genetic Algorithms: Analysis of Price Ceilings, Taxes, Advertising and Welfare," Caepr Working Papers 2008-010, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
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