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Stochastic stability and time-dependent mutations

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  • Pak, Maxwell

Abstract

This paper considers stochastic stability analysis in evolutionary models with time-dependent mutations. It takes a class of time-homogeneous Markov models where the transition probabilities are approximately polynomial functions of the mutation parameter and allows the mutation parameter to decline to zero over time. The main result shows that as long as the mutation parameter converges to zero slowly enough and its variation is finite, the resulting time-inhomogeneous model has a limiting distribution regardless of the details of the mutation process. Moreover, a bound on the required rate of decline is explicitly expressed as a function of the minimum coradius of the limit sets and the transition probabilities within the minimum coradius set.

Suggested Citation

  • Pak, Maxwell, 2008. "Stochastic stability and time-dependent mutations," Games and Economic Behavior, Elsevier, vol. 64(2), pages 650-665, November.
  • Handle: RePEc:eee:gamebe:v:64:y:2008:i:2:p:650-665
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    References listed on IDEAS

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    1. Glenn Ellison, 2000. "Basins of Attraction, Long-Run Stochastic Stability, and the Speed of Step-by-Step Evolution," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 67(1), pages 17-45.
    2. Young, H Peyton, 1993. "The Evolution of Conventions," Econometrica, Econometric Society, vol. 61(1), pages 57-84, January.
    3. Sandholm, William H. & Pauzner, Ady, 1998. "Evolution, Population Growth, and History Dependence," Games and Economic Behavior, Elsevier, vol. 22(1), pages 84-120, January.
    4. Robles, Jack, 1998. "Evolution with Changing Mutation Rates," Journal of Economic Theory, Elsevier, vol. 79(2), pages 207-223, April.
    5. Bergin, James & Lipman, Barton L, 1996. "Evolution with State-Dependent Mutations," Econometrica, Econometric Society, vol. 64(4), pages 943-956, July.
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    Cited by:

    1. Katsuhiko Aiba, 2015. "Waiting times in evolutionary dynamics with time-decreasing noise," International Journal of Game Theory, Springer;Game Theory Society, vol. 44(2), pages 499-514, May.
    2. Kevin Hasker, 2014. "The Emergent Seed: A Representation Theorem for Models of Stochastic Evolution and two formulas for Waiting Time," Levine's Working Paper Archive 786969000000000954, David K. Levine.
    3. Lim, Wooyoung & Neary, Philip R., 2016. "An experimental investigation of stochastic adjustment dynamics," Games and Economic Behavior, Elsevier, vol. 100(C), pages 208-219.

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