IDEAS home Printed from https://ideas.repec.org/a/wsi/igtrxx/v23y2021i03ns0219198921500018.html
   My bibliography  Save this article

Markovian Switching of Mutation Rates in Evolutionary Network Dynamics

Author

Listed:
  • Andrew Yardley Vlasic

    (Department of Mathematics and Statistics, Queen’s University, Kingston, ON K7L 3N6, Canada)

Abstract

The replicator–mutator dynamic was originally derived to model the evolution of language, and since the model was derived in such a general manner, it has been applied to the dynamics of social behavior and decision making in multi-agent networks. For the two type population, a bifurcation point of the mutation rate was derived, displaying different long-run behaviors above and below this point. The long-run behavior would naturally be subjected to noise from the environment, however, to date, there does not exist a model that dynamically accounts for the effects of the environment. To account for the environmental impacts on the evolution of the populace, mutation rates above and below this bifurcation point are switched according to a continuous-time Markov chain. The long-run behaviors of this model are derived, showing a counterintuitive result that the majority of initial conditions will favor the dominated type.

Suggested Citation

  • Andrew Yardley Vlasic, 2021. "Markovian Switching of Mutation Rates in Evolutionary Network Dynamics," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 23(03), pages 1-18, September.
    • Handle: RePEc:wsi:igtrxx:v:23:y:2021:i:03:n:s0219198921500018
    DOI: 10.1142/S0219198921500018
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219198921500018
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219198921500018?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wsi:igtrxx:v:23:y:2021:i:03:n:s0219198921500018. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/igtr/igtr.shtml .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.