IDEAS home Printed from https://ideas.repec.org/h/spr/lnechp/978-3-642-02956-1_18.html
   My bibliography  Save this book chapter

An Attempt to Integrate Path-Dependency in a Learning Model

In: Artificial Economics

Author

Listed:
  • Narine Udumyan

    (GREQAM)

  • Juliette Rouchier

    (GREQAM)

  • Dominique Ami

    (IDEP DESMID)

Abstract

The absence of information on the state of the resource is considered as one of the main reasons of resource collapses. In the current study, we propose a solution to this problem stemming from the resource users. They can perceive the resource dynamics by the impact it has on their profits. At a given time step, the state of the resource depends on its previous states and hence on the agents’ past decisions. In this perspective, different perceptions are characterized by different weights that the resource users assign to the current and past actions in the profit formation. In order to capture these individual differences, we consider Schaefer-Gordon dynamic model. On its basis, we develop a learning model, adapted from Roth-Erev model. The simulation results show that the resource can be exploited in a sustainable manner if the past action is taken into account.

Suggested Citation

  • Narine Udumyan & Juliette Rouchier & Dominique Ami, 2009. "An Attempt to Integrate Path-Dependency in a Learning Model," Lecture Notes in Economics and Mathematical Systems, in: Cesáreo Hernández & Marta Posada & Adolfo López-Paredes (ed.), Artificial Economics, chapter 0, pages 223-234, Springer.
    • Handle: RePEc:spr:lnechp:978-3-642-02956-1_18
    DOI: 10.1007/978-3-642-02956-1_18
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:lnechp:978-3-642-02956-1_18. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.