Dynamic Programming And Social Learning Via Replicator Dynamics
AbstractThis paper introduces a social learning algorithm for recursive decision problems faced by players in large anonymous games. The algorithm keeps track of only the distributions of agents over possible state-action pairs. State update, value update and behavior update constitute the three stages of the algorithm. The stability of the algorithm is studied. Numerical applications to consumption problems with and without cash-in-advance constraints are considered.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" 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.
Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2000 with number 190.
Date of creation: 05 Jul 2000
Date of revision:
Contact details of provider:
Postal: CEF 2000, Departament d'Economia i Empresa, Universitat Pompeu Fabra, Ramon Trias Fargas, 25,27, 08005, Barcelona, Spain
Fax: +34 93 542 17 46
Web page: http://enginy.upf.es/SCE/
More information through EDIRC
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).
If references are entirely missing, you can add them using this form.