Evolutionary Drift and Equilibrium Selection
This paper develops an approach to equilibrium selection in game theory based on studying the learning process through which equilibrium is achieved. The differential equations derived from models of interactive learning typically have stationary states that are not isolated. Instead, Nash equilibria that specify different out-of- equilibrium behavior appear in connected components of stationary states. The stability properties of these components can depend critically on the perturbations to which the system is subjected. We argue that it is then important to incorporate such drift into the model. A sufficient condition is provided for drift to create stationary states, with strong stability properties, near a component of equilibria. Applications to questions of forward and backward induction are developed.
(This abstract was borrowed from another version of this item.)
To our knowledge, this item is not available for
download. To find whether it is available, there are three
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.
|Date of creation:||1995|
|Date of revision:|
|Contact details of provider:|| Postal: UNIVERSITY OF WISCONSIN MADISON, SOCIAL SYSTEMS RESEARCH INSTITUTE(S.S.R.I.), MADISON WISCONSIN 53706 U.S.A.|
When requesting a correction, please mention this item's handle: RePEc:att:wimass:9529. See general 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: (Ailsenne Sumwalt)
If references are entirely missing, you can add them using this form.