Updating Strategies Through Observed Play - Optimization Under Bounded Rationality
Individuals repeatedly face a multi-decision task with unknown payoff distributions. They have minimal memory and update their strategy by observing previous play (and not strategy) of someone else. We select behavior rules that increase average payoffs as often as possible in a large population where all use the same rule. Here imitation generalizes to a pasting procedure. When decisions within the task are unrelated, individuals eventually learn the efficient strategy but the underlying dynamic is not monotone. However, when choices influence which decisions are subsequently faced in the task, play may not be efficient in the long run as it approaches a Nash equilibrium of the agent normal form.
|Date of creation:||Apr 1998|
|Date of revision:|
|Contact details of provider:|| Postal: |
Fax: +49 228 73 6884
Web page: http://www.bgse.uni-bonn.de
When requesting a correction, please mention this item's handle: RePEc:bon:bonsfb:432. 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: (BGSE Office)
If references are entirely missing, you can add them using this form.