Non-probabilistic decision making with memory constraints
AbstractThe single decision maker chooses one of the actions repeatedly. She chooses the action with the highest weighted average of the past payoffs. In the long run either the action with highest expected payoff or the action with highest minimal payoff is chosen depending on how weights evolve.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Economics Letters.
Volume (Year): 117 (2012)
Issue (Month): 1 ()
Contact details of provider:
Web page: http://www.elsevier.com/locate/ecolet
Adaptive learning; Constrained memory; Bandit problems;
Find related papers by JEL classification:
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
- D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
- C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Sarin, Rajiv, 2000. "Decision Rules with Bounded Memory," Journal of Economic Theory, Elsevier, vol. 90(1), pages 151-160, January.
- Sarin, Rajiv & Vahid, Farshid, 2001.
"Predicting How People Play Games: A Simple Dynamic Model of Choice,"
Games and Economic Behavior,
Elsevier, vol. 34(1), pages 104-122, January.
- Sarin, R. & Vahid, F., 1999. "Predicting how People Play Games: a Simple Dynamic Model of Choice," Monash Econometrics and Business Statistics Working Papers 12/99, Monash University, Department of Econometrics and Business Statistics.
- Young, H. Peyton, 2009. "Learning by trial and error," Games and Economic Behavior, Elsevier, vol. 65(2), pages 626-643, March.
- Sarin, Rajiv & Vahid, Farshid, 1999. "Payoff Assessments without Probabilities: A Simple Dynamic Model of Choice," Games and Economic Behavior, Elsevier, vol. 28(2), pages 294-309, August.
- Huck Steffen & Sarin Rajiv, 2004.
"Players With Limited Memory,"
The B.E. Journal of Theoretical Economics,
De Gruyter, vol. 4(1), pages 1-27, September.
- Steffen Huck & Rajiv Sarin, 2000. "Players with Limited Memory," Econometric Society World Congress 2000 Contributed Papers 1645, Econometric Society.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
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.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.