Dynamic programming and behavioral rules
Dale O. Stahl ()
Additional contact information
Dale O. Stahl: University of Texas
Economic Theory Bulletin, 2017, vol. 5, issue 2, 165-174
Abstract The standard dynamic programming approach to exact optimization of sequential decision problems is extended to allow approximate optimization. An optimization-based solution is a behavioral rule that satisfies a modified Bellman equation. Existence of a solution is proven. Conversely, given any behavioral rule, there exist infinitely many dynamic programming problems for which the behavioral rule is an optimization-based solution. This result raises the question of whether we need to continue assuming decision makers optimize or approximately optimize.
Keywords: Dynamic programming; Approximate optimization; Behavioral rules (search for similar items in EconPapers)
JEL-codes: B4 C61 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
http://link.springer.com/10.1007/s40505-016-0110-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:spr:etbull:v:5:y:2017:i:2:d:10.1007_s40505-016-0110-3
Ordering information: This journal article can be ordered from
Access Statistics for this article
Economic Theory Bulletin is currently edited by Nicholas C. Yannelis
More articles in Economic Theory Bulletin from Springer, Society for the Advancement of Economic Theory (SAET) Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla ().