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Dynamic programming and behavioral rules

Dale O. Stahl ()
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Dale O. Stahl: University of Texas

Economic Theory Bulletin, 2017, vol. 5, issue 2, 165-174

Abstract: 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)
Date: 2017
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