Abstract
In the self-regulation model of decision-making under uncertainty, the dynamic programming principle of optimality transforms into the principle of instrumental rationality, according to which the proximate goal should be reached from the perspective of attaining the distal goal. The solution of the problem is considered to be a result of multiple iterations in evaluating an alternative’s pros and cons from the perspective of the distal (long-term) goal. This paper demonstrates how the self-regulation approach for setting and resetting goals when making difficult decisions helps differentiate the alternatives and find the most suitable course of action by recognizing cons in proximal positive outcomes and pros in proximal negative outcomes, or by changing the new distal goal, which should be more long-term than the previous one.
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Yemelyanov, A.M., Bedny, I.S. (2021). Self-regulation Approach for Setting Goals in Problem-Solving. In: Ayaz, H., Asgher, U., Paletta, L. (eds) Advances in Neuroergonomics and Cognitive Engineering. AHFE 2021. Lecture Notes in Networks and Systems, vol 259. Springer, Cham. https://doi.org/10.1007/978-3-030-80285-1_24
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