This paper considers the motivational approach to decision-making in problems of uncertainty from the position of the psychological theory of SSAT. Illustrated throughout the paper is the notion of how the use of the major provisions of this theory, related to the concepts of goals, self-regulation, positive feedback, etc., helps in understanding the deeper mechanisms of decision-making and in creating effective systems for their computer support. Instead of the traditionally used approach, the paper proposes that when the solution of the problem is preceded by the construction of its mathematical model, it is better to use a fundamentally different approach to modeling, such as when the mental decision-making model is constructed by the subject himself in the process of solving the problem under consideration. If the solution of the problem is determined by a previously-constructed mathematical model at the first approach, then at the second approach, the solution depends on a mental model, which may not even be fully acknowledged by the subject. This paper describes the Motivation Evaluation Process for solving a problem and the Performance Evaluation Process with decision support for making a decision.
CITATION STYLE
Yemelyanov, A. (2019). Decision support of mental model formation in the self-regulation process of goal-directed decision-making under risk and uncertainty. In Advances in Intelligent Systems and Computing (Vol. 775, pp. 225–236). Springer Verlag. https://doi.org/10.1007/978-3-319-94866-9_23
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