This section reviews a specialty within the field of decision-making known as dynamic decision-making. Dynamic decisions are characterized by a decision-maker choosing among various actions at different points in time in order to control and optimize performance of a dynamic stochastic system. Realistic examples include fighting fires, navigational control, battlefield decisions, medical emergencies, etc. The section is broken down into four parts: The first reviews basic theory concerning optimal decision principles in a dynamic context; the second summarizes empirical approaches to the study of human performance on dynamic decision tasks; the third presents theoretical models that describe how humans learn to control dynamic systems; and the last discusses methodological issues arising from the study of complex decisions including differences between field versus laboratory research.
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