Toward the cognitive modeling of dynamic decision making.

Although most research into risky decision making has focused on simple scenarios - where isolated choices are made independent of one another - many important decisions in life play out across sequences of interdependent events and actions. Despite the ubiquity and importance of such decision problems, we know relatively little about how people manage the complexities of dynamic, multistage decisions. Our work combines techniques from two research traditions to investigate how people handle the challenges of dynamic decision making. We use true-and-error models to estimate the distribution and stability of preference profiles, and the presence of errors. In a complementary analysis we use cognitive modeling based on the Decision Field Theory to investigate the psychological processes underlying dynamic decision making. Decision Field Theory provides a unified framework for testing competing hypotheses about how people collect information and plan for the future. Results from both sets of analyses identify distinct groups of individuals. We discuss the behavioral and cognitive factors distinguishing groups from one another, including degree of planning, strategy shifts, biased information sampling, and effort-saving information processing.