This article presents a dual system model (DSM) of decision making under risk and uncertainty according to which the value of a gamble is a combination of the values assigned to it independently by the affective and deliberative systems. On the basis of research on dual process theories and empirical research in Hsee and Rottenstreich (2004) and…

Reinforcement learning theories postulate that actions are chosen to maximize a long-term sum of positive outcomes based on value functions, which are subjective estimates of future rewards. In simple reinforcement learning algorithms, value functions are updated only by trial-and-error, whereas they are updated according to the decision-maker's…

The authors examined internal representations of conditional strategies for a situation of object conflict in 849 adolescents and young adults between the ages of 11 and 19 years. To examine participants' expectations of strategy use, the authors developed questionnaires that depicted a variety of contexts in which 2 people wanted an object that…

Analysis of binary choice behavior in iterated tasks with immediate feedback reveals robust deviations from maximization that can be described as indications of 3 effects: (a) a payoff variability effect, in which high payoff variability seems to move choice behavior toward random choice; (b) underweighting of rare events, in which alternatives…

Discusses problems with the use of stochastic (probabilistic) models for the analysis of juvenile offense data. Analyzes longitudinal data for White and non-White delinquents which show significant evidence of offense specialization and a random distribution of offenses if no specialization occurs. (Author/GC)

Random-walk conceptions of performance, aspirations, and risk preferences are used to model a pattern of risk taking responsive to a risk taker's changing fortune. The impact of adaptive aspirations and attention focus on risk taking over time is explored for cohorts and a renewing population of risk takers. (SLD)

The authors explore the division of labor between the basal ganglia-dopamine (BG-DA) system and the orbitofrontal cortex (OFC) in decision making. They show that a primitive neural network model of the BG-DA system slowly learns to make decisions on the basis of the relative probability of rewards but is not as sensitive to (a) recency or (b) the…

Examines a statistical model in which the users of an online system continually update their estimated probability of success, and quit or continue the search according to the expected utility of each action. The implications for search strategies are discussed. (Author/EM)