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A sequential risk-taking paradigm used to identify real-world risk takers invokes both learning and decision processes. This article expands the paradigm to a larger class of tasks with different stochastic environments and different learning requirements. Generalizing a Bayesian sequential risk-taking model to the larger set of tasks clarifies the roles of learning and decision making during sequential risky choice. Results show that respondents adapt their learning processes and associated mental representations of the task to the stochastic environment. Furthermore, their Bayesian learning processes are shown to interfere with the paradigm's identification of risky drug use, whereas the decision-making process facilitates its diagnosticity. Theoretical implications of the results in terms of both understanding risk-taking behavior and improving risk-taking assessment methods are discussed. Keywords: risk taking, learning, Bayesian, individual differences, cognitive psychometrics

Humans and animals learn from experience by reducing the probability of sampling alternatives with poor past outcomes. Using simulations, J. G. March (1996) illustrated how such adaptive sampling could lead to risk-averse as well as risk-seeking behavior. In this article, the author develops a formal theory of how adaptive sampling influences risk taking. He shows that a risk-neutral decision maker may learn to prefer a sure thing to an uncertain alternative with identical expected value and a symmetric distribution, even if the decision maker follows an optimal policy of learning. If the distribution of the uncertain alternative is negatively skewed, risk-seeking behavior can emerge. Consistent with recent experiments, the model implies that information about foregone payoffs increases risk taking. Keywords: decisions from experience, risk taking, decisions under uncertainty, adaptive behavior, learning from outcome feedback

Influence of mental accounting on consumer credit decision making is examined.

Compensation specialists made two survey-sample decisions in a simulated wage survey. Policy-capturing analyses indicated that most specialists relied extensively on two of the available cues and consistently applied that policy across judgments. They were not able to accurately estimate their own decision-making policies, as demonstrated by the fact that rationally generated assessments of cue importance were significantly different from their actual policies. Finally, meta-analyses demonstrated that the variation in policies across decision makers could not be attributed to statistical artifacts or any moderators (e.g., salary-survey experience or industry) associated with the demographic data. Thus, different compensation specialists are likely to select a different sample of employers even for the same wage survey. Implications for the relevance of market wages obtained from surveys are discussed. (Reprinted by permission of the publisher.)

The effect of semantic information on episodic source decisions is examined. A robust schema-related response bias in source monitoring was demonstrated and it was further observed that when schemas were present only during retrieval, the response bias was more likely to occur.

Decision-making deficits exhibited by people with brain damage, psychopathology, antisocial personality or drug abuse problems are examined by using the Bechara simulated gambling task method.

Redish et al. rely too much on a rational and innate view of decision-making, when their emphasis on variation, their integrative spirit, and their neuroscientific insights point towards a broader view of why addiction is such a tenacious problem. The integration of subjective, sociocultural, and evolutionary factors with cognitive neuroscience advances our understanding of addiction and decision-making.

The framework for addiction offered by the target article can perhaps be simplified into fewer, more basic, vulnerabilities. 'Impulsivity' covers a number of vulnerabilities, not just enhanced delay discounting. Real-world drug-use decisions involve both delay and probability discounting. The motivational salience of, and attentional bias for, drug cues may be related to a number of vulnerabilities. Interactions among vulnerabilities are of significance and complicate the application of this framework.

Neuroscientists and psychologists have proposed a variety of well-supported theories to explain addiction. Many of these theories suggest that addiction results from a single process or dysfunction across all of its forms. The authors of the current review, in contrast, have used a well-defined theoretical account of decision-making to outline the variety of dysfunctions that could account for addictive behavior.