Proceedings of the Annual Meeting of the Cognitive Science Society

The Balloon Analogue Risk Task (BART) is a sequential decision making paradigm that assesses risk-taking behavior.Several computational models have been proposed for the BART that accurately characterize risk-taking propensity. Anaspect of task performance that has proven challenging to model is the learning that develops from experiencing winsand losses across trials, which has the potential to provide further insight into risky decision making. The Scaled TargetLearning (STL) model was developed for this purpose. STL describes learning as adjustments to the pumping strategyin reaction to previous outcomes, and the size of adjustments reflects an individuals sensitivity to wins and losses. STLis shown to be sensitive to the learning elicited by experimental manipulations. In addition, the model matches or beststhe performance of three competing models in traditional model comparison tests (e.g., parameter recovery performance,predictive accuracy, sensitivity to risk-taking propensity). Findings are discussed in the context of the learning processinvolved in the task. By characterizing the extent to which people are willing to adapt their strategies based on pastexperience, STL provides a more complete depiction of the psychological processes underlying sequential risk-takingbehavior.