Abstract Machine learning has the potential to facilitate the development of computational
methods that improve the measurement of cognitive and mental functioning. In three …

Abstract Machine learning has the potential to facilitate the development of computational
methods that improve the measurement of cognitive and mental functioning. In three …

Delay discounting has been linked to important behavioral, health, and social outcomes,
including academic achievement, social functioning and substance use, but thoroughly …

A state-of-the-art data analysis procedure is presented to conduct hierarchical Bayesian
inference and hypothesis testing on delay discounting data. The delay discounting task is a …

A novel method for analyzing delay discounting data is proposed. This newer metric, a
model‐based Area Under Curve (AUC) combining approximate Bayesian model selection …

Original, open‐source computer software was developed and validated against established
delay discounting methods in the literature. The software executed approximate Bayesian …

The study of delay discounting, or valuation of future rewards as a function of delay, has
contributed to understanding the behavioral economics of addiction. Accurate …

Interest in computational modeling of cognition and behavior continues to grow. To be most
productive, modelers should be equipped with tools that ensure optimal efficiency in data …

Delayed and risky choice (DARC) experiments are a cornerstone of research in psychology,
behavioural economics and neuroeconomics. By collecting an agent's preferences between …

Background The tendency to devaluate future options as a function of time, known as delay
discounting, is associated with various factors such as psychiatric illness and personality …