Computational modelling of switching behaviour in repeated gambles

摘要

We present a computational model which predicts people’s switching behaviour in repeated gambling scenarios such as the Iowa Gambling Task. This Utility-Caution model suggests that people’s tendency to switch away from an option is due to a utility factor which reflects the probability and the amount of losses experienced compared to gains, and a caution factor which describes the number of choices made consecutively in that option. Using a novel next-choice-prediction method, the Utility-Caution model was tested using two sets of data on the performance of participants in the Iowa Gambling Task. The model produced significantly more accurate predictions of people’s choices than the previous Bayesian expected-utility model and expectancy-valence model.