due to subjects’ inferring the state of the reward probabilities and deploying fixed habitual actions conditioned on this, as discussed above. Third, behavior with fixed transition probabilities may be mediated by a successor representation (Dayan, 1993), which characterizes current states in terms of their likely future. Successor representations support rapid updating of values in the face of changes in the reward function (and so could generate “model-based” behavior in the fixed transition probability version), but not changes in state transition probabilities (and so could not solve the new task) (Russek et al., 2017). Both of these strategies are of substantial interest in their own right, so understanding what underpins the behavioral differences between the task variants is a pressing question for future work.
