Model-based reinforcement learning (RL) has been argued to underlie the goal-directed process; however, the way in which it interacts with habits and the structure of the habitual process has remained unclear. According to a flat architecture, the habitual process corresponds to model-free RL, and its interaction with the goal-directed process is coordinated by an external arbitration mechanism. Alternatively, the interaction between these systems has recently been argued to be hierarchical, such that the formation of action sequences

underlies habit learning and a goal-directed process selects between goal-directed actions and habitual sequences of actions to reach the goal. Here we used a two-stage decision-making task to test predictions from IWR-1-endo nmr these accounts. The hierarchical KU-57788 datasheet account predicts that, because they are tied to each other as an action sequence, selecting a habitual action in the first stage will be followed by a habitual action in the second stage, whereas the flat account predicts that the statuses of the first and second stage actions are independent of each other. We found, based on subjects’ choices and

reaction times, that human subjects combined single actions to build action sequences and that the formation of such action sequences was sufficient to explain habitual actions. Furthermore, based on Bayesian model comparison, a family of hierarchical RL models, assuming a hierarchical interaction between habit and goal-directed processes, provided a better fit of the subjects’ behavior than a family of flat models. Although these findings do not rule out all possible model-free accounts of instrumental conditioning, they do show such accounts are not necessary

to explain habitual actions and provide a new basis for understanding how goal-directed and habitual action control interact. Author Summary Quizartinib mw In order to make choices that lead to desirable outcomes, individuals tend to deliberate over the consequences of various alternatives. This goal-directed deliberation is, however, slow and cognitively demanding. As a consequence, under appropriate conditions decision-making can become habitual and automatic. The nature of these habitual actions, how they are learned, expressed, and interact with the goal-directed process is not clearly understood. Here we report that (1) habits interact with the goal-directed process in a hierarchical manner (i.e., the goal-directed system selects a goal, and then determines which habit should be executed to reach that goal), and (2) habits are learned sequences of actions that, once triggered by the goal-directed process, can be expressed quickly and in an efficient manner. The findings provide critical new experimental and computational information on the nature of habits and how they interact with the goal-directed decision-making.