Topic: cognitive models

Value-based decision-making in a context-changing environment is known to be guided by the two distinctive reinforcement learning (RL) strategies: goal-directed and habitual learning. Despite decades-long efforts to reveal that different environmental variables influence these RL processes, it remains unknown exactly how we create a situation by manipulating a set of environmental variables to guide these processes separately. This is mostly because of the complex interactions between environmental variables and RL, often beyond the experimenter’s comprehension. Here we show that an RL algorit