Impaired Arbitration Between Decision-Making Strategies in Alcohol and Cannabis Users: A Preliminary Computational Modeling Study

Recent advances in reinforcement learning dissociate between habitual processing and goal-oriented planning via the engagement of computationally cheap model-free (habit) and costly model-based (goal-directed) control, whereby the reliance of model-based control is increased under high stakes conditions. Addicted individuals purportedly rely more on model-free control; however, it remains to be studied how they arbitrate between model-free and model-based control under higher stakes of reward.