Theories of instrumental behavior distinguish between goal-directed decisions, motivated by a consideration of the probabilities and current utilities of their consequences, and habits, which are rigidly and automatically elicited by the stimulus environment based on reinforcement history.  In spite of the far-reaching implications of this distinction, ranging from the structuring of economic policies to the diagnosis and treatment of behavioral pathology, much is still unknown about what factors shape goal-directed decisions and what conditions prompt a transition from goal-directed to habitual action selection. Generally, while computationally expensive, a goal-directed strategy offers greater levels of flexible instrumental control. Since subjective utilities often change from one moment to the next, such flexibility is essential for reward maximization and thus may have intrinsic value, potentially serving to motivate and reinforce specific decisions, as well as to justify the general processing cost of goal-directed computations. A critical requirement for flexible instrumental control, however, is that alternative actions yield distinct consequences. In this talk,  Liljeholm will present behavioral and neural data suggesting that instrumental divergence – the distance between outcome probability distributions associated with alternative actions – can shape choice preferences and arbitrate between goal-directed and habitual decision strategies. Implications include the potential use of instrumental divergence as an optimization criterion for reinforcement learning, and as a diagnostic tool in pre-clinical evaluation of cognitive and affective impairment.