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Published January 2017 | Accepted Version
Journal Article Open

Learning, Reward, and Decision Making


In this review, we summarize findings supporting the existence of multiple behavioral strategies for controlling reward-related behavior, including a dichotomy between the goal-directed or model-based system and the habitual or model-free system in the domain of instrumental conditioning and a similar dichotomy in the realm of Pavlovian conditioning. We evaluate evidence from neuroscience supporting the existence of at least partly distinct neuronal substrates contributing to the key computations necessary for the function of these different control systems. We consider the nature of the interactions between these systems and show how these interactions can lead to either adaptive or maladaptive behavioral outcomes. We then review evidence that an additional system guides inference concerning the hidden states of other agents, such as their beliefs, preferences, and intentions, in a social context. We also describe emerging evidence for an arbitration mechanism between model-based and model-free reinforcement learning, placing such a mechanism within the broader context of the hierarchical control of behavior.

Additional Information

© 2017 by Annual Reviews. First published online as a Review in Advance on September 28, 2016. This work was supported by a National Institutes of Health (NIH) Conte Center grant for research on the neurobiology of social decision making (P50MH094258-01A1), NIH grant number DA033077-01 (supported by OppNet, NIH's Basic Behavioral and Social Science Opportunity Network), and National Science Foundation grant number 1207573 to J.O.D. The authors are not aware of any affiliations, memberships, funding, or financial holdings that might be perceived as affecting the objectivity of this review.

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Accepted Version - nihms-989286.pdf


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