Citation

O'Doherty JP, Lee SW, McNamee D. Curr. Opin. Behav. Sci. 2015; 1: 94-100.

Copyright

(Copyright © 2015, Elsevier Publishing)

DOI

10.1016/j.cobeha.2014.10.004

PMID

unavailable

Abstract

Here we review recent developments in the application of reinforcement-learning theory as a means of understanding how the brain learns to select actions to maximize future reward, with a focus on human neuroimaging studies. We evaluate evidence for the distinction between model-based and model-free reinforcement-learning and their arbitration, and consider hierarchical reinforcement-learning schemes and structure learning. Finally we discuss the possibility of integrating across these different domains as a means of gaining a more complete understanding of how it is the brain learns from reinforcement.