@article{ref1,
title="The structure of reinforcement-learning mechanisms in the human brain",
journal="Current opinion in behavioral sciences",
year="2015",
author="O'Doherty, John P. and Lee, Sang Wan and McNamee, Daniel",
volume="1",
number="",
pages="94-100",
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.<p />",
language="",
issn="2352-1546",
doi="10.1016/j.cobeha.2014.10.004",
url="http://dx.doi.org/10.1016/j.cobeha.2014.10.004"
}