José J. F. Ribas-Fernandes, Yael Niv, and Matthew M. Botvinick
- Published in print:
- 2011
- Published Online:
- August 2013
- ISBN:
- 9780262016438
- eISBN:
- 9780262298490
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262016438.003.0016
- Subject:
- Neuroscience, Behavioral Neuroscience
This chapter discusses the relevance of reinforcement learning (RL) to its hierarchical structure. It first reviews the fundamentals of RL, with a focus on temporal-difference learning in ...
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This chapter discusses the relevance of reinforcement learning (RL) to its hierarchical structure. It first reviews the fundamentals of RL, with a focus on temporal-difference learning in actor-critic models. Next, it discusses the scaling problem and the computational issues that stimulated the development of hierarchical reinforcement learning (HRL). The potential neuroscientific correlates of HRL are also described. The chapter also presents the results of some initial empirical tests and ends with directions for further research.Less
This chapter discusses the relevance of reinforcement learning (RL) to its hierarchical structure. It first reviews the fundamentals of RL, with a focus on temporal-difference learning in actor-critic models. Next, it discusses the scaling problem and the computational issues that stimulated the development of hierarchical reinforcement learning (HRL). The potential neuroscientific correlates of HRL are also described. The chapter also presents the results of some initial empirical tests and ends with directions for further research.
