Reinforcement learning with Marr

Citation:

Niv, Y., & Langdon, A. J. (2016). Reinforcement learning with Marr. Current Opinion in Behavioral Sciences , 11, 67–73.

ISSN:

2352-1546

Abstract:

To many, the poster child for David Marr's famous three levels of scientific inquiry is reinforcement learning – a computational theory of reward optimization, which readily prescribes algorithmic solutions that evidence striking resemblance to signals found in the brain, suggesting a straightforward neural implementation. Here we review questions that remain open at each level of analysis, concluding that the path forward to their resolution calls for inspiration across levels, rather than a focus on mutual constraints.

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DOI:

http://dx.doi.org/10.1016/j.cobeha.2016.04.005
Last updated on 12/11/2019