4.4 Article

Reinforcement learning with Marr

Journal

CURRENT OPINION IN BEHAVIORAL SCIENCES
Volume 11, Issue -, Pages 67-73

Publisher

ELSEVIER
DOI: 10.1016/j.cobeha.2016.04.005

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Funding

  1. Human Frontier Science Program Organization
  2. NIMH [R01MH098861]

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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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