Reinforcement learning with Marr

Yael Niv, Angela Langdon

Research output: Contribution to journalReview article

9 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)67-73
Number of pages7
JournalCurrent Opinion in Behavioral Sciences
Volume11
DOIs
StatePublished - Oct 1 2016

All Science Journal Classification (ASJC) codes

  • Cognitive Neuroscience
  • Psychiatry and Mental health
  • Behavioral Neuroscience

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