| Literature DB >> 27408906 |
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.Entities:
Year: 2016 PMID: 27408906 PMCID: PMC4939081 DOI: 10.1016/j.cobeha.2016.04.005
Source DB: PubMed Journal: Curr Opin Behav Sci ISSN: 2352-1546