4.4 Article

Reinforcement learning with Marr

期刊

CURRENT OPINION IN BEHAVIORAL SCIENCES
卷 11, 期 -, 页码 67-73

出版社

ELSEVIER
DOI: 10.1016/j.cobeha.2016.04.005

关键词

-

资金

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

向作者/读者索取更多资源

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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据