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  Neural Reinforcement Learning

Dayan, P. (2019). Neural Reinforcement Learning. Talk presented at Humboldt Lecture Series at Tübingen University. Tübingen, Germany. 2019-11-06.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0004-F64E-0 Version Permalink: http://hdl.handle.net/21.11116/0000-0004-F64F-F
Genre: Talk

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 Creators:
Dayan, P1, 2, Author              
Affiliations:
1Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_3017468              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Reinforcement learning has become a wide and deep conduit that links ideas and results in computer science, statistics, control theory and economics to a near century's worth of psychological data on animal and human decision-making, and a fantastic wealth of findings concerning the neural basis of choice. There is a ready and free flow of ideas among these disciplines, providing a powerful foundation for exploring some of the complexities of both normal and abnormal behaviours. I will provide an overview, illustrating the themes with examples showing how far we have come, and how far we still have to go. The lecture will be followed up by a reception.

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 Dates: 2019-11
 Publication Status: Published online
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Title: Humboldt Lecture Series at Tübingen University
Place of Event: Tübingen, Germany
Start-/End Date: 2019-11-06
Invited: Yes

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