Neural Reinforcement Learning

Dayan, P

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Neural Reinforcement Learning

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Dayan, P
Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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https://uni-tuebingen.de/einrichtungen/zentrale-einrichtungen/forum-scientiarum/veranstaltungen/vorlesungsreihen/humboldt-lecture-series/winter1920/dayan/
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Citation

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

Cite as: https://hdl.handle.net/21.11116/0000-0004-F64E-0

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.