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Posner Lecture
Neural Reinforcement Learning
Peter Dayan

Sun Dec 08 09:00 AM -- 09:45 AM (PST) @ Harvey's Convention Center Floor, CC

Reinforcement learning has become a wide and deep conduit that links ideas and results in computer science, statistics, control theory and economics to psychological data on animal and human decision-making, and 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 outline some of the happy circumstances that led us to this point; discuss current computational, algorithmic and implementational themes; and provide some pointers to the future.

Author Information

Peter Dayan (Gatsby Unit, UCL)

I am Director of the Gatsby Computational Neuroscience Unit at University College London. I studied mathematics at the University of Cambridge and then did a PhD at the University of Edinburgh, specialising in associative memory and reinforcement learning. I did postdocs with Terry Sejnowski at the Salk Institute and Geoff Hinton at the University of Toronto, then became an Assistant Professor in Brain and Cognitive Science at the Massachusetts Institute of Technology before moving to UCL.

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