Online Brain Science Seminar Series (BSS)

Online Brain Science Seminar Series(Online BSS)
Dr. Matthew Botvinick

Director of Neuroscience and Team Lead in AGI Research, DeepMind
Honorary Professor, Gatsby Computational Neuroscience Unit, University College London


Thursday, May 12, 2021, 9:00-10:30


Deep reinforcement learning and its neuroscientific implications

The last few years have seen some dramatic developments in artificial intelligence research. What implications might these have for neuroscience and psychology? Investigations of this question have, to date, focused largely on deep neural networks trained using supervised learning, in tasks such as image classification. In this talk, I’ll discuss another area of recent AI work which has so far received less attention from neuroscientists and psychologists, but which may have more profound implications: Deep reinforcement learning. Deep RL provides a rich framework for studying the interplay among learning, representation and decision-making, offering to the brain sciences a new set of research tools and a wide range of novel hypotheses. I’ll provide a high level introduction to deep RL and survey some of its key implications for research on the brain and behavior.


Matthew Botvinick, M.D., Ph.D. is Director of Neuroscience Research at DeepMind and Honorary Professor at the Gatsby Computational Neuroscience Unit at University College London. Botvinick completed his undergraduate studies at Stanford University in 1989 and medical studies at Cornell University in 1994, before completing a Ph.D. in Psychology and Cognitive Neuroscience at the Neural Basis for Cognition at Carnegie Mellon University in 2001. Botvinick served as Assistant Professor of Psychiatry and Psychology at the University of Pennsylvania until 2007 and Professor of Psychology and Neuroscience at Princeton University until joining DeepMind in 2016. Botvinick’s work at DeepMind straddles the boundaries between cognitive psychology, computational and experimental neuroscience and artificial intelligence.


Rei Akaishi, Ph.D.

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