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CNI Speaker Series: Sam Gershman

Monday, November 14, 2016 - 12:00pm

Barchi Library, 140 John Morgan Building

Sam Gershman
Computational Cognitive Neuroscience Lab
Department of Psychology and Center for Brain Science
Harvard University

Predictive foundations for reinforcement learning

In this talk, I will present a theory of reinforcement learning that falls in between "model-based" and "model-free" approaches. The key idea is to represent a "predictive map" of the environment, which can then be used to efficiently compute values. I show how such a map explains many aspects of the hippocampal representation of space, and the map's eigendecomposition reveals latent structure resembling entorhinal grid cells. I will then present evidence, using novel revaluation tasks, that humans employ such a predictive map to solve reinforcement learning tasks.A pizza lunch will be served.