What Do Animals Really Learn? Adventures of Reinforcement Learning in the Real World

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About Interdisciplinary

Interdisciplinary lectures are open to the public and are held at the Gerald D. Fischbach Auditorium at the Simons Foundation headquarters in New York City. Tea is served prior to each lecture.

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Animals and humans alike can quickly learn to associate different stimuli in the environment with rewards or punishments. In recent years, ideas from the computational field of reinforcement learning have revolutionized the study of learning in the brain, providing new, precise theories of how such associations are formed. However, although these learning algorithms work well in simplified laboratory scenarios, they are known to suffer from the “curse of dimensionality” that makes learning in complex, multidimensional scenarios infeasible. How does the brain scale reinforcement learning to realistic tasks?

In this lecture, Yael Niv will argue that the key to learning efficiently in real-world scenarios is to use a simplified representation of the task that includes only those dimensions of the environment that are relevant to obtaining reward. This, however, raises the new question of how such task representations are learned. She will first demonstrate, using behavioral experiments, that animals and humans learn the causal, often hidden structure of a task, thus forming a concise task representation through experience. Dr. Niv will then suggest that these task representations reside in the orbitofrontal cortex, and show how we can visualize these mental maps of task space and how these maps are related to behavioral performance.

About the Speaker

Dr. Yael Niv is associate professor of psychology and neuroscience at Princeton University. Her work investigates the neural and computational processes underlying reinforcement learning—the ongoing day-to-day processes by which we learn from trial and error to maximize reward and minimize punishment. She is the recipient of the 2015 National Academy of Sciences Troland Research Award, and the 2012 Presidential Early Career Award for Scientists and Engineers, is an Ellison Foundation Scholar and was an Alfred P. Sloan Research Fellow.

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