AI Seminar Series 2023: Eric Graves

The AI Seminar is a weekly meeting at the University of Alberta where researchers interested in artificial intelligence (AI) can share their research. Presenters include both local speakers from the University of Alberta and visitors from other institutions. Topics can be related in any way to artificial intelligence, from foundational theoretical work to innovative applications of AI techniques to new fields and problems.

On October 20, Eric Graves, from the University of Alberta, presented “Balancing Bias and Variance in Emphatic Off-policy Reinforcement Learning" at the AI Seminar.

Abstract:

Emphatic algorithms are an under-explored approach to off-policy reinforcement learning that emphasize or de-emphasize learning updates in a way that preserves many of the benefits of on-policy algorithms. However, existing methods for estimating how much to emphasize each update suffer from either extreme variance or extreme bias that can both lead to failure of the learning process in different situations. In this talk, Graves discusses how these disparate algorithms can be combined to balance their strengths and weaknesses and successfully learn in situations where one or both of the constituent algorithms fails.

Watch the full presentation below:

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