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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 15, Daniel Brown, postdoc at UC Berkeley, presented “Efficient and Robust Learning of Human Intent” at the AI Seminar.
In it, he discusses recent research into autonomous systems that learn reward functions and policies from human demonstrations and preferences. He focuses on the problem of dealing with uncertainty over the true intent of the humans that the system is learning from, and consequently the question of what is the desired behaviour from the system. Brown then goes over the current research on how to counteract this problem.
Watch the full presentation below:
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