Efficient Multi-Task and Multi-Robot Learning

Can robots learn from each other? Is sharing information between robots beneficial? Robots should be able to learn from few demonstrations of a task, and generalize to new tasks in an efficient way. They should also be able to transfer learned experiences to different robots such that the latter can achieve high performance without having to learn from scratch. We explore these questions from a theoretical point of view as well as through experiments.


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University of Toronto Institute for Aerospace Studies