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AAAI
2007

Active Imitation Learning

11 years 3 months ago
Active Imitation Learning
Imitation learning, also called learning by watching or programming by demonstration, has emerged as a means of accelerating many reinforcement learning tasks. Previous work has shown the value of imitation in domains where a single mentor demonstrates execution of a known optimal policy for the benefit of a learning agent. We consider the more general scenario of learning from mentors who are themselves agents seeking to maximize their own rewards. We propose a new algorithm based on the concept of transferable utility for ensuring that an observer agent can learn efficiently in the context of a selfish, not necessarily helpful, mentor. We also address the questions of when an imitative agent should request help from a mentor, and when the mentor can be expected to acknowledge a request for help. In analogy with other types of active learning, we call the proposed approach active imitation learning.
Aaron P. Shon, Deepak Verma, Rajesh P. N. Rao
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2007
Where AAAI
Authors Aaron P. Shon, Deepak Verma, Rajesh P. N. Rao
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