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• W2337330 abstract "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." @default.
• W2337330 created "2016-06-24" @default.
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• W2337330 date "2007-07-22" @default.
• W2337330 modified "2023-09-24" @default.
• W2337330 title "Active imitation learning" @default.
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