Reinforcement and Imitation Learning via Interactive No-Regret Learning

23 Jun 2014 Stephane Ross J. Andrew Bagnell

Recent work has demonstrated that problems-- particularly imitation learning and structured prediction-- where a learner's predictions influence the input-distribution it is tested on can be naturally addressed by an interactive approach and analyzed using no-regret online learning. These approaches to imitation learning, however, neither require nor benefit from information about the cost of actions... (read more)

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