WebMay 8, 2024 · On-policy imitation learning algorithms such as Dagger evolve a robot control policy by executing it, measuring performance (loss), obtaining corrective feedback from a supervisor, and generating the next policy. As the loss between iterations can vary unpredictably, a fundamental question is under what conditions this process will … WebWe call this problem the “DAgger problem” as it is reminiscent of a previous RL method [15] that suffered from the inability to generalize because it cannot work on states that an expert has not been to.... [15] S. Ross, G. J. Gordon, and J. A. Bagnell. No-regret reductions for imitation learning and structured prediction.

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