Scalable reward learning from demonstration

Robotics and Automation, 2013, Pages 303-308.

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Abstract:

Reward learning from demonstration is the task of inferring the intents or goals of an agent demonstrating a task. Inverse reinforcement learning methods utilize the Markov decision process (MDP) framework to learn rewards, but typically scale poorly since they rely on the calculation of optimal value functions. Several key modifications ...More

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