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Experience Selection Using Dynamics Similarity for Efficient Multi-Source Transfer Learning Between Robots
We show that selecting experiences based on the proposed similarity metric effectively facilitates the learning of the target quadrotor, improving performance by 62% compared to a poorly selected experience.
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