MANGA: Method Agnostic Neural-policy Generalization and Adaptation

19 Nov 2019Homanga BharadhwajShoichiro YamaguchiShin-ichi Maeda

In this paper we target the problem of transferring policies across multiple environments with different dynamics parameters and motor noise variations, by introducing a framework that decouples the processes of policy learning and system identification. Efficiently transferring learned policies to an unknown environment with changes in dynamics configurations in the presence of motor noise is very important for operating robots in the real world, and our work is a novel attempt in that direction... (read more)

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