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Generalizing to New Physical Systems via Context-Informed Dynamics Model. (arXiv:2202.01889v3 [cs.LG] UPDATED)
June 27, 2022, 1:11 a.m. | Matthieu Kirchmeyer, Yuan Yin, Jérémie Donà, Nicolas Baskiotis, Alain Rakotomamonjy, Patrick Gallinari
stat.ML updates on arXiv.org arxiv.org
Data-driven approaches to modeling physical systems fail to generalize to
unseen systems that share the same general dynamics with the learning domain,
but correspond to different physical contexts. We propose a new framework for
this key problem, context-informed dynamics adaptation (CoDA), which takes into
account the distributional shift across systems for fast and efficient
adaptation to new dynamics. CoDA leverages multiple environments, each
associated to a different dynamic, and learns to condition the dynamics model
on contextual parameters, specific to …
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