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In this work, we aim to teach robots to manipulate various thin-shell materials.
Completely derandomized self-adaptation in evolution strategies
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Earlier work this paper cites.
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Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction
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