A differentiable neural model recovers ground-truth lifted action schemas from state traces by jointly learning schemas and inferring unobserved action arguments.
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Differentiable Learning of Lifted Action Schemas for Classical Planning
A differentiable neural model recovers ground-truth lifted action schemas from state traces by jointly learning schemas and inferring unobserved action arguments.