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Creators/Authors contains: "Tiwari, Saket"

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  1. ; ; ; ; (, Proceedings of the Fortieth International Conference on Machine Learning)
    We propose a novel parameterized skill-learning algorithm that aims to learn transferable parameterized skills and synthesize them into a new action space that supports efficient learning in long-horizon tasks. We propose to leverage off-policy Meta-RL combined with a trajectory-centric smoothness term to learn a set of parameterized skills. Our agent can use these learned skills to construct a three-level hierarchical framework that models a Temporally-extended Parameterized Action Markov Decision Process. We empirically demonstrate that the proposed algorithms enable an agent to solve a set of difficult long-horizon (obstacle-course and robot manipulation) tasks. 
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    Accepted Manuscript Full Text Available
  2. ; ; ; ; ; ; ; ; ; ; et al (, Neural Networks)
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