Adversarial Actor-Critic Method for Task and Motion Planning Problems Using Planning Experience

Adversarial Actor-Critic Method for Task and Motion Planning Problems Using Planning Experience

We propose an actor-critic algorithm that uses past planning experience to improve the efficiency of solving robot task-and-motion planning (TAMP) problems. TAMP planners search for goal-achieving sequences of high-level operator instances specified by both discrete and continuous parameters. Our al...

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Bibliographic Details
Main Authors: Kim, Beomjoon (Author), Kaelbling, Leslie P (Author), Lozano-Pérez, Tomás (Author)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: Association for the Advancement of Artificial Intelligence (AAAI), 2021-03-02T19:31:01Z.
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