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...
Main Authors: | Kim, Beomjoon, Kaelbling, Leslie P, Lozano-Pérez, Tomás |
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Other Authors: | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
Format: | Article |
Published: |
Association for the Advancement of Artificial Intelligence (AAAI)
2021
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Online Access: | https://hdl.handle.net/1721.1/130053 |
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