Learning Quickly to Plan Quickly Using Modular Meta-Learning
Multi-object manipulation problems in continuous state and action spaces can be solved by planners that search over sampled values for the continuous parameters of operators. The efficiency of these planners depends critically on the effectiveness of the samplers used, but effective sampling in turn...
Main Authors: | Chitnis, Rohan, Kaelbling, Leslie P, Lozano-Pérez, Tomás |
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Other Authors: | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
Format: | Article |
Language: | English |
Published: |
IEEE
2021
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Online Access: | https://hdl.handle.net/1721.1/129777 |
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