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Practice Makes Perfect: Planning to Learn Skill Parameter Policies
Feb. 26, 2024, 5:43 a.m. | Nishanth Kumar, Tom Silver, Willie McClinton, Linfeng Zhao, Stephen Proulx, Tom\'as Lozano-P\'erez, Leslie Pack Kaelbling, Jennifer Barry
cs.LG updates on arXiv.org arxiv.org
Abstract: One promising approach towards effective robot decision making in complex, long-horizon tasks is to sequence together parameterized skills. We consider a setting where a robot is initially equipped with (1) a library of parameterized skills, (2) an AI planner for sequencing together the skills given a goal, and (3) a very general prior distribution for selecting skill parameters. Once deployed, the robot should rapidly and autonomously learn to improve its performance by specializing its skill …
abstract arxiv cs.lg cs.ro decision decision making horizon learn library making planning practice robot sequencing skills tasks together type
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