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Jun, 2022
学习神经符号技能以进行双层规划
Learning Neuro-Symbolic Skills for Bilevel Planning
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Tom Silver, Ashay Athalye, Joshua B. Tenenbaum, Tomas Lozano-Perez, Leslie Pack Kaelbling
TL;DR
本研究中,通过将符号操作和神经采样器与参数化策略相结合,将它们打包成模块化的神经符号技能,并将其顺序化组合为搜索-采样二层任务和动作规划来解决新任务。在四个机器人领域的实验中,展示了具有神经符号技能的二层规划策略能够解决各种具有不同初始状态、目标和对象的任务,优于六个基线和消融。
Abstract
decision-making
is challenging in
robotics
environments with continuous object-centric states, continuous actions, long horizons, and sparse feedback. Hierarchical approaches, such as
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