Discovering State and Action Abstractions for Generalized Task and Motion Planning

<jats:p>Generalized planning accelerates classical planning by finding an algorithm-like policy that solves multiple instances of a task. A generalized plan can be learned from a few training examples and applied to an entire domain of problems. Generalized planning approaches perform well in...

全面介绍

书目详细资料
Main Authors: Curtis, Aidan, Silver, Tom, Tenenbaum, Joshua B, Lozano-Pérez, Tomás, Kaelbling, Leslie
其他作者: Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
格式: 文件
语言:English
出版: Association for the Advancement of Artificial Intelligence (AAAI) 2023
在线阅读:https://hdl.handle.net/1721.1/150399