Deep Bayesian Nonparametric Learning of Rules and Plans from Demonstrations with a Learned Automaton Prior

Deep Bayesian Nonparametric Learning of Rules and Plans from Demonstrations with a Learned Automaton Prior

<jats:p>We introduce a method to learn imitative policies from expert demonstrations that are interpretable and manipulable. We achieve interpretability by modeling the interactions between high-level actions as an automaton with connections to formal logic. We achieve manipulability by integr...

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Bibliographic Details
Main Authors: Araki, Brandon, Vodrahalli, Kiran, Leech, Thomas, Vasile, Cristian-Ioan, Donahue, Mark, Rus, Daniela
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:English
Published: Association for the Advancement of Artificial Intelligence (AAAI) 2021
Online Access:https://hdl.handle.net/1721.1/135230

Internet

https://hdl.handle.net/1721.1/135230

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