Imitation Learning via Simultaneous Optimization of Policies and Auxiliary Trajectories

Imitation learning (IL) is a frequently used approach for data-efficient policy learning. Many IL methods, such as Dataset Aggregation (DAgger), combat challenges like distributional shift by interacting with oracular experts. Unfortunately, assuming access to oracular experts is often unrealistic i...

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Bibliographische Detailangaben

Hauptverfasser:	Xie, Mandy, Li, Anqi, Van Wyk, Karl, Dellaert, Frank, Boots, Byron, Ratliff, Nathan
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Computer Science - Robotics
Online-Zugang:	Volltext bestellen
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