Maximum Likelihood Constraint Inference for Inverse Reinforcement Learning

While most approaches to the problem of Inverse Reinforcement Learning (IRL) focus on estimating a reward function that best explains an expert agent's policy or demonstrated behavior on a control task, it is often the case that such behavior is more succinctly represented by a simple reward co...

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Hauptverfasser:	Scobee, Dexter R. R, Sastry, S. Shankar
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Learning Computer Science - Robotics Computer Science - Systems and Control Statistics - Machine Learning
Online-Zugang:	Volltext bestellen
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