Inverse reinforcement learning with locally consistent reward functions

Existing inverse reinforcement learning (IRL) algorithms have assumed each expert's demonstrated trajectory to be produced by only a single reward function. This paper presents a novel generalization of the IRL problem that allows each trajectory to be generated by multiple locally consistent r...

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Bibliographic Details
Main Authors: Nguyen, Quoc Phong (Author), Low, Bryan Kian Hsiang (Author), Jaillet, Patrick (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: Neural Information Processing Systems Foundation, 2018-01-12T19:51:36Z.
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