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...
Main Authors: | , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
Neural Information Processing Systems Foundation,
2018-01-12T19:51:36Z.
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Subjects: | |
Online Access: | Get fulltext |