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arXiv:1801.06503stat.ML

Global overview of Imitation Learning

Alexandre Attia, Sharone Dayan

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Abstract

Imitation Learning is a sequential task where the learner tries to mimic an expert's action in order to achieve the best performance. Several algorithms have been proposed recently for this task. In this project, we aim at proposing a wide review of these algorithms, presenting their main features and comparing them on their performance and their regret bounds.

arXiv comments
9 pages, 5 figures, 5 appendix pages
Journal reference
DOI
Subjects
stat.MLMachine Learning (Statistics) cs.LGMachine Learning

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