A Divergence Minimization Perspective on Imitation Learning Methods

Ghasemipour Seyed Kamyar Seyed
Ghasemipour Seyed Kamyar Seyed
Zemel Richard
Zemel Richard

CoRL, pp. 1259-1277, 2019.

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Other Links: arxiv.org|dblp.uni-trier.de

Abstract:

In many settings, it is desirable to learn decision-making and control policies through learning or bootstrapping from expert demonstrations. The most common approaches under this Imitation Learning (IL) framework are Behavioural Cloning (BC), and Inverse Reinforcement Learning (IRL). Recent methods for IRL have demonstrated the capacit...More

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