5.7k citations · 11.9k across the 19 of their papers we have counts for
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cs.LG2016★ 353 cited
Generative Adversarial Imitation Learning
Jonathan Ho, Stefano Ermon
Consider learning a policy from example expert behavior, without interaction with the expert or access to reinforcement signal. One approach is to recover the expert's cost functio…
cs.LG2016★ 41 cited
Model-Free Imitation Learning with Policy Optimization
Jonathan Ho, Jayesh K. Gupta, Stefano Ermon
In imitation learning, an agent learns how to behave in an environment with an unknown cost function by mimicking expert demonstrations. Existing imitation learning algorithms typi…