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ICML 2017poster125 citations

End-to-End Differentiable Adversarial Imitation Learning

Nir Baram, Oron Anschel, Itai Caspi, Shie Mannor

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Abstract

Generative Adversarial Networks (GANs) have been successfully applied to the problem of

BibTeX
@InProceedings{pmlr-v70-baram17a,
  title = 	 {End-to-End Differentiable Adversarial Imitation Learning},
  author =       {Nir Baram and Oron Anschel and Itai Caspi and Shie Mannor},
  booktitle = 	 {Proceedings of the 34th International Conference on Machine Learning},
  pages = 	 {390--399},
  year = 	 {2017},
  editor = 	 {Precup, Doina and Teh, Yee Whye},
  volume = 	 {70},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {06--11 Aug},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v70/baram17a/baram17a.pdf},
  url = 	 {https://proceedings.mlr.press/v70/baram17a.html},
  abstract = 	 {Generative Adversarial Networks (GANs) have been successfully applied to the problem of
End-to-End Differentiable Adversarial Imitation Learning · ICML 2017