Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning

Andrea Zanette, Martin J. Wainwright, Emma Brunskill. Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning. In Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, editors, Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual. pages 13626-13640, 2021. [doi]

@inproceedings{ZanetteWB21,
  title = {Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning},
  author = {Andrea Zanette and Martin J. Wainwright and Emma Brunskill},
  year = {2021},
  url = {https://proceedings.neurips.cc/paper/2021/hash/713fd63d76c8a57b16fc433fb4ae718a-Abstract.html},
  researchr = {https://researchr.org/publication/ZanetteWB21},
  cites = {0},
  citedby = {0},
  pages = {13626-13640},
  booktitle = {Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual},
  editor = {Marc'Aurelio Ranzato and Alina Beygelzimer and Yann N. Dauphin and Percy Liang and Jennifer Wortman Vaughan},
}