Epsilon-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning

Epsilon-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning. Gimelfarb, M., Sanner, S., & Lee, C. In Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI-19), Tel Aviv, Israel, 2019.

Paper bibtex 6 downloads

@inproceedings{sanner:uai19,
  author = {Michael Gimelfarb and Scott Sanner and Chi-Guhn Lee},
  title = {Epsilon-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning},
  year = {2019},
  booktitle = {Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence ({UAI-19})},
  address = {Tel Aviv, Israel},
  url_paper = {https://ssanner.github.io/papers/uai19_epsbmc.pdf}
}

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