8 papers accepted to NeurIPS

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8 papers accepted to NeurIPS

We are excited about 8 accepted papers with WhiRL members, and look forward to discussing our work at NeurIPS 2019 in Vancouver! Camera ready versions of all papers will be available soon.

“Generalized Off-Policy Actor-Critic” – Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson (https://arxiv.org/abs/1903.11329)

“DAC: The Double Actor-Critic Architecture for Learning Options” – Shangtong Zhang, Shimon Whiteson (https://arxiv.org/abs/1904.12691)

“Fast Efficient Hyperparameter Tuning for Policy Gradient Methods” – Supratik Paul, Vitaly Kurin, Shimon Whiteson (https://arxiv.org/abs/1902.06583)

“VIREL: A Variational Inference Framework for Reinforcement Learning” – Matthew Fellows, Anuj Mahajan, Tim G. J. Rudner, Shimon Whiteson (Spotlight) (https://arxiv.org/abs/1811.01132)

“MAVEN: Multi-Agent Variational Exploration” – Anuj Mahajan, Tabish Rashid, Mikayel Samvelyan, Shimon Whiteson (https://arxiv.org/abs/1910.07483)

“Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Gradient Estimators for Reinforcement Learning” – Gregory Farquhar, Shimon Whiteson, Jakob Foerster (https://arxiv.org/abs/1909.10549)

“Multi-Agent Common Knowledge Reinforcement Learning” – Christian Schroeder de Witt*, Jakob Foerster*, Gregory Farquhar, Philip Torr, Wendelin Boehmer, Shimon Whiteson (https://arxiv.org/abs/1810.11702)

“Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck” – M. Igl, K. Ciosek, Y. Li, S. Tschiatschek, C. Zhang, S. Devlin, K. Hofmann (Work done during an internship at Microsoft Research Cambridge)

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