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Oral
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Tue 5:00 |
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot Joel Z Leibo · Edgar Duenez-Guzman · Alexander Vezhnevets · John Agapiou · Peter Sunehag · Raphael Koster · Jayd Matyas · Charles Beattie · Igor Mordatch · Thore Graepel |
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Oral
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Tue 5:00 |
Phasic Policy Gradient Karl Cobbe · Jacob Hilton · Oleg Klimov · John Schulman |
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Oral
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Tue 5:00 |
Deeply-Debiased Off-Policy Interval Estimation Chengchun Shi · Runzhe Wan · Victor Chernozhukov · Rui Song |
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Spotlight
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Tue 5:20 |
UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning Tarun Gupta · Anuj Mahajan · Bei Peng · Wendelin Boehmer · Shimon Whiteson |
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Spotlight
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Tue 5:20 |
Reinforcement Learning with Prototypical Representations Denis Yarats · Rob Fergus · Alessandro Lazaric · Lerrel Pinto |
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Spotlight
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Tue 5:20 |
Offline Contextual Bandits with Overparameterized Models David Brandfonbrener · William Whitney · Rajesh Ranganath · Joan Bruna |
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Spotlight
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Tue 5:25 |
Demonstration-Conditioned Reinforcement Learning for Few-Shot Imitation Christopher Dance · Perez Julien · Théo Cachet |
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Spotlight
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Tue 5:25 |
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning Dong Ki Kim · Miao Liu · Matthew Riemer · Chuangchuang Sun · Marwa Abdulhai · Golnaz Habibi · Sebastian Lopez-Cot · Gerald Tesauro · Jonathan How |
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Spotlight
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Tue 5:25 |
Diversity Actor-Critic: Sample-Aware Entropy Regularization for Sample-Efficient Exploration Seungyul Han · Youngchul Sung |
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Spotlight
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Tue 5:30 |
A New Representation of Successor Features for Transfer across Dissimilar Environments Majid Abdolshah · Hung Le · Thommen Karimpanal George · Sunil Gupta · Santu Rana · Svetha Venkatesh |
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Spotlight
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Tue 5:30 |
Muesli: Combining Improvements in Policy Optimization Matteo Hessel · Ivo Danihelka · Fabio Viola · Arthur Guez · Simon Schmitt · Laurent Sifre · Theophane Weber · David Silver · Hado van Hasselt |
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Spotlight
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Tue 5:30 |
Bias-Robust Bayesian Optimization via Dueling Bandits Johannes Kirschner · Andreas Krause |