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Standard dynamics models for continuous control make use of feedforward computation to predict the conditional distribution of next state and reward given current state and action using a multivariate Gaussian with a diagonal covariance structure.
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Pilco: A model-based and data-efficient approach to policy search
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Miroslav Dudík, John Langford, and Lihong Li · 2011
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Neural machine translation by jointly learning to align and translate
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Adam: A method for stochastic optimization
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On minimax optimal offline policy evaluation
Lihong Li, Remi Munos, and Csaba Szepesvári · 2014
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Offline policy evaluation across representations with applications to educational games
Travis Mandel, Yun-En Liu, Sergey Levine, Emma Brunskill, and Zoran Popovic · 2014
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Off-policy model-based learning under unknown factored dynamics
Assaf Hallak, François Schnitzler, Timothy Mann, and Shie Mannor · 2015
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Model predictive path integral control using covariance variable importance sampling
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Wavenet: A generative model for raw audio
Aaron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew Senior, and Koray Kavukcuoglu · 2016
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Distributed distributional deterministic policy gradients
Gabriel Barth-Maron, Matthew W Hoffman, David Budden, Will Dabney, Dan Horgan, Dhruva Tb, Alistair Muldal, Nicolas Heess, and Timothy Lillicrap · 2018
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Deep reinforcement learning in a handful of trials using probabilistic dynamics models
Kurtland Chua, Roberto Calandra, Rowan McAllister, and Sergey Levine · 2018
Empirical study of off-policy policy evaluation for reinforcement learning
Cameron Voloshin, Hoang M Le, Nan Jiang, and Yisong Yue · 2019
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Benchmarking model-based reinforcement learning
Tingwu Wang, Xuchan Bao, Ignasi Clavera, Jerrick Hoang, Yeming Wen, Eric Langlois, Shunshi Zhang, Guodong Zhang, Pieter Abbeel, and Jimmy Ba · 2019
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Behavior regularized offline reinforcement learning
Yifan Wu, George Tucker, and Ofir Nachum · 2019
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An optimistic perspective on offline reinforcement learning
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Model-Ensemble Trust-Region Policy Optimization
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Breaking the curse of horizon: Infinite-horizon off-policy estimation
Qiang Liu, Lihong Li, Ziyang Tang, and Dengyong Zhou · 2018
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Neural network dynamics for model-based deep reinforcement learning with model-free fine-tuning
Anusha Nagabandi, Gregory Kahn, Ronald S Fearing, and Sergey Levine · 2018
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Language models are few-shot learners
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Statistical bootstrapping for uncertainty estimation in off-policy evaluation, 2020
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Objective mismatch in model-based reinforcement learning
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Hyperparameter selection for offline reinforcement learning
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Off-policy evaluation via the regularized lagrangian, 2020
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Benchmarks for deep off-policy evaluation
Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, and Thomas Paine · 2021
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