Model-Based RL

Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models and Amortized Policy Search ICML 2022 Pareto Set Learning for Expensive Multi-Objective Optimization NeurIPS 2022 S2P: State-conditioned Image Synthesis for Data Augmentation in Offline Reinforcement Learning NeurIPS 2022 Sample-Efficient Reinforcement Learning via Conservative Model-Based Actor-Critic AAAI 2022 Minimax Model Learning AISTATS 2021 PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators NeurIPS 2021 Weighted model estimation for offline model-based reinforcement learning NeurIPS 2021 Deep Model-Based Reinforcement Learning via Estimated Uncertainty and Conservative Policy Optimization AAAI 2020 Examination and Extension of Strategies for Improving Personalized Language Modeling via Interpolation ACL 2020 Generalized Hidden Parameter MDPs:Transferable Model-Based RL in a Handful of Trials AAAI 2020 Model-Based Reinforcement Learning with a Generative Model is Minimax Optimal COLT 2020 Uncertainty Based Camera Model Selection CVPR 2020 Universal Value Iteration Networks: When Spatially-Invariant Is Not Universal AAAI 2020 Bootstrap Estimated Uncertainty of the Environment Model for Model-Based Reinforcement Learning AAAI 2019 Explicit Explore-Exploit Algorithms in Continuous State Spaces NeurIPS 2019 Regularizing Trajectory Optimization with Denoising Autoencoders NeurIPS 2019 When to Trust Your Model: Model-Based Policy Optimization NeurIPS 2019 When to use parametric models in reinforcement learning? NeurIPS 2019 Iterative Value-Aware Model Learning NeurIPS 2018 Learning the Reward Function for a Misspecified Model ICML 2018 PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos ICML 2018 Learning Deep CNN Denoiser Prior for Image Restoration CVPR 2017 Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics NeurIPS 2014 Environmental statistics and the trade-off between model-based and TD learning in humans NeurIPS 2011 Closing the Learning-Planning Loop with Predictive State Representations RSS 2010