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Model-Based RL

291 papers

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Papers

Improving Transformer World Models for Data-Efficient RL ICML 2025 Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games ICML 2025 Knowledge Retention in Continual Model-Based Reinforcement Learning ICML 2025 KoopMotion: Learning Almost Divergence Free Koopman Flow Fields for Motion Planning CoRL 2025 Learning Dynamics under Environmental Constraints via Measurement-Induced Bundle Structures ICML 2025 Learning Utilities from Demonstrations in Markov Decision Processes ICML 2025 Learning View-invariant World Models for Visual Robotic Manipulation ICLR 2025 LLM-Guided Probabilistic Program Induction for POMDP Model Estimation CoRL 2025 Logarithmic regret of exploration in average reward Markov decision processes COLT 2025 Minimax Optimal Regret Bound for Reinforcement Learning with Trajectory Feedback ICML 2025 Minimax Optimal Reinforcement Learning with Quasi-Optimism ICLR 2025 Model-Based Exploration in Monitored Markov Decision Processes ICML 2025 Model-based Offline Reinforcement Learning with Lower Expectile Q-Learning ICLR 2025 Model-based RL as a Minimalist Approach to Horizon-Free and Second-Order Bounds ICLR 2025 Model predictive control is almost optimal for restless bandits COLT 2025 Monte-Carlo Tree Search with Uncertainty Propagation via Optimal Transport ICML 2025 Multi-Stage Manipulation with Demonstration-Augmented Reward, Policy, and World Model Learning ICML 2025 Near-Optimal Sample Complexity for Iterated CVaR Reinforcement Learning with a Generative Model AISTATS 2025 Necessary and Sufficient Oracles: Toward a Computational Taxonomy for Reinforcement Learning COLT 2025 Neural Robot Dynamics CoRL 2025 Neural Stochastic Differential Equations for Uncertainty-Aware Offline RL ICLR 2025 Neurosymbolic World Models for Sequential Decision Making ICML 2025 Novelty Detection in Reinforcement Learning with World Models ICML 2025 Online Robust Reinforcement Learning Through Monte-Carlo Planning ICML 2025 On Rollouts in Model-Based Reinforcement Learning ICLR 2025