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Found 3 papers, 2 papers with code
MBRL-Lib: A Modular Library for Model-based Reinforcement Learning
MBRL-Lib is designed as a platform for both researchers, to easily develop, debug and compare new algorithms, and non-expert user, to lower the entry-bar of deploying state-of-the-art algorithms.
Model-based Reinforcement Learning
reinforcement-learning
+1
Learning Accurate Long-term Dynamics for Model-based Reinforcement Learning
Accurately predicting the dynamics of robotic systems is crucial for model-based control and reinforcement learning.
Model-based Reinforcement Learning
reinforcement-learning
+1
Low Level Control of a Quadrotor with Deep Model-Based Reinforcement Learning
Designing effective low-level robot controllers often entail platform-specific implementations that require manual heuristic parameter tuning, significant system knowledge, or long design times.
Model-based Reinforcement Learning
reinforcement-learning
+1
