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LightZero is an efficient, scalable, and open-source framework implementing MuZero, a powerful model-based reinforcement learning algorithm that learns to predict rewards and transitions without explicit environment models. Developed by OpenDILab, LightZero focuses on providing a highly optimized and user-friendly platform for both academic research and industrial applications of MuZero and similar algorithms.
Features
- Full implementation of MuZero for model-based RL
- Highly efficient and scalable for large-scale training
- Modular and extensible architecture for custom research
- Supports a variety of Gym and custom environments
- Includes pre-built pipelines for training, evaluation, and benchmarking
- Offers tools for visualizing agent learning and model predictions
Project Samples
Categories
Reinforcement Learning AlgorithmsLicense
Apache License V2.0Follow LightZero
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