Shypd.aiThe largest open index of AI toolsgarage is an open-source toolkit for reproducible reinforcement learning research. It provides modular tools for developing and evaluating RL algorithms, supporting PyTorch and TensorFlow frameworks.
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garage is a comprehensive, open-source toolkit designed for developing and evaluating reinforcement learning (RL) algorithms, emphasizing reproducibility in research. It offers a wide array of modular tools, including composable neural network models, high-performance samplers, replay buffers, and an expressive experiment definition interface. The toolkit supports logging to various outputs like TensorBoard, ensures reliable experiment checkpointing and resuming, and provides environment interfaces for popular benchmark suites. garage is compatible with Python 3.6+ and supports both PyTorch and TensorFlow for neural network implementations, with algorithms not requiring neural networks found in the `garage.np` package. Its robust testing strategy, including continuous integration and comprehensive benchmarks, ensures state-of-the-art performance and reliability.
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