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TensorHouse is a scalable reinforcement learning (RL) platform that focuses on high-throughput experience generation and distributed training. It is designed to efficiently train agents across multiple environments and compute resources. TensorHouse enables flexible experiment management, making it suitable for large-scale RL experiments in both research and applied settings.
Features
- Supports distributed and parallel RL training across multiple nodes
- High-throughput experience collection from multiple environments
- Modular and extensible framework for custom algorithm integration
- Efficient resource management and task orchestration
- Includes tools for tracking experiments and analyzing results
- Compatible with existing RL libraries and custom policies
Project Samples
Categories
Reinforcement Learning Frameworks, Reinforcement Learning Libraries, Reinforcement Learning AlgorithmsLicense
Apache License V2.0Follow TensorHouse
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