For now, this category only contains system for drl papers and projects.
- Mao, Hongzi, et al. "Park: An Open Platform for Learning-Augmented Computer Systems." Advances in Neural Information Processing Systems. 2019.
- Summary: This work builds a platform to introduce DRL to computer system optimizaton. It provides a lot of APIs so researcher can focus on developing algorithm rather spend a lot of time on writing system engineering codes.
- Ray: A Distributed Framework for Emerging {AI} Applications [GitHub]
- Moritz, Philipp, et al. (OSDI 2018)
- Summary: Distributed DRL training, simulation and inference system. Can be used as a high-performance python framework.
- Elf: An extensive, lightweight and flexible research platform for real-time strategy games [Paper] [GitHub]
- Tian, Yuandong, Qucheng Gong, Wenling Shang, Yuxin Wu, and C. Lawrence Zitnick. (NIPS 2017)
- Summary:
- Horizon: Facebook's Open Source Applied Reinforcement Learning Platform [Paper] [GitHub]
- Gauci, Jason, et al. (preprint 2019)
- RLgraph: Modular Computation Graphs for Deep Reinforcement Learning [Paper][GitHub]
- Schaarschmidt, Michael, Sven Mika, Kai Fricke, and Eiko Yoneki. (SysML 2019)
- Summary:
- Stable-Baselines: Stable-Baselines3: Reliable Reinforcement Learning Implementations 2021