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stable-baselines3
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
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stable-baselines3-contrib
Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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rl-baselines3-zoo
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
https://github.com/DLR-RM/stable-baselines3/issues/18 and https://github.com/DLR-RM/stable-baselines3/issues/160
But as we already have vanilla DQN and QR-DQN (in our contrib repo: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib ) I think it is already a good start for off-policy discrete action algorithms. (QR-DQN is usually competitive vs DQN+extensions)
We also release 100+ trained models in our experimental framework, the rl zoo: https://github.com/DLR-RM/rl-baselines3-zoo
Related posts
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Easily load and upload Stable-baselines3 models from the Hugging Face Hub 🤗
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Can't solve MountainCar-v0 with A2C algorithm (stable-baselines3)
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Stable-Baselines3 v2.0: Gymnasium Support
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Tips and Tricks for RL from Experimental Data using Stable Baselines3 Zoo
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Help comparing Double DQN against another paper's results