heronsystems/adeptRL
Reinforcement learning framework to accelerate research
This framework helps machine learning researchers rapidly experiment with deep reinforcement learning models. You can input custom models, agents, and environments to train them efficiently, even across multiple GPUs. It outputs trained models, performance logs, and evaluations, ideal for researchers focused on advancing AI algorithms.
206 stars. No commits in the last 6 months. Available on PyPI.
Use this if you are a machine learning researcher who needs to quickly prototype and train novel deep reinforcement learning algorithms and models.
Not ideal if you are a practitioner looking for an out-of-the-box solution to apply existing reinforcement learning models without custom algorithm development.
Stars
206
Forks
26
Language
Python
License
GPL-3.0
Category
Last pushed
Aug 25, 2021
Commits (30d)
0
Dependencies
10
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