rlgraph/rlgraph
RLgraph: Modular computation graphs for deep reinforcement learning
This is a framework for machine learning researchers and practitioners who develop and test reinforcement learning (RL) algorithms. It takes your RL algorithm definitions and executes them, providing a flexible way to move from rapid prototyping to large-scale, distributed training. Users would be machine learning engineers or researchers working on AI agents.
323 stars. No commits in the last 6 months.
Use this if you need a flexible way to prototype and then scale reinforcement learning algorithms using either TensorFlow or PyTorch, potentially across multiple GPUs or distributed systems.
Not ideal if you are looking for a pre-built, plug-and-play RL solution without needing to dive into algorithm definition and framework configurations.
Stars
323
Forks
40
Language
Python
License
Apache-2.0
Category
Last pushed
Nov 05, 2019
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/rlgraph/rlgraph"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
DLR-RM/stable-baselines3
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
google-deepmind/dm_control
Google DeepMind's software stack for physics-based simulation and Reinforcement Learning...
Denys88/rl_games
RL implementations
pytorch/rl
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
yandexdataschool/Practical_RL
A course in reinforcement learning in the wild