archsyscall/DeepRL-TensorFlow2
🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
This project provides straightforward implementations of popular Deep Reinforcement Learning algorithms using TensorFlow2. It helps students and researchers understand how these algorithms work by offering clean, single-file code examples. You input defined environments and the project outputs trained models capable of learning optimal strategies for various tasks.
606 stars. No commits in the last 6 months.
Use this if you are a student or researcher studying Deep Reinforcement Learning and need clear, easy-to-understand code examples for various algorithms.
Not ideal if you need a high-level API for rapidly deploying reinforcement learning solutions without focusing on the underlying algorithmic details.
Stars
606
Forks
138
Language
Python
License
Apache-2.0
Category
Last pushed
Jun 04, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/archsyscall/DeepRL-TensorFlow2"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
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