navneet-nmk/pytorch-rl
This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch
This is a tool for machine learning researchers and practitioners who are experimenting with deep reinforcement learning. It takes in environment definitions (like those from OpenAI Gym) and outputs trained models that can learn to perform tasks in those environments. It's designed for those working on training AI agents for complex decision-making scenarios.
452 stars. No commits in the last 6 months.
Use this if you need to quickly implement and test various state-of-the-art deep reinforcement learning algorithms for continuous control tasks or robotic simulations.
Not ideal if you are looking for a high-level, no-code solution for applying AI, or if you need to deploy ready-made reinforcement learning models without deep customization.
Stars
452
Forks
56
Language
Python
License
—
Category
Last pushed
Jul 14, 2019
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/navneet-nmk/pytorch-rl"
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