Status: Maintenance (expect bug fixes and minor updates)
Change(s):
- Pytorch implementation of PointNet in
common.py
- Adapted PPO_pytorch with PointNet. It can now learn from point cloud data. (Other algorithms coming soon..)
This is an educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL).
For the unfamiliar: reinforcement learning (RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with deep learning.
This module contains a variety of helpful resources, including:
- a short introduction to RL terminology, kinds of algorithms, and basic theory,
- an essay about how to grow into an RL research role,
- a curated list of important papers organized by topic,
- a well-documented code repo of short, standalone implementations of key algorithms,
- and a few exercises to serve as warm-ups.
Get started at spinningup.openai.com!
If you reference or use Spinning Up in your research, please cite:
@article{SpinningUp2018,
author = {Achiam, Joshua},
title = {{Spinning Up in Deep Reinforcement Learning}},
year = {2018}
}