Python libraries for solving reinforcement learning problems implemented in OpenAI gym

This page summarizes the projects mentioned and recommended in the original post on reddit.com/r/reinforcementlearning

Our great sponsors
  • Scout APM - Less time debugging, more time building
  • SonarQube - Static code analysis for 29 languages.
  • SaaSHub - Software Alternatives and Reviews
  • d3rlpy

    An offline deep reinforcement learning library

  • rlai

    This is a Python implementation of concepts and algorithms described in "Reinforcement Learning: An Introduction" (Sutton and Barto, 2018, 2nd edition).

    I've worked through several OpenAI Gym environments with my RL library, which is based almost entirely on the RL textbook by Sutton and Barto (case studies here). No neural networks, nothing too fancy. But I do explore JAX for policy gradient methods / continuous control.

  • Scout APM

    Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.

  • Coursera_Reinforcement_Learning

    Coursera Reinforcement Learning Specialization by University of Alberta & Alberta Machine Intelligence Institute

    I meant State Of The Art (SOTA) ;) Look here for a simple implementation of Expected Sarsa ( you can also find sarsa on github) https://github.com/LucasBoTang/Coursera_Reinforcement_Learning/blob/master/02Sample-based_Learning_Methods/02Q-Learning_and_Expected_Sarsa.ipynb

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

Suggest a related project

Related posts