Python libraries for solving reinforcement learning problems implemented in OpenAI gym

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  • 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)

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