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A repository for easy understanding of codes in Deep Reinforcement Learning

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RL.Fun.Do

A repository for easy understanding of codes in Deep Reinforcement Learning

This tutorial presents latest research in policy gradient methods for modle-free RL in the following order:

  1. Advantage Actor Critic (A2C)
  1. Continuous control with deep reinforcement learning
  1. Proximal Policy Optimization Algorithms
  1. Trust Region Policy Optimization
  1. Soft Actor Critic Algorithm

I have also updated Soft Actor Critic with tensorboard feature to plot your learning curves.

Here is one of the training sample for MuJoCo HalfCheetah:

If you want a hang in PyTorch then refer my tutorials to get started or the official tutorials.

Best RL courses to refer: