In this tutorial we will implement the paper Continuous Control with Deep Reinforcement Learning, published by Google DeepMind and presented as a conference paper at ICRL 2016. The networks will be implemented in PyTorch and using OpenAI gym. The algorithm combines Deep Learning and Reinforcement Learning techniques to deal with high-dimensional, i.e. continuous, action spaces.
This is a companion discussion topic for the original entry at https://blog.paperspace.com/physics-control-tasks-with-deep-reinforcement-learning