Getting Started With MarathonEnvs v0.5.0a

I have spent the last two years learning Reinforcement Learning. I created Marathon Environments to help explore the applicability of robotics and locomotion research to Video Games in the domain of Active Ragdoll and Virtual Agents. This tutorial provides a primer on Marathon Environments. Marathon Environments re-implements the classic set of Continuous Control benchmarks typically seen in Deep Reinforcement Learning literature as Unity environments using the ML-Agents toolkit. Marathon Environments was released alongside Unity ML- Agents v0.5 and includes four continuous control environments.