A short RL tutorial for an engineering audience

This tutorial aims at introducing the key concepts in (Deep) Reinforcement Learning in a practical, intuitive way, for people who don't know Reinforcement Learning. It keeps the jargon, technicalities and theory as limited as possible in order to leave room for algorithms and individual practice. It supposes the reader has a minimum knowledge of Python and a few basic math (probability and optimization) notions.

The tutorial can be started with docker using docker-compose : open a terminal or powershell and enter

''' docker-compose up '''

Password : deeprl