Teaching Reinforcement Learning Fundamentals in Vocational Education and Training with RoboboSim

The current paper presents an educational resource to introduce Vocational Education and Training (VET) students to the topic of Reinforcement Learning (RL) through a practical activity. Specifically, they have to program a Q-learning algorithm using Python language to obtain a policy that allows a mobile robot to solve a task autonomously in an industrial-like setup. To this end, a 3D simulation platform called RoboboSim, and the Python libraries of the Robobo educational robot are used. The resource has been developed in the scope of the Erasmus + project called AIM@VET, and it has been tested with a group of 12 VET students from Spain, Portugal, and Slovenia. The obtained results have been successful, and students with no previous background on RL have learned its fundamentals through a purely practical methodology. In addition, some drawbacks have been captured from teachers and students, and the resource has been improved accordingly before it was made available through the project web.