Users will be taken through a journey that starts by showing them the various algorithms that can be used for reward-based learning. The video describes and compares the range of model-based and model-free learning algorithms that constitute RL algorithms.

The primary aim is to learn how to create efficient, goal-oriented business policies, and how to evaluate and optimize those policies, primarily using the MDPtoolbox package in R. Finally, the video shows how to build actions, rewards, and punishments with a simulated annealing approach.