Fundamentals of Reinforcement Learning

Reinforcement Learning is a subfield of Machine Learning, but is also a general purpose formalism for automated decision-making and AI. This course introduces you to statistical learning techniques where an agent explicitly takes actions and interacts with the world. Understanding the importance and challenges of learning agents that make decisions is of vital importance today, with more and more companies interested in interactive agents and intelligent decision-making. This course introduces

• Formalize problems as Markov Decision Processes
• Understand basic exploration methods and the exploration / exploitation tradeoff
• Understand value functions, as a general-purpose tool for optimal decision-making
• Know how to implement dynamic programming as an efficient solution approach to an industrial control problem