Grokking Deep Reinforcement Learning

2 Mathematical foundations of reinforcement learning

In this chapter

• You will learn about the core components of reinforcement learning.
• You will learn to represent sequential decision-making problems as reinforcement learning environments using a mathematical framework known as Markov decision processes.
• You will build from scratch environments that reinforcement learning agents learn to solve in later chapters.

Mankind’s history has been a struggle against a hostile environment. We finally have reached a point where we can begin to dominate our environment. ... As soon as we understand this fact, our mathematical interests necessarily shift in many areas from descriptive analysis to control theory.

— Richard Bellman American applied mathematician, ...