Mathematical and Algorithmic Understanding of Reinforcement Learning

Abstract

In this chapter, we will discuss the Bellman Equation and the Markov Decision Process (MDP), which are the basis for almost all the approaches that we will be discussing further. We will thereafter discuss some of the non-model-based approaches for Reinforcement Learning like Dynamic Programming. It is imperative to understand these concepts before going forward to discussing some advanced topics ahead. Finally, we will cover the algorithms like value iteration and policy iteration for solving the MDP.