Mathematical and Algorithmic Understanding of Reinforcement Learning

Abstract

In this chapter, we will discuss the Bellman EquationBellman Equationand the Markov Decision ProcessMarkov Decision ProcessMDP(MDPMDP), 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 iterationValue IterationDynamic Programmingand policy iterationPolicy IterationDynamic Programmingfor solving the MDP.