Practical Machine Learning Cookbook

Chapter 8. Reinforcement Learning

In this chapter, we will cover the following recipes:

• Markov chains - the stocks regime switching model
• Markov chains - the multi-channel attribution model
• Markov chains - the car rental agency service
• Continuous Markov chains - vehicle service at the gas station
• Monte Carlo simulations - calibrated hull and white short-rates

Introduction

The Markov chain: A sequence  of trials of an experiment is a Markov chain if the outcome of each experiment is one of the set of discrete states, and the outcome of the experiment is dependent only on the present state and not of any of the past states. The probability of changing from one state to another state is represented as. It is called a transition probability. The transition ...