Practical Reinforcement Learning Develop self-evolving, intelligent agents with

Chapter 1. Reinforcement Learning In this chapter, we will learn what machine learning is and how reinforcement learning is different from other machine learning techniques, such as supervised learning and unsupervised learning. Furthermore, we will look into reinforcement learning elements such as state, agent, environment, and reward. After that, we will discuss positive and negative reinforcement learning. Then we will explore the latest applications of reinforcement learning. As this book covers both Java and Python programm ing languages, the later part of the chapter will cover various frameworks of reinforcement learning. We will see how to set up the development environment and develop some programs using open-air gym and Brown-UMBC Reinforcement Learning and Planning (BURLAP).