Master reinforcement learning, a popular area of machine learning, starting with the basics. Discover how agents and the environment evolve and gain a clear picture of their interrelation. You'll then work with theories related to reinforcement learning and explore the concepts that build the reinforcement learning process. The book discusses algorithm implementations important for reinforcement learning, including Markov's Decision Process and Semi Markov Decision Process. The next section shows you how to get started with OpenAI before looking at OpenAI Gym. You'll then learn about swarm intelligence with Python in terms of reinforcement learning. The last part of the book begins with the TensorFlow environment and outlines how reinforcement learning can be applied to TensorFlow. There's also coverage of Keras, a framework that can be used with reinforcement learning.