If you enjoyed this book, you may be interested in these other books by Packt:

Hands-On Reinforcement Learning with Python
Sudharsan Ravichandiran

ISBN: 978-1-78883-652-4

• Understand the basics of reinforcement learning methods, algorithms, and elements
• Train an agent to walk using OpenAI Gym and Tensorflow
• Understand the Markov Decision Process, Bellman’s optimality, and TD learning
• Solve multi-armed-bandit problems using various algorithms
• Master deep learning algorithms, such as RNN, LSTM, and CNN with applications
• Build intelligent agents using the DRQN algorithm to play the Doom game
• Teach agents to play the Lunar Lander game using DDPG
• Train an agent to win a car racing game using dueling DQN

Python Reinforcement Learning Projects
Rajalingappaa Shanmugamani, Sean Saito, Et al

ISBN: 978-1-78899-161-2

• Train and evaluate neural networks built using TensorFlow for RL
• Use RL algorithms in Python and TensorFlow to solve CartPole balancing
• Create deep reinforcement learning algorithms to play Atari games
• Deploy RL algorithms using OpenAI Universe
• Develop an agent to chat with humans 
• Implement basic actor-critic algorithms for continuous control
• Apply advanced deep RL algorithms to games such as Minecraft
• Autogenerate an image classifier using RL