Summary

Congratulations! You just learned four important things. The first one is how to implement an Atari game emulator using gym, and how to play Atari games for relaxation and having fun. The second one is that you learned how to preprocess data in reinforcement learning tasks such as Atari games. For practical machine learning applications, you will spend a great deal of time on understanding and refining data, which affects the performance of an AI system a lot. The third one is the deep Q-learning algorithm. You learned the intuition behind it, for example, why the replay memory is necessary, why the target network is needed, where the update rule comes from, and so on. The final one is that you learned how to implement DQN using TensorFlow, and how to visualize the training process. Now, you are ready for the more advanced topics that we will discuss in the following chapters.

In the next chapter, you will learn how to simulate classic control tasks, and how to implement the state...