Summary

Congratulations, readers; you have made it to the end! We covered basic concepts related to reinforcement learning in this chapter. You learned about the various concepts and algorithms of building the gaming bot. You also learned how the Deep Q Learner algorithm works. Using the gym library, we loaded the gaming world. By using the dqn library, we will be able to train the model. Training a gaming bot that can defeat human level experts takes a lot of time. So, I trained it for a few hours only. If you want to train for more hours, you can definitely do that. We tried to build a variety of simple Atari games, such as a simple pathfinder gaming bot, Space Invaders, Pong, and Flappy Bird. You can expand this basic approach to the bigger gaming environment. If you want to get yourself updated and contribute, then you can take a look at the OpenAI GitHub repository at: https://github.com/openai. Deep Mind news and the blog section are at this link: https://deepmind.com/blog/ .

In the...