Python Reinforcement Learning
上QQ阅读APP看书,第一时间看更新

Summary

In this chapter, we learned how to set up our machine by installing Anaconda, Docker, OpenAI Gym, Universe, and TensorFlow. We also learned how to create simulations using OpenAI and how to train agents to learn in an OpenAI environment. Then we came across the fundamentals of TensorFlow followed by visualizing graphs in TensorBoard. 

In the Chapter 3The Markov Decision Process and Dynamic Programming we will learn about Markov Decision Process and dynamic programming and how to solve frozen lake problem using value and policy iteration.