4 – Resources

In this course, you’ll learn about many classical algorithms in reinforcement learning. You may discover that some algorithms are initially harder to conceptualize than others. If at any point you’d like to have a conversation to deepen your understanding, we encourage you to start a thread in the slack channels. We at Udacity believe in learning by doing. So for all of the algorithms we’ll discuss, you’ll write your own implementations. Just watching the videos should be enough to pass the course. But if you’d like to go above and beyond, we have a few suggestions. First, the most popular textbook on reinforcement learning is available for free online. Throughout the course, we’ll provide recommended readings from this book that you can use to deepen your understanding. It’s a great book and highly enjoyable to read so highly recommended. Second, you’ll encounter quite a few equations while learning about RL. We’ll carefully discuss the meaning behind these equations, but after the lessons finish, be sure to revisit them and make sure that you can describe them in your own words. Make this content yours. It won’t come easily at first but I guarantee you that if you work hard, it’ll be an amazing experience. We hope you’re as excited to learn about this fascinating content as we are to teach you. But that’s all for now. I’ll see you in the next lesson.

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