June 2018
Intermediate to advanced
546 pages
13h 30m
English
book
Deep Reinforcement Learning Hands-On
by Oleg Vasilev, Maxim Lapan, Martijn van Otterlo, Mikhail Yurushkin, Basem O. F. Alijla
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Summary
In this chapter, we saw an alternative way of solving RL problems: PG, which is different in many ways from the familiar DQN method. We explored the basic method called REINFORCE, which is a generalization of our first method in RL-domain cross entropy. This method is simple, but, being applied to the Pong environment, didn’t show good results.
In the next chapter, we’ll consider ways to improve the stability of PG by combining both families of value-based and policy-based methods.
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.