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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Roboschool
To experiment with the methods in this chapter, we'll use roboschool, which uses PyBullet as a physics engine and has 13 environments of various complexity. PyBullet has similar environments, but at the time of writing it wasn't possible to create several instances of the same environment due to internal OpenGL issue. In this chapter, we'll get in touch with two problems: RoboschoolHalfCheetah-v1, which models a two-legged creature and RoboschoolAnt-v1, which has four legs. The state and action spaces of them are very similar to the Minitaur environment that we saw in the previous chapter: the state includes characteristics from joints and actions are activations of those joints. The goal for both is to move as far as possible, minimizing ...
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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.