April 2018
Intermediate to advanced
334 pages
10h 18m
English
Content preview from Reinforcement Learning with TensorFlow
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Asynchronous advantage actor-critic
The A3C algorithm was published in June 2016 by the combined team of Google DeepMind and MILA. It is simpler and has a lighter framework that used the asynchronous gradient descent to optimize the deep neural network. It was faster and was able to show good results on the multi-core CPU instead of GPU. One of A3C's big advantages is that it can work on continuous as well as discrete action spaces. As a result, it has opened the gateway for many new challenging problems that have complex state and action spaces.
We will discuss it at a high note here, but we will dig deeper in Chapter 6, Asynchronous Methods. Let's start with the name, that is, asynchronous advantage actor-critic (A3C) algorithm and unpack ...
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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.