July 2018
Intermediate to advanced
254 pages
8h 12m
English
Content preview from Hands-On Intelligent Agents with OpenAI Gym
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Launching the training process
We have now put together all the pieces for the deep Q-learner and are ready to train the agent! Be sure to check out/pull/download the latest code from this book's code repository.
You can pick any environment from the list of Atari environments and train the agent we developed using the following command:
(rl_gym_book) praveen@ubuntu:~/HOIAWOG/ch6$ python deep_Q_learner.py --env "ENV_ID"
In the previous command, ENV_ID is the name/ID of the Atari Gym environment. For example, if you want to train the agent on the pong environment with no frame skip, you would run the following command:
(rl_gym_book) praveen@ubuntu:~/HOIAWOG/ch6$ python deep_Q_learner.py --env "PongNoFrameskip-v4"
By default, the training ...
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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.