July 2018
Intermediate to advanced
254 pages
8h 12m
English
Content preview from Hands-On Intelligent Agents with OpenAI Gym
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Revisiting the epsilon-greedy action policy
In the previous chapter, we discussed the 
-greedy action selection policy which takes the best action as per the agent's action-value estimate with a probability of 1-
and takes a random action with a probability given by epsilon, 
. Epsilon is a hyperparameter that can be tuned based on the experiments to a good value. A higher value of means that the agent's actions will be random and a lower value ...
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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.