July 2018
Intermediate to advanced
254 pages
8h 12m
English
Content preview from Hands-On Intelligent Agents with OpenAI Gym
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Double Q-Learning
In Double Q-Learning, there are two action-value/Q functions. Let's call them Q1 and Q2. The idea in double Q-learning is to decouple action selection from the value estimation. That is, when we want to update Q1, we select the best action according to Q1, but use Q2 to find the value of the selected action. Similarly, when Q2 is being updated, we select the action based on Q2, but use Q1 to determine the value of the selected action. In practice, we can use the main Q network 
as Q1 and the slow-moving target network 
as Q2, ...
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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.