June 2018
Intermediate to advanced
318 pages
9h 24m
English
Content preview from Hands-On Reinforcement Learning with Python
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Target network
In our loss function, we calculate the squared difference between a target and predicted value:
We are using the same Q function for calculating the target value and the predicted value. In the preceding equation, you can see the same weights 
are used for both target Q and predicted Q. Since the same network is calculating the predicted value and target value, there could be a lot of divergence between these two.
To avoid this problem, we use a separate network called a target network for calculating the target value. So, our ...
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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.