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Reinforcement Learning with TensorFlow
book

Reinforcement Learning with TensorFlow

by Sayon Dutta
April 2018
Intermediate to advanced content levelIntermediate to advanced
334 pages
10h 18m
English
Packt Publishing
Content preview from Reinforcement Learning with TensorFlow

Model and training

Here, a deep Q-network is trained for which two models are used to create a part of state representation of the agent. The two models are as follows:

  • ImageZooms model
  • Pool45-Crops model

For the Image-Zooms model, each region is resized to 224x224 and fed into VGG-16 through the Pool5 layer to obtain a feature map. For the Pool45-Crops model, the image at full-resolution is fed into VGG-16 through the Pool5 layer. The feature maps extracted from the whole image for all the regions of interest (ROI) is pooled.

The two models for feature extraction outputs a feature map of 7x7, which is fed into the common block (as shown in the following architecture). These feature maps and the memory vector (discussed previously) are ...

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Publisher Resources

ISBN: 9781788835725Supplemental Content