You're reading from Deep Reinforcement Learning Hands-On. - Second Edition

Product typeBook

Published inJan 2020

Reading LevelIntermediate

PublisherPackt

ISBN-139781838826994

Edition2nd Edition

Languages

Python

Tools

Keras TensorFlow

Concepts

Deep Reinforcement Learning

Author (1)

Maxim Lapan

Adding text descriptions

As the last example of this chapter, we will add text descriptions of the problem into observations of our model. I have already mentioned that some problems contain vital information given in a text description, like the index of tabs needed to be clicked or the list of entries that the agent needs to check. The same information is shown on top of the image observation, but pixels are not always the best representation of simple text.

To take this text into account, we need to extend our model's input from an image only to an image and text data. We worked with text in the previous chapter, so a recurrent neural network (RNN) is quite an obvious choice (maybe not the best for such a toy problem, but it is flexible and scalable).

Implementation

I'm not going to cover this example in detail but will just focus on the most important points of the implementation. (The whole code is in Chapter16/wob_click_mm_train.py.) In comparison to our clicker...

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Deep Reinforcement Learning Hands-On. - Second Edition

Published in: Jan 2020Publisher: PacktISBN-13: 9781838826994

Author (1)

Maxim Lapan

Maxim has been working as a software developer for more than 20 years and was involved in various areas: distributed scientific computing, distributed systems and big data processing. Since 2014 he is actively using machine and deep learning to solve practical industrial tasks, such as NLP problems, RL for web crawling and web pages analysis. He has been living in Germany with his family.
Read more about Maxim Lapan

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You're reading from Deep Reinforcement Learning Hands-On. - Second Edition

Adding text descriptions

Implementation

Unlock this book and the full library FREE for 7 days

Author (1)

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