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Deep Reinforcement Learning Hands-On
book

Deep Reinforcement Learning Hands-On

by Oleg Vasilev, Maxim Lapan, Martijn van Otterlo, Mikhail Yurushkin, Basem O. F. Alijla
June 2018
Intermediate to advanced content levelIntermediate to advanced
546 pages
13h 30m
English
Packt Publishing
Content preview from Deep Reinforcement Learning Hands-On

Chapter 12. Chatbots Training with RL

In this chapter, we'll take a look at another practical application of Deep Reinforcement Learning (Deep RL), which has become popular over the Past two years: the training of natural language models with RL methods. It started with a paper called Recurrent Models of Visual Attention, published in 2014, and has been successfully applied to a wide variety of problems from the Natural Language Processing (NLP) domain.

To understand the method, we will begin with a brief introduction to the NLP basics, including Recurrent Neural Networks (RNNs), word embeddings, and the seq2seq model. Then we'll discuss similarities between the NLP and RL problems and take a look at original ideas on how to improve NLP seq2seq ...

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Publisher Resources

ISBN: 9781788834247Supplemental Content