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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

Summary

We saw that using parallel learners to update a shared model produced a great improvement on the learning process. We learned about the reason behind the use of asynchronous methods in deep learning and their different variants, including asynchronous one-step Q-learning, asynchronous one-step SARSA, asynchronous n-step Q-learning, and asynchronous advantage actor-critic. We also learned to implement the A3C algorithm, where we made an agent learn to play the games Breakout and Doom.

In the coming chapters, we will focus on different domains and how deep reinforcement learning is being, and can be, applied.

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Publisher Resources

ISBN: 9781788835725Supplemental Content