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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
546 pages
13h 30m
English
Packt Publishing
Content preview from Deep Reinforcement Learning Hands-On

Summary

My congratulations, you've made another step towards understanding modern, state-of-the-art RL methods! We learned about some very important concepts that are widely used in deep RL: the value of state, the value of actions, and the Bellman equation in various forms. We saw the value iteration method, which is a very important building block in the area of Q-learning. Finally, we got to know how value iteration can improve our FrozenLake solution.

In the next chapter, we'll learn about deep Q-networks, which started the deep RL revolution in 2013, by beating humans on lots of Atari 2600 games.

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Publisher Resources

ISBN: 9781788834247