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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

Evolution strategies

The subset of black-box optimization methods is called evolution strategies (ES) and has been inspired by the evolution process, where the most successful individuals have the highest influence on the overall direction of the search. There are many different methods that fall into this class and in this chapter, we'll consider the approach taken by OpenAI researchers Tim Salimans, Jonathan Ho, and others in their paper, Evolution Strategies as a Scalable Alternative to Reinforcement Learning [1], published in March 2017.

The underlying idea of ES methods is simple: on every iteration, we perform random perturbation of our current policy parameters and evaluate the resulting policy fitness function. Then we adjust the policy ...

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Publisher Resources

ISBN: 9781788834247