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Python Deep Learning - Second Edition
book

Python Deep Learning - Second Edition

by Ivan Vasilev, Daniel Slater, Gianmario Spacagna, Peter Roelants, Valentino Zocca
January 2019
Intermediate to advanced content levelIntermediate to advanced
386 pages
11h 13m
English
Packt Publishing
Content preview from Python Deep Learning - Second Edition

Actor-Critic with advantage

One of the drawbacks of AC (and policy-based methods in general) is the high variance of . To understand this, note that we update the policy parameters θ by observing the rewards of multiple episodes. Let's focus on a single episode. The agent starts at initial state s and then takes a series of actions following the policy . These actions lead to new states and their corresponding rewards. When the terminal state is reached, the episode has accumulated some total reward. We'll use these rewards to update the policy ...

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Publisher Resources

ISBN: 9781789348460Supplemental Content