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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

Q-learning

In reinforcement learning, we want the Q-function Q(s,a) to predict the best action for a state s in order to maximize the future reward. The Q-function is estimated using Q-learning, which involves the process of updating the Q-function using Bellman equations through a series of iterations as follows:

Here:

Q(s,a) = Q value for the current state s and action a pair

 = learning rate of convergence

 = discounting factor of future rewards ...

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Publisher Resources

ISBN: 9781788835725Supplemental Content