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Hands-On Reinforcement Learning with Python
book

Hands-On Reinforcement Learning with Python

by Sudharsan Ravichandiran
June 2018
Intermediate to advanced content levelIntermediate to advanced
318 pages
9h 24m
English
Packt Publishing
Content preview from Hands-On Reinforcement Learning with Python

Q learning

We will now look into the very popular off-policy TD control algorithm called Q learning. Q learning is a very simple and widely used TD algorithm. In control algorithms, we don't care about state value; here, in Q learning, our concern is the state-action value pair—the effect of performing an action A in the state S.

We will update the Q value based on the following equation:

The preceding equation is similar to the TD prediction update rule with a little difference. We will see this in detail step by step. The steps involved in Q learning are as follows:

  1. First, we initialize the Q function to some arbitrary values
  2. We take an ...
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Publisher Resources

ISBN: 9781788836524Supplemental Content