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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

Policy evaluation example

To better understand this, let's use an example. Imagine that we have a simple robot, navigating a grid environment (this example is also known as gridworld). We'll assume that:

  • The grid is size 4 x 4. It's very similar to the maze example we defined earlier, with the exception that it has no walls. The cells are numbered from 1 to 16, where cells 1 and 16 are terminal states.
  • The robot can navigate up, down, left, or right to any of the neighboring states. Actions that take the robot off the grid leave it in its current state (but the reward is still received).
  • The environment is deterministic that is, the transition probability of moving to the corresponding neighbor state when taking an action is always 1. ...
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Publisher Resources

ISBN: 9781789348460Supplemental Content