Skip to Content
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

Reinforcement learning in RTS gaming

Here we will discuss how reinforcement learning algorithms can be implemented to solve the real-time strategy gaming problem. Let's recall the basic components of reinforcement learning again, they are are follows:

  • States S
  • Actions A
  • Rewards R
  • Transition model (if on-policy, not required for off-policy learning)

If these components are perceived and processed by the sensors present on the learning agent while receiving signals from the given gaming environment, then a reinforcement learning algorithm can be successfully applied. The signals perceived by the sensors can be processed to form the current environment state, predict the action as per the state information, and receive feedback, that is, reward ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Deep Learning with TensorFlow - Second Edition

Deep Learning with TensorFlow - Second Edition

Giancarlo Zaccone, Vihan Jain, Md. Rezaul Karim, Motaz Saad
Deep Learning with TensorFlow 2 and Keras - Second Edition

Deep Learning with TensorFlow 2 and Keras - Second Edition

Antonio Gulli, Dr. Amita Kapoor, Sujit Pal

Publisher Resources

ISBN: 9781788835725Supplemental Content