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Hands-On Reinforcement Learning for Games
book

Hands-On Reinforcement Learning for Games

by Micheal Lanham
January 2020
Intermediate to advanced
432 pages
10h 18m
English
Packt Publishing
Content preview from Hands-On Reinforcement Learning for Games

Exercises

Completing the exercises in this section is entirely optional, but, hopefully, you can start to appreciate that we, as reinforcement learners ourselves, learn best by doing. Do your best and attempt to complete at least 2-3 exercises from the following:

  1. Consider other problems you could use DP with? How would you break the problem up into subproblems and calculate each subproblem?
  2. Code up another example that compares a problem programmed linearly versus dynamically. Use the example from Exercise 1. The code examples, Chapter_2_2.py and Chapter_2_3.py, are good examples of side-by-side comparisons.
  3. Look through the OpenAI documentation and explore other RL environments.
  4. Create, render, and explore other RL environments from Gym ...
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Publisher Resources

ISBN: 9781839214936