June 2018
Intermediate to advanced
318 pages
9h 24m
English
Now we will see how to build an agent to play any Atari game. You can get the complete code as a Jupyter notebook with the explanation here (https://github.com/sudharsan13296/Hands-On-Reinforcement-Learning-With-Python/blob/master/08.%20Atari%20Games%20with%20DQN/8.8%20Building%20an%20Agent%20to%20Play%20Atari%20Games.ipynb).
First, we import all the necessary libraries:
import numpy as npimport gymimport tensorflow as tffrom tensorflow.contrib.layers import flatten, conv2d, fully_connectedfrom collections import deque, Counterimport randomfrom datetime import datetime
We can use any of the Atari gaming environments given here: http://gym.openai.com/envs/#atari.
In this example, we use the Pac-Man game ...