Hands-On Reinforcement Learning with Python

Building an agent to play Atari games

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 ...