Playing Pacman Using Deep Reinforcement Learning

Reinforcement learning refers to a paradigm where an agent learns from environment feedback by virtue of receiving observations and rewards in return for actions it takes. The following diagram captures the feedback-based learning loop of reinforcement learning:

Although mostly applied to learn how to play games, reinforcement learning has also been successfully applied in digital advertising, stock trading, self-driving cars, and industrial robots.

In this chapter, we will use reinforcement learning to create a PacMan game and learn about reinforcement learning in the process. We will cover the following topics: 

• Reinforcement learning
• Reinforcement learning  versus supervised and unsupervised learning
• Components of reinforcement learning
• OpenAI Gym
• A PacMan game in OpenAI Gym
• DQN for deep reinforcement...