Deep Q Learning and Self Play Beat Humans at Super Auto Pets

Super Auto Pets is a popular online zero-sum extensive form game that emphasizes taking discrete actions to ensemble a cohesive team of pets to win.

To better understand various principle related to Deep Q Learning, I designed and built a AI modet to complete agains humas in the game. My work:

• Broke the challenge into sub-components to minimize cost of computation.
• Reduced a large action space into one dramatically smaller, but maintaining all the actions available in the game.
• Created a domain-specific search algorithm that increased performance from 3.6 to 5.5 points per game.
• Oversaw optimization. Tested how hyperparameters of the model affected AI performance.

I was successfully able to develop an AI that outperforms human players in diverse game scenarios.

This video explains the project in detail.