Date of Award

6-10-2025

Document Type

Thesis

Publisher

Santa Clara : Santa Clara University, 2025

Department

Computer Science and Engineering

First Advisor

Michael Schimpf

Abstract

This project explores the integration of artificial intelligence into retro-style arcade titles to enhance the gameplay, while still preserving the nostalgic aesthetic and overall mechanics of the titles. By using Pygame to explore clones of the existing video game titles, we modified the existing games to develop AI into the games using various AI algorithms. The system introduces adaptive enemy behavior that responds to the players actions and also introduces an additional player to some games that will play alongside the player as well. This helps to create a more engaging and unpredictable gaming experience. The AI logic is implemented in python within the player class itself for the games with additional players.

The primary goal of the project is to explore various AI algorithms to maintain an understanding of how AI can be implemented into various arcade titles effectively. By doing this it allows us to select the best algorithms for this project that can help enhance a player’s experience, instead of frustrating the player. The result of our project demonstrates the potential for AI to bring new life to these older video games, which allows us as the developers to discover how we can effectively and creatively reinterpret the familiar gameplay.

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