Using reinforcement learning to design an AI assistantfor a satisfying co-op experience

TL;DR

This paper presents a reinforcement learning-based AI assistant for Space Invaders, aiming to enhance cooperative gameplay experience by validating that AI can provide satisfying co-op interactions.

Contribution

It introduces a reinforcement learning approach to design an AI assistant for a game, focusing on improving co-op satisfaction, which is a novel application in this context.

Findings

AI assistant improves co-op experience in Space Invaders

Reinforcement learning effectively models cooperative behavior

Validation shows AI can satisfy co-op criteria

Abstract

In this project, we designed an intelligent assistant player for the single-player game Space Invaders with the aim to provide a satisfying co-op experience. The agent behaviour was designed using reinforcement learning techniques and evaluated based on several criteria. We validate the hypothesis that an AI-driven computer player can provide a satisfying co-op experience.