This paper presents a novel approach to procedural generation of urban maps for First Person Shooter (FPS) games. A multi-agent evolutionary system is employed to place streets, buildings and other items inside the Unity3D game engine, resulting in playable video game levels. A computational agent is trained using machine learning techniques to capture the intent of the game designer as part of the multi-agent system, and to enable a semi-automated aesthetic selection for the underlying genetic algorithm.
@article{arxiv.1604.05791,
title = {Procedural urban environments for FPS games},
author = {Jan Kruse and Ricardo Sosa and Andy M. Connor},
journal= {arXiv preprint arXiv:1604.05791},
year = {2016}
}