Multi-level evolution of shooter levels

13Citations
Citations of this article
17Readers
Mendeley users who have this article in their library.

Abstract

This paper introduces a search-based generative process for first person shooter levels. Genetic algorithms evolve the level's architecture and the placement of powerups and player spawnpoints, generating levels with one floor or two floors. The evaluation of generated levels combines metrics collected from simulations of artificial agents competing in the level and theory-based heuristics targeting general level design patterns. Both simulation-based and theory-driven evaluations target player balance and exploration, while resulting levels emergently exhibit several popular design patters of shooter levels.

Cite

CITATION STYLE

APA

Cachia, W., Liapis, A., & Yannakakis, G. N. (2015). Multi-level evolution of shooter levels. In Proceedings of the 11th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2015 (Vol. 2015-November, pp. 115–121). The AAAI Press. https://doi.org/10.1609/aiide.v11i1.12799

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free