Evolving cellular automata for maze generation

Authors

Andrew Pech, Edith Cowan UniversityFollow
Philip Hingston, Edith Cowan University
Martin Masek, Edith Cowan UniversityFollow
Chiou P. Lam, Edith Cowan University

Document Type

Conference Proceeding

Publisher

Springer Verlag

School

School of Computer and Security Science

RAS ID

21016

Comments

Pech, A., Hingston, P., Masek, M., Lam, C.P. (2015). Evolving cellular automata for maze generation. In Proceedings of the First Australasian Conference on Artificial Life and Computational Intelligence (pp. 112-124) Newcastle, Australia: Newcastle University. Available here.

Abstract

This paper introduces a new approach to the procedural generation of maze-like game level layouts by evolving CA. The approach uses a GA to evolve CA rules which, when applied to a maze configuration, produce level layouts with desired maze-like properties. The advantages of this technique is that once a CA rule set has been evolved, it can quickly generate varying instances of maze-like level layouts with similar properties in real time.

DOI

10.1007/978-3-319-14803-8_9

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