Evolving cellular automata for maze generation
School of Computer and Security Science
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.