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Evolving Cellular Automata for Maze Generation

  • Andrew Pech
  • Philip Hingston
  • Martin Masek
  • Chiou Peng Lam
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8955)

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.

Keywords

procedural content evolutionary algorithm cellular automaton 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Andrew Pech
    • 1
  • Philip Hingston
    • 1
  • Martin Masek
    • 1
  • Chiou Peng Lam
    • 1
  1. 1.School of Computer and Security ScienceEdith Cowan UniversityAustralia

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