Evolving continuous cellular automata for aesthetic objectives

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@Article{Heaton:2019:GPEM,

• author = "Jeff Heaton",
• title = "Evolving continuous cellular automata for aesthetic objectives",
• journal = "Genetic Programming and Evolvable Machines",
• year = "2019",
• volume = "20",
• number = "1",
• pages = "93--125",
• month = mar,
• keywords = "genetic algorithms, genetic programming, Cellular automata, Generative art, Multi-objective optimization",
• ISSN = "1389-2576",
• DOI = "doi:10.1007/s10710-018-9336-1",
• size = "33 pages",
• abstract = "We present MergeLife, a genetic algorithm (GA) capable of evolving continuous cellular automata (CA) that generate full colour dynamic animations according to aesthetic user specifications. A simple 16-byte update rule is introduced that is evolved through an objective function that requires only initial human aesthetic guidelines. This update rule provides a fixed-length genome that can be successfully optimized by a GA. Also introduced are several novel fitness measures that when given human selected aesthetic guidelines encourage the evolution of complex animations that often include spaceships, oscillators, still life, and other complex emergent behaviour. The results of this research are several complex and long running update rules and the objective function parameters that produced them. Several update rules produced from this paper exhibit complex emergent behaviour through patterns, such as spaceships, guns, oscillators, and Universal Turing Machines. Because the true animated behavior of these CA cannot be observed from static images, we also present an on-line JavaScript viewer that is capable of animating any MergeLife 16-byte update rule.",

}

Genetic Programming entries for Jeff Heaton

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