Evolutionary Art typically involves a tradeoff between the size and flexibility of genotype space and its mapping to an expressive phenotype space. Ideally we would like a genotypic representation that is terse but expressive, that is, we want to maximise the useful variations the genotype is capable of expressing in phenotype space. Terseness is necessary to minimise the size of the overall search space, and expressiveness can be loosely interpreted as phenotypes that are useful (of high fitness) and diverse (in feature space). In this paper I describe a system that attempts to maximise this ratio between terseness and expressiveness. The system uses a binary string up to any maximum length as the genotype. The genotype string is interpreted as building instructions for a graph, similar to the cellular programming techniques used to evolve artificial neural networks. The graph is then interpreted as a form-building automaton that can construct animated 3-dimensional forms of arbitrary complexity. In the test case the requirement for expressiveness is that the resultant form must have recognisable biomorphic properties and that every possible genotype must fulfil this condition. After much experimentation, a number of constraints in the mapping technique were devised to satisfy this condition. These include a special set of geometric building operators that take into account morphological properties of the generated form. These methods were used in the evolutionary artwork “Codeform”, developed for the Ars Electronica museum. The work generated evolved virtual creatures based on genomes acquired from the QR codes on museum visitor’s entry tickets.


Evolutionary Art Aesthetics Artificial Life genotype-phenotype mapping 


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© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Jon McCormack
    • 1
  1. 1.Centre for Electronic Media ArtMonash UniversityCaulfield EastAustralia

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