Abstract
Since the pioneer observations of Alan Turing, emotional and aesthetical capabilities have been considered as one of the fundamental element of a genuinely intelligent machine. Among the proposed approaches, genetic algorithms try to combine intuitively a generative impulse with a critical capacity that steers the production towards a valuable goal. The approach here presented is based on Karl Sim’s approach in which a set of possible primitives is defined and it represent the genotype of the system. Such expressions are combined using genetic algorithms rules to obtain more complex functions that describe new images. At each step, images are evaluated by the user and this implicitly drives the evolution process. Results can be impressive, however a clear understanding of the determinants of our aesthetic evaluation is presently beyond reach.
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Bellini, R., Borghese, N.A. (2014). Genetic Art in Perspective. In: Bassis, S., Esposito, A., Morabito, F. (eds) Recent Advances of Neural Network Models and Applications. Smart Innovation, Systems and Technologies, vol 26. Springer, Cham. https://doi.org/10.1007/978-3-319-04129-2_9
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DOI: https://doi.org/10.1007/978-3-319-04129-2_9
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-04128-5
Online ISBN: 978-3-319-04129-2
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