The Development of a Tool for the Preference Assessment of the Visual Aesthetics of an Object Using Interactive Genetic Algorithms

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Jarod Kelly, Panos Papalambros, Gregory Wakefield: The Development of a Tool for the Preference Assessment of the Visual Aesthetics of an Object Using Interactive Genetic Algorithms. In: Generative Art 2006.



Interactive evolutionary algorithms (IEAs) have been proposed as creativity aids to designers with regard to visual aesthetics. Algorithms have been developed to expose the designer to new designs and thus spark imagination and improve creativity. The present paper focuses on utilizing interactive genetic algorithms (IGAs), a subset of IEAs, to understand the visual aesthetic preferences of the user. A design concept is input to the IGA program, which utilizes information gathered from the user to create new designs. The program collects preferences from the user in a simulated “marketplace” setting. These preferences inform the evolution of the object’s design over several generations until a final “ideal design" is reached. This "ideal design" is considered to be the most preferred visual aesthetics for that user within the specified design space. Monte Carlo simulations indicate that the IGA can locate such ideal designs with high probability. Human studies suggest that users can express their visual aesthetic preferences for a design with the IGA. This is important because few scientific tools exist for acquiring such preference information reliably and efficiently. Design decisions regarding visual aesthetics of a product often interact with its technical attributes. The proposed preference assessment tool aims to facilitate such interactions in a more analytical manner than is currently available.

Extended Abstract


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