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Investigating Aesthetic Features to Model Human Preference in Evolutionary Art

机译:研究美学特征以模拟进化艺术中的人类偏好

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In this paper we investigate aesthetic features in learning aesthetic judgments in an evolutionary art system. We evolve genetic art with our evolutionary art system, BioEAS, by using genetic programming and an aesthetic learning model. The model is built by learning both phenotype and genotype features, which we extracted from internal evolutionary images and external real world paintings, which could lead to more interesting paths. By learning aesthetic judgment and applying the knowledge to evolve aesthetical images, the model helps user to automate the process of evolutionary process. Several independent experimental results show that our system is efficient to reduce user fatigue in evolving art.
机译:在本文中,我们研究了进化艺术系统中学习美学判断时的美学特征。我们通过使用遗传编程和审美学习模型,通过我们的进化艺术系统BioEAS来进化遗传艺术。该模型是通过学习表型和基因型特征而构建的,我们从内部进化图像和外部真实世界绘画中提取了这些特征,这可能会导致更有趣的路径。通过学习美学判断并应用知识来演化美学图像,该模型可帮助用户使演化过程自动化。几个独立的实验结果表明,在不断发展的艺术中,我们的系统可有效减少用户疲劳。

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