基于有序-无序偏好谱的数学函数的蒙太奇最优构造

IF 0.3 Q4 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Journal of Mathematics and the Arts Pub Date : 2022-10-02 DOI:10.1080/17513472.2022.2139663
K. Smith‐Miles, Mario Andrés Muñoz
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引用次数: 0

摘要

我们以前生成了各种各样的数学函数,这些函数很难用于优化算法。以二维等高线图表示,每张图像都描绘了一条穿过复杂景观的“蓝色河流”。本文描述了构建这些图像的美学蒙太奇的挑战。一项调查显示,考虑到连接这些“蓝色河流”所创造的结构,人们的品味从有序到无序都有所不同。一件名为neg熵三联画(Negentropy tritych)的新作品被创造出来,通过手动交换随机排列的图像来描绘这种光谱,在人眼的引导下增强或破坏结构。一种优化算法使这一过程自动化,其结果是努力模仿所呈现和讨论的艺术视觉。尽管该算法探索了几个目标函数,但它所面临的挑战突显了捕捉人类决策者容易实现的目标的困难。因此,这些目标的机器学习是一个很有前途的未来方向。图形抽象
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Optimal construction of montages from mathematical functions on a spectrum of order–disorder preference
ABSTRACT We previously generated diverse mathematical functions that are difficult for optimization algorithms. Represented as 2D contour plots, each image depicts a ‘blue river’ running through an intricate landscape. This paper describes the challenge of constructing an aesthetic montage of these images. A survey revealed a spectrum of tastes, divergent in preference from order to disorder, considering the structure created by connecting these ‘blue rivers’. A new artwork, Negentropy Triptych, was created to depict this spectrum by manually swapping images from a random arrangement, guided by human eye to enhance or destroy the structure. An optimization algorithm automates the process, with the results of its efforts to emulate the artistic vision presented and discussed. The challenges faced by the algorithm, despite exploring several objective functions, highlight the difficulties of capturing the goals that a human decision-maker can easily achieve. Therefore, machine learning of these goals is a promising future direction. GRAPHICAL ABSTRACT
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来源期刊
Journal of Mathematics and the Arts
Journal of Mathematics and the Arts MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
CiteScore
0.50
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0.00%
发文量
19
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