Evolutionary Image Transition and Painting Using Random Walks

Superior Exploration-Exploitation Balance with Quantum-Inspired Hadamard Walks

This paper extends the analogies employed in the development of quantum-inspired evolutionary algorithms by proposing quantum-inspired Hadamard walks, called QHW. A novel quantum-inspired evolutionary algorithm, called HQEA, for solving combinatorial optimization problems, is also proposed. The novelty of HQEA lies in it's incorporation of QHW Remote Search and QHW Local Search - the quantum equivalents of classical mutation and local search, that this paper defines. The intuitive reasoning behind this approach, and the exploration-exploitation balance thus occurring is explained. From the res…

Modern Evolution Strategies for Creativity: Fitting Concrete Images and Abstract Concepts

Evolutionary algorithms have been used in the digital art scene since the 1970s. A popular application of genetic algorithms is to optimize the procedural placement of vector graphic primitives to resemble a given painting. In recent years, deep learning-based approaches have also been proposed to generate procedural drawings, which can be optimized using gradient descent. In this work, we revisit the use of evolutionary algorithms for computational creativity. We find that modern evolution strategies (ES) algorithms, when tasked with the placement of shapes, offer large improvements in both q…

Evolutionary Image Transition Based on Theoretical Insights of Random Processes

Evolutionary algorithms have been widely studied from a theoretical perspective. In particular, the area of runtime analysis has contributed significantly to a theoretical understanding and provided insights into the working behaviour of these algorithms. We study how these insights into evolutionary processes can be used for evolutionary art. We introduce the notion of evolutionary image transition which transfers a given starting image into a target image through an evolutionary process. Combining standard mutation effects known from the optimization of the classical benchmark function OneMa…

Evolutionary Image Composition Using Feature Covariance Matrices

Evolutionary algorithms have recently been used to create a wide range of artistic work. In this paper, we propose a new approach for the composition of new images from existing ones, that retain some salient features of the original images. We introduce evolutionary algorithms that create new images based on a fitness function that incorporates feature covariance matrices associated with different parts of the images. This approach is very flexible in that it can work with a wide range of features and enables targeting specific regions in the images. For the creation of the new images, we pro…

网格中的进化觅食：有限、可耗竭景观中涌现的间歇性搜索动态

Evolutionary foraging in grids: Intermittent search dynamics emerge in finite, depletable landscapes

通过进化模拟研究有限可耗竭景观中的搜索策略，发现进化搜索更符合间歇性动态而非Lévy行走，为资源受限探索提供启示。

基于贝塞尔曲线的随机游走全局优化

Random Walk on Bézier Curves for Global Optimization

提出贝塞尔游走进化算法(BWE)，利用贝塞尔曲线和距离感知随机游走平衡探索与开发，在CEC2017/2022基准测试和工程问题中优于L-SHADE和CMA-ES等先进优化器。