Evolutionary computation uses computational models of evolutionary processes as key elements in the design and implementation of computerbased problem solving systems. In this paper we provide an overview of evolutionary computation, and describe several evolutionary algorithms that are currently of interest. Important similarities and differences are noted, which lead to a discussion of import...

The use of Evolutionary Computation approaches to create images has reached a great popularity, leading to the appearance of a new art form – Evolutionary Art – and to the proliferation of Evolutionary Art Tools. In this paper we present and make an assessment of one of these tools: NEvAr. We also systematise and describe the work methodology currently used to generate images. When working with...

We present an extensive study into aesthetic measures in unsupervised evolutionary art (EvoArt). In contrast to several mainstream EvoArt approaches we evolve images without human interaction, using one or more aesthetic measures as fitness functions. We perform a series of systematic experiments, comparing 7 di↵erent aesthetic measures through subjective criteria (‘style’) as well as by quanti...

In recent years, the widespread penetration of the Internet has led to the use of diverse expressions over the Web. Among them, many appear to have strong video elements. However, few expressions are based on human beings, with whom we are most familiar. This is deemed to be attributable to the fact that it is not easy to generate human movements. This is attributable to the fact that the creat...

When multiple algorithms are applied to multiple benchmarks as it is common in evolutionary computation, a typical issue rises, how can we rank the algorithms? It is a common practice in evolutionary computation to execute the algorithms several times and then the mean value and the standard deviation are calculated. In order to compare the algorithms performance it is very common to use statis...