Document Design with Interactive Evolution (original) (raw)
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Exploring Automatic Fitness Evaluation for Evolutionary Typesetting
Creativity and Cognition, 2021
The recent popularity of creative coding tools and Computational Creativity approaches are promoting a paradigm shift in the creation, development and production of Graphic Design artefacts. In this work, we present an evolutionary system for the automatic typesetting of typographic posters. This system is inspired by the letterpress typesetting process of the print houses in the earlier 19th century and employs lexicon-based approaches to recognise the semantic meaning of the posters' content. During the evolutionary process, poster designs are automatically created and evaluated according to three objectives: legibility, aesthetics, and semantics. The system allows the users to express their preferences by specifying the intended visual features for the output designs, selecting the preferable fitness assignment strategy, and controlling different aspects of the evaluation strategy. We implemented three automatic strategies to evaluate the fitness of the posters: a multi-criteria hardwired fitness function, a multi-objective optimisation approach, and a hybrid strategy that combines features from the previous two strategies. The experimental results demonstrate the ability of the presented system to generate typographic posters, from scratch, and show the impact of the different evaluation strategies on the evolved poster designs. Overall, this research reveals how Evolutionary Computation approaches can be employed to develop novel co-creative typesetting tools and enable the automatic creation of customised typographic designs. CCS CONCEPTS • Computing methodologies → Information extraction; • Theory of computation → Evolutionary algorithms; • Applied computing → Publishing; Arts and humanities.
Interactive Genetic Algorithms for User Interface Design
2007 IEEE Congress on Evolutionary Computation, 2007
We attack the problem of user fatigue in using an interactive genetic algorithm to evolve user interfaces in the XUL interface definition language. The interactive genetic algorithm combines computable user interface design metrics with subjective user input to guide evolution. Individuals in our population represent interface specifications and we compute an individual's fitness from a weighted combination of user input
Optimizing Website Design Through the Application of an Interactive Genetic Algorithm
The goal of this project was to determine the efficacy and practicality of "optimizing" the design of a webpage through the application of an interactive genetic algorithm. Software was created to display a "population" of mutable designs, collect user feedback as a measure of fitness, and apply genetic operations in an ongoing evolutionary process. By tracking the prevalence of design parameters over multiple generations and evaluating their associated "fitness" values, it was possible to judge the overall performance of the algorithm when applied to this unique problem space. 4
User Interface Optimization using Genetic Programming with an Application to Landing Pages
The design of user interfaces (UIs), such as World Wide Web pages, usually consists in a human designer mapping one particular problem (e.g., the demands of a customer) to one particular solution (i.e., the UI). In this article, a technology based on Genetic Programming is proposed to automate critical parts of the design process. In this approach, designers are supposed to define basic content elements and ways to combine them, which are then automatically composed and tested with real users by a genetic algorithm in order to find optimized compositions. Such a strategy enables the exploration of large design state-spaces in a systematic manner, hence going beyond traditional A/B testing approaches. In relation to similar techniques also based on genetic algorithms, this system has the advantage of being more general, providing the basis of an overall programmatic UI design workflow, and of calculating the fitness of solutions incrementally. To illustrate and evaluate the approach, an experiment based on the optimization of landing pages is provided. The empirical result obtained, though preliminary, is statistically significant and corroborates the hypothesis that the technique works.
2003
The Human Based Genetic Algorithm is an extension of the field of Interactive Evolutionary Computation where, in addition to fitness and selection, the user performs all the other genetic operators. The definition of operators is left intentionally loose to stimulate the user's creativity in the evolutionary process. This framework naturally extends to cooperative environments and has great potentiality in fields like marketing, industrial design, creative writing. This paper presents a full design, web-oriented implementation ...
Survey on Interactive Genetic Algorithm for Web Page Design
— It is said that ability to create interesting and new things can be improved through the use of Interactive Genetic Algorithm (IGAs). The objective of this project was to decide the adequacy and practicality of optimizing the outline of a webpage through the utilization of an interactive genetic algorithm. Programming was made to show a population of mutable designs, gather client feedback as a measure of fitness, and apply genetic operations in a continuous evolutionary process. The review proposes utilization of genetic algorithm driven Cascading Style Sheets (CSS) to help the procedure of website optimization. This strategy will draw in visitors to remotely alter and upgrade the style (type, layout and color) of site to fit their stylish and practical portrayal of well-received design. Survey in this paper with the issue of automatically creating the style and the design of site pages and sites in a genuine application where many sites are considered. One of the fundamental trouble is to consider the user inclinations which are significant in sites plan.
Interactive design of web sites with a genetic algorithm
2002
We deal in this paper with the problem of automatically generating the style and the layout of web pages and web sites in a real world application where many web sites are considered. One of the main difficulty is to take into account the user preferences which are crucial in web sites design. We propose the use of an interactive genetic algorithm which generates solutions (styles, layouts) and which lets the user select the solutions that he favors based on their graphical representation. Two encodings have been defined for this problem, one linear and fixed length encoding for representing the style, and one variable length encoding based on HTML tables syntax for the layout. We present the results obtained by our method and the analysis of users behavior.
2010
Evolution is a substrate-neutral algorithm that creates design, working with three conditions: replication, variation, and selection. The memetic theory posits that elements of human culture are subject to the algorithm of evolution as the memes that code for them are replicated, varied and selected. Within this paradigm, human creativity can be explained as an evolutionary process within the brain where random variations are unconsciously selected in milliseconds. Digital evolutionary algorithms are being used today to create design and to solve optimization problems. Graphic design, due to its functional nature, has the potential to be a very fruitful area of research and application for evolutionary algorithms. Gráphagos uses genetic algorithms to randomly mutate and replicate the designs according to a human user's evaluation. The program is primarily designed as a model for the creative process occurring in the system that consists of the graphic designer and the sketching medium. Gráphagos demonstrates how graphic design can emerge when random mutations are selected and accumulated. The program additionally offers a new tool for making graphic design. It may also be used as a tool for gathering data about our visual preferences.
EvoDesigner: Evolving Poster Layouts
Entropy
Frequently, one of the goals of Graphic Design (gd) is discovering disruptive visual solutions that stand out and attract people’s attention. However, due to the increasing democratisation of gd, graphic designers tend to adopt design trends, leading to designs that many times lack innovative and catchy features. EvoDesigner is an evolutionary extension for Adobe InDesign that aims to aid gd processes by automatically evolving layout and style variations of given InDesign pages. The generated pages might be previously created and post-edited by designers, promoting co-creation. As an extension of the study EvoDesigner: Towards Aiding Creativity in Graphic Design, this article begins with a general introduction of EvoDesigner. Then, we review previous experiments on evolving pages towards the page balance of existing target posters. Furthermore, we present new experiments exploring the benefits of using grid systems to position and scale page items along with a user survey made to ga...
Template Personalization and Evolutionary Algorithms
Due to the rapid and hectic growth of the Web, its access and design have become a challenge. Web personalization has occurred to solve this problem. However, such personalization mostly deals with the visitors rather than other types of website users. Alternatively, Web Content Management System (WCMS) has occurred to facilitate website development, including its design. Nevertheless, designing of such websites are only customized. Thus, website developers need to further choose and refine the appropriate design. Such process needs a lot of effort and wastes a lot of time. Consequently, this paper will present a new approach that extracts and personalize templates by combining web personalization and template extraction in order to automatically extract templates and, thereby, simplify WCMS and increase its scalability. In specific, to accomplish this approach a new technique is used, which mixes Genetic Algorithm, Ant Colony Clustering, and Cluster Tree Matching. This approach is tested with an experiment, which proved its quality, in regard of speed, precision, and accuracy.