Eugene: a generic interactive genetic algorithm controller

This paper outlines the development of an open source generic hardware-based interactive Genetic Algorithm controller (Eugene) and explores contexts in which it may be deployed. The system was first applied to the generation of synthetic sound using MIDI and a simple analogue synthesiser with 27 continuous controller values. It was then applied in the area of image evaluation using an image enhancer program with 7 continuous controller values. The system was evaluated by experimental observation of users attempting various tasks with different success criteria. This led to the identification of issues, some of which were specific to, and others divorced from the application domain. These are discussed together with areas for improvement

Multi-agent evolutionary systems for the generation of complex virtual worlds

Modern films, games and virtual reality applications are dependent on convincing computer graphics. Highly complex models are a requirement for the successful delivery of many scenes and environments. While workflows such as rendering, compositing and animation have been streamlined to accommodate increasing demands, modelling complex models is still a laborious task. This paper introduces the computational benefits of an Interactive Genetic Algorithm (IGA) to computer graphics modelling while compensating the effects of user fatigue, a common issue with Interactive Evolutionary Computation. An intelligent agent is used in conjunction with an IGA that offers the potential to reduce the effects of user fatigue by learning from the choices made by the human designer and directing the search accordingly. This workflow accelerates the layout and distribution of basic elements to form complex models. It captures the designer's intent through interaction, and encourages playful discovery

Biomorpher: interactive evolution for parametric design

Combining graph-based parametric design with metaheuristic solvers has to date focussed solely on performance based criteria and solving clearly defined objectives. In this paper, we outline a new method for combining a parametric modelling environment with an interactive Cluster-Orientated Genetic Algorithm (COGA). In addition to performance criteria, evolutionary design exploration can be guided through choice alone, with user motivation that cannot be easily defined. As well as numeric parameters forming a genotype, the evolution of whole parametric definitions is discussed through the use of genetic programming. Visualisation techniques that enable mixing small populations for interactive evolution with large populations for performance-based optimisation are discussed, with examples from both academia and industry showing a wide range of applications

The development and application of an optimization tool in industrial design

AbstractDesigners are identified, in industry 4.0, as the professional figures that have to design well performing new object. In order to do this, it is necessary to take into account a series of properties called design objectives. Often the structural problem of new design is underestimated or even not considered. This can be a real problem because this objective is in competitive and in contrast with other design objectives. So, this can bring to substantial change in a design in the final phase and sometimes to the complete change. In this paper is presented an optimization workflow that adopt a Multi Objective Optimization engine so called "Octopus" and Karamba3D, that is a Finite Elements (FE) plug-in, typically used in structural simulations, these extensions run in a software: Grassopper3D, that is a parametric design tool. The workflow allows designers to explore a large range of solutions and at the same time permits to filter and sort the optimized models in order to analyze the tradeoff of the resultant solution space, both qualitatively and quantitatively. In such way designers can obtain easily a lot of information of the generate design and identify potential solution for immediate use or for further optimization. In this paper is analyzed a design problem of an ergonomic chair in order to provide the efficiency of the workflow. The design criteria and the structural problem for this type of design object are identified as the main optimization objectives in order to iteratively improve the design solutions

30th Anniversary of Applied Intelligence: A combination of bibliometrics and thematic analysis using SciMAT

Applied Intelligence is one of the most important international scientific journals in the field of artificial intelligence. From 1991, Applied Intelligence has been oriented to support research advances in new and innovative intelligent systems, methodologies, and their applications in solving real-life complex problems. In this way, Applied Intelligence hosts more than 2,400 publications and achieves around 31,800 citations. Moreover, Applied Intelligence is recognized by the industrial, academic, and scientific communities as a source of the latest innovative and advanced solutions in intelligent manufacturing, privacy-preserving systems, risk analysis, knowledge-based management, modern techniques to improve healthcare systems, methods to assist government, and solving industrial problems that are too complex to be solved through conventional approaches. Bearing in mind that Applied Intelligence celebrates its 30th anniversary in 2021, it is appropriate to analyze its bibliometric performance, conceptual structure, and thematic evolution. To do that, this paper conducts a bibliometric performance and conceptual structure analysis of Applied Intelligence from 1991 to 2020 using SciMAT. Firstly, the performance of the journal is analyzed according to the data retrieved from Scopus, putting the focus on the productivity of the authors, citations, countries, organizations, funding agencies, and most relevant publications. Finally, the conceptual structure of the journal is analyzed with the bibliometric software tool SciMAT, identifying the main thematic areas that have been the object of research and their composition, relationship, and evolution during the period analyzed

Texture Based Image retrieval using Human interactive Genetic Algorithm

Content-based image retrieval has been keenly calculated in numerous fields. This provides more active management and retrieval of images than the keyword-based method. So the content based image retrieval has become one of the liveliest researches in the past few years. As earlier, we were using the text-based approach where it initiate very boring and hard task for solving the purpose of image retrieval. But the CBIR is the method where there are several methodologies are available and the task of image retrieval becomes well easier. In this, there are specific effective methods for CBIR are discussed and the relative study is made. However most of the proposed methods emphasize on finding the best representation for diverse image features. Here, the user-oriented mechanism for CBIR method based on an interactivegenetic algorithm (IGA) is proposed. Color attributes likethe mean value, the standard deviation, and the image bitmap of a color image are used as the features for retrieval. In addition, the entropy based on the gray level co-occurrence matrix and the edge histograms of an image are too considered as the texture features

Fashion sketch design by interactive genetic algorithms

Author name used in this publication: Mok, P.Y.Author name used in this publication: Kwok, Y.L.Refereed conference paper2012-2013 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Fashion sketch design by interactive genetic algorithms

Computer aided design is vitally important for the modern industry, particularly for the creative industry. Fashion industry faced intensive challenges to shorten the product development process. In this paper, a methodology is proposed for sketch design based on interactive genetic algorithms. The sketch design system consists of a sketch design model, a database and a multi-stage sketch design engine. First, a sketch design model is developed based on the knowledge of fashion design to describe fashion product characteristics by using parameters. Second, a database is built based on the proposed sketch design model to define general style elements. Third, a multi-stage sketch design engine is used to construct the design. Moreover, an interactive genetic algorithm (IGA) is used to accelerate the sketch design process. The experimental results have demonstrated that the proposed method is effective in helping laypersons achieve satisfied fashion design sketches.Institute of Textiles and ClothingAuthor name used in this publication: Mok, P.Y.Author name used in this publication: Kwok, Y.L.Refereed conference pape