Automatic Structure Generation using Genetic Programming and Fractal Geometry

Three dimensional model design is a well-known and studied field, with numerous real-world applications. However, the manual construction of these models can often be time-consuming to the average user, despite the advantages o ffered through computational advances. This thesis presents an approach to the design of 3D structures using evolutionary computation and L-systems, which involves the automated production of such designs using a strict set of fitness functions. These functions focus on the geometric properties of the models produced, as well as their quantifiable aesthetic value - a topic which has not been widely investigated with respect to 3D models. New extensions to existing aesthetic measures are discussed and implemented in the presented system in order to produce designs which are visually pleasing. The system itself facilitates the construction of models requiring minimal user initialization and no user-based feedback throughout the evolutionary cycle. The genetic programming evolved models are shown to satisfy multiple criteria, conveying a relationship between their assigned aesthetic value and their perceived aesthetic value. Exploration into the applicability and e ffectiveness of a multi-objective approach to the problem is also presented, with a focus on both performance and visual results. Although subjective, these results o er insight into future applications and study in the fi eld of computational aesthetics and automated structure design

Worldwide Infrastructure for Neuroevolution: A Modular Library to Turn Any Evolutionary Domain into an Online Interactive Platform

Across many scientific disciplines, there has emerged an open opportunity to utilize the scale and reach of the Internet to collect scientific contributions from scientists and non-scientists alike. This process, called citizen science, has already shown great promise in the fields of biology and astronomy. Within the fields of artificial life (ALife) and evolutionary computation (EC) experiments in collaborative interactive evolution (CIE) have demonstrated the ability to collect thousands of experimental contributions from hundreds of users across the glob. However, such collaborative evolutionary systems can take nearly a year to build with a small team of researchers. This dissertation introduces a new developer framework enabling researchers to easily build fully persistent online collaborative experiments around almost any evolutionary domain, thereby reducing the time to create such systems to weeks for a single researcher. To add collaborative functionality to any potential domain, this framework, called Worldwide Infrastructure for Neuroevolution (WIN), exploits an important unifying principle among all evolutionary algorithms: regardless of the overall methods and parameters of the evolutionary experiment, every individual created has an explicit parent-child relationship, wherein one individual is considered the direct descendant of another. This principle alone is enough to capture and preserve the relationships and results for a wide variety of evolutionary experiments, while allowing multiple human users to meaningfully contribute. The WIN framework is first validated through two experimental domains, image evolution and a new two-dimensional virtual creature domain, Indirectly Encoded SodaRace (IESoR), that is shown to produce a visually diverse variety of ambulatory creatures. Finally, an Android application built with WIN, filters, allows users to interactively evolve custom image effects to apply to personalized photographs, thereby introducing the first CIE application available for any mobile device. Together, these collaborative experiments and new mobile application establish a comprehensive new platform for evolutionary computation that can change how researchers design and conduct citizen science online

Semiotic Shortcuts. The Graphical Abstract Strategies of Engineering Students

  Graphical abstracts are representative of the rising promotionalism, interdisciplinarity and changing researcher roles in the current dissemination of science and technology. Their design, moreover, amalgamates a number of transdisciplinary skills much valued in higher education, such as critical and lateral thinking, and cultural and audience awareness. In this study, I investigate a corpus of 56 samples of graphical abstracts devised by my aeronautical engineering students, to find out the ‘semiotic shortcuts’ or encoding strategies they deploy, without any previous instruction, to pack information and translate the verbal into the visual. Findings suggest that their ‘natural digital-native graphicacy’ is conservative as to the medium, format and type of representation, but versatile regarding particular meanings, although not always unambiguous or register-appropriate. Consequently, I claim the convenience of including graphicacy/visual literacy and some basic training on graphical abstract design in the English for Specific Purposes and the disciplinary English-medium curriculum.  

Adapting models of visual aesthetics for personalized content creation

This paper introduces a search-based approach to personalized content generation with respect to visual aesthetics. The approach is based on a two-step adaptation procedure where (1) the evaluation function that characterizes the content is adjusted to match the visual aesthetics of users and (2) the content itself is optimized based on the personalized evaluation function. To test the efficacy of the approach we design fitness functions based on universal properties of visual perception, inspired by psychological and neurobiological research. Using these visual properties we generate aesthetically pleasing 2D game spaceships via neuroevolutionary constrained optimization and evaluate the impact of the designed visual properties on the generated spaceships. The offline generated spaceships are used as the initial population of an interactive evolution experiment in which players are asked to choose spaceships according to their visual taste: the impact of the various visual properties is adjusted based on player preferences and new content is generated online based on the updated computational model of visual aesthetics of the player. Results are presented which show the potential of the approach in generating content which is based on subjective criteria of visual aesthetics.Thanks to all the participants of the interactive evolution experiement. The research was supported, in part, by the FP7 ICT project SIREN (project no: 258453) and by the Danish Research Agency, Ministry of Science, Technology and Innovation project AGameComIn; project number: 274- 09-0083.peer-reviewe

Doctor of Philosophy

dissertationThis dissertation establishes a new visualization design process model devised to guide visualization designers in building more effective and useful visualization systems and tools. The novelty of this framework includes its flexibility for iteration, actionability for guiding visualization designers with concrete steps, concise yet methodical definitions, and connections to other visualization design models commonly used in the field of data visualization. In summary, the design activity framework breaks down the visualization design process into a series of four design activities: understand, ideate, make, and deploy. For each activity, the framework prescribes a descriptive motivation, list of design methods, and expected visualization artifacts. To elucidate the framework, two case studies for visualization design illustrate these concepts, methods, and artifacts in real-world projects in the field of cybersecurity. For example, these projects employ user-centered design methods, such as personas and data sketches, which emphasize our teams' motivations and visualization artifacts with respect to the design activity framework. These case studies also serve as examples for novice visualization designers, and we hypothesized that the framework could serve as a pedagogical tool for teaching and guiding novices through their own design process to create a visualization tool. To externally evaluate the efficacy of this framework, we created worksheets for each design activity, outlining a series of concrete, tangible steps for novices. In order to validate the design worksheets, we conducted 13 student observations over the course of two months, received 32 online survey responses, and performed a qualitative analysis of 11 in-depth interviews. Students found the worksheets both useful and effective for framing the visualization design process. Next, by applying the design activity framework to technique-driven and evaluation-based research projects, we brainstormed possible extensions to the design model. Lastly, we examined implications of the design activity framework and present future work in this space. The visualization community is challenged to consider how to more effectively describe, capture, and communicate the complex, iterative nature of data visualization design throughout research, design, development, and deployment of visualization systems and tools

Evolving levels for Super Mario Bros using grammatical evolution

This paper presents the use of design grammars to evolve playable 2D platform levels through grammatical evolution (GE). Representing levels using design grammars allows simple encoding of important level design constraints, and allows remarkably compact descriptions of large spaces of levels. The expressive range of the GE-based level generator is analyzed and quantitatively compared to other feature-based and the original level generators by means of aesthetic and similarity based measures. The analysis reveals strengths and shortcomings of each generator and provides a general framework for comparing content generated by different generators. The approach presented can be used as an assistive tool by game designers to compare and analyze generators' capabilities within the same game genre.peer-reviewe

A cognition-analogous approach to early-stage creative ideation support in music composition software

Examination of the underlying principles of creativity reveal theoretical aspects that have not been well explored in creativity facilitation software. Most significantly of these, there has been little investigation into exploiting the distinctions between early- and late-stage creative processes and the attendant differences in cognitive processing active at those times, nor into employing the structural scaffolding embedded within creative works and the manner in which these can be extracted and harnessed to define levels of abstraction through which the material can be viewed and manipulated. The Wheelsong project was conceived to exploit these principles, in the service of devising more creatively facilitative music composition tools, by focusing on these earlier, exploratory stages of the creative process, and by privileging structure over minutiae, in alignment with the mode of cognition (and corresponding user needs) that dominate the exploratory phase. Explorations conducted with Wheelsong demonstrate that the platform embraces broad stylistic and cultural ranges of output. Experiments comparing the creative merits of early-stage, fragmentary outputs produced by Wheelsong against those produced by traditional representation schemes show a substantial improvement in both subjective quality and diversity indicators adhering to the structurally produced candidates, as measured by human judges