Abstract — We present an introduction to the new interdisciplinary area of aesthetic computing and then define this area with examples from each of our own disciplines, practices, and research. While several decades of publication and work have resulted in significant advancements in art, as instrumented with technology, less emphasis has been placed on studying the converse issue of art affecting computing, or “aesthetic computing. ” We present our individual work in this area, and then critique each others ’ work to surface different perspectives of the area. By approaching the topic of aesthetic computing in this manner, the paper serves as an introduction, survey, and analysis of the field.

Among the different sorts of challenges for the modeling and simulation community, two types of challenges face us: challenges that optimize space and time for the computer, and challenges that improve the human interface to the modeling and simulation process itself. While of these types of challenges are important for the future health of simulation, we present a grand challenge of the latter variety, based on an area termed integrative multimodeling. The purpose of integrative multimodeling is to provide a human-computer interaction environment that allows components of different model types to be linked to one another—most notably dynamic models used in simulation to geometry models for the phenomena being modeled. We specify current modeling practices in simulation and proceed to justify a need for the challenge. We then follow this with two areas: aesthetic computing and the RUBE software framework, which supports customized “notations” for dynamic models constructed using the eXtensible Markup Language (XML).

The task of visualization, as it applies to computing, includes by default the notion of pluralism and perspectivism since there is an explicit attempt at representing one, often textual, interface in terms of a more graphical one. This desire for alternate perspectives is consistent with art theory and practice, and even though rigor and formalism generally mean different things to artists and computer scientists, there is room for collaboration and connection by applying artistic aesthetics to computing, while maintaining that which makes computing a viable, usable field. This new area is called aesthetic computing. Within this area, there is an attempt to balance qualitative with quantitative representational aspects of visual computing, recognizing that aesthetics creates a dimension that is consistent with supporting numerous visual perspectives. I introduce one aspect of aesthetic computing, with specific examples from our research and teaching to illustrate the potential and possibilities associated with alternate representations. We show that by linking with aesthetics, we surface some important philosophical and cultural questions regarding notation, which turn out to be at least as important as the algorithmic and procedural means of achieving customized model component representations.

We present empirical results from a new approach, Aesthetic Computing to customizing model structures for designing models for systems found in mathematics and computer simulation. At the University of Florida, we have taught the methodology of Aesthetic Computing as a separate class, and within the context of a Simulation class. Students in the simulation class were taught the method and then subsequently allowed to construct their own interactive 3D representations of typical simulation model structures such as Petri nets and finite state automata. While using the method, natural issues arise, questioning where aesthetic computing can provide benefit in model representation. To help answer such questions, a student needs to be presented with a body of knowledge that represents the “aesthetic computing technique, ” and then the student applies this knowledge to create the modeling artifacts. We present recent empirical studies from two classes, Aesthetic Computing and Computer Simulation, where aesthetic “methods/techniques” were employed. From the studies, we determined that there were several key results associated with Aesthetic Computing: 1) the ability for the student to be more creative in building their own custom models, and 2) the ability to improve perceived communication of technical topics (e.g., associated with the models) to non-experts.