Aesthetic complexity: practice and perception in art & design

My research investigates the aesthetics of visual complexity in the practice and perception of visual art and design. The aim is to understand visual complexity in terms of the relationship between the objective properties of images and subjective properties of perception. I take a computational and empirical approach to this subject, incorporating methods from information theory, computer graphics, complexity theory and experimental psychology. For testing, I create cellular automata programs to generate stimulus images, and borrow other types of visual material from students and professional artists, designers and craftspeople. Visual complexity is measured in two ways: Firstly, an objective measure of complexity is based on the compression of digital image files, which provides an information-based scale of order to randomness. Secondly, psychophysical techniques are employed to measure the subjective complexity of the images and other aesthetic judgements. Research in complex systems theory and experimental aesthetics suggests that we can expect an inverted ‘U’ correlation between the two measures of complexity

Multifractal Network Generator

We introduce a new approach to constructing networks with realistic features. Our method, in spite of its conceptual simplicity (it has only two parameters) is capable of generating a wide variety of network types with prescribed statistical properties, e.g., with degree- or clustering coefficient distributions of various, very different forms. In turn, these graphs can be used to test hypotheses, or, as models of actual data. The method is based on a mapping between suitably chosen singular measures defined on the unit square and sparse infinite networks. Such a mapping has the great potential of allowing for graph theoretical results for a variety of network topologies. The main idea of our approach is to go to the infinite limit of the singular measure and the size of the corresponding graph simultaneously. A very unique feature of this construction is that the complexity of the generated network is increasing with the size. We present analytic expressions derived from the parameters of the -- to be iterated-- initial generating measure for such major characteristics of graphs as their degree, clustering coefficient and assortativity coefficient distributions. The optimal parameters of the generating measure are determined from a simple simulated annealing process. Thus, the present work provides a tool for researchers from a variety of fields (such as biology, computer science, biology, or complex systems) enabling them to create a versatile model of their network data.Comment: Preprint. Final version appeared in PNAS

Consistency of Social Interactions in Sooty Mangabeys and Chimpanzees

Predictability of social interactions can be an important measure for the social complexity of an animal group. Predictability is partially dependent on how consistent interaction patterns are over time: does the behavior on 1 day explain the behavior on another? We developed a consistency measure that serves two functions: detecting which interaction types in a dataset are so inconsistent that including them in further analyses risks introducing unexplained error; and comparatively quantifying differences in consistency within and between animal groups. We applied the consistency measure to simulated data and field data for one group of sooty mangabeys (Cercocebus atys atys) and to groups of Western chimpanzees (Pan troglodytes verus) in the Taï National Park, Côte d'Ivoire, to test its properties and compare consistency across groups. The consistency measures successfully identified interaction types whose low internal consistency would likely create analytical problems. Species-level differences in consistency were less pronounced than differences within groups: in all groups, aggression and dominance interactions were the most consistent, followed by grooming; spatial proximity at different levels was much less consistent than directed interactions. Our consistency measure can facilitate decision making of researchers wondering whether to include interaction types in their analyses or social networks and allows us to compare interaction types within and between species regarding their predictability.Peer Reviewe

Complexity Metrics for Systems Development Methods and Techniques

So many systems development methods have been introduced in the last decade that one can talk about a ¿methodology jungle¿. To aid the method developers and evaluators in fighting their way through this jungle, we propose a systematic approach for measuring properties of methods. We describe two sets of metrics which measure the complexity of single diagram techniques, and of complete systems development methods. The proposed metrics provide a relatively fast and simple way to analyse the descriptive capabilities of a technique or method. When accompanied with other selection criteria, the metrics can be used for estimating the relative complexity of a technique compared to others. To demonstrate the applicability of the metrics, we have applied them to 36 techniques and 11 methods