Computational Design Emergence by Complexity and Morphogenesis

Emergence is the form or behavior of natural or artificial systems, which materializes due to the system components’ interactions with each other and their environment. Emergent properties are a result of processes of self-organization of complex systems such as swarming behavior of birds, insect colonies, immune systems, cities, the World Wide Web, social interactions, etc., as well as processes of natural morphogenesis that exhibit behavior of growth and adaptation. Emergent systems are also closely related to the field of creative design, where novelty and utility are equally valued. Here, the idea that natural phenomena in nature emerge spontaneously from the interplay of intersity differences is extended to design, wherein design morphogenesis assumes the role of the generative mechanism. The ability of morphogenetic processes to adapt and transform renders the design form dynamic, mutable and evolvable through its transformative interactions. Similar to complex systems, therefore, morphogenetic forms can be said to be emergent. Computational design systems such as agent-based systems, cellular morphologies, branching systems, neural networks, evolutionary algorithms can simulate the mechanisms of emergent systems. Characteristics of such design systems exhibit non-linear bottom-up behavior are accompanied by qualities such as stochastics, spontaneity, unpredictability, irreducibility and innovation instead of typology and standardization. This paper explores the concept of emergence, its implications on and implementation in the creative design field. To this end, we first introduce characteristics of emergent systems in natural and artificial systems as well as design. We then present a design example of a generative system that makes use of diffusion-limited aggregation. Finally, we discuss the potentials and limitations of emergent design systems for both routine and creative design tasks
Generative Art Conference, (15 - 17 Aralık 2016)


Predictive models in ecology: Comparison of performances and assessment of applicability
Tan, Can Ozan; Ozesmi, Uygar; Beklioğlu, Meryem; Per, Esra; Kurt, Bahtiyar (Elsevier BV, 2006-04-01)
Ecological systems are governed by complex interactions which are mainly nonlinear. In order to capture the inherent complexity and nonlinearity of ecological, and in general biological systems, empirical models recently gained popularity. However, although these models, particularly connectionist approaches such as multilayered backpropagation networks, are commonly applied as predictive models in ecology to a wide variety of ecosystems and questions, there are no studies to date aiming to assess the perfo...
Graphical models in inference of biological networks
Farnoudkia, Hajar; Purutçuoğlu Gazi, Vilda; Department of Statistics (2020)
In recent years, particularly, on the studies about the complex system’s diseases, better understanding the biological systems and observing how the system’s behaviors, which are affected by the treatment or similar conditions, accelerate with the help of the explanation of these systems via the mathematical modeling. Gaussian Graphical Models (GGM) is a model that describes the relationship between the system’s elements via the regression and represents the states of the system via the multivariate Gaussia...
Computation and analysis of spectra of large undirected networks
Erdem, Özge; Karasözen, Bülent; Jost, Jürgen; Department of Scientific Computing (2010)
Many interacting complex systems in biology, in physics, in technology and social systems, can be represented in a form of large networks. These large networks are mathematically represented by graphs. A graph is represented usually by the adjacency or the Laplacian matrix. Important features of the underlying structure and dynamics of them can be extracted from the analysis of the spectrum of the graphs. Spectral analysis of the so called normalized Laplacian of large networks became popular in the recent ...
Computer simulation of processes involving multicomponent multiphase equilibria
Aras, Mustafa Serdal; Karakaya, İshak; Demirci, Gökhan; Department of Metallurgical and Materials Engineering (2016)
A computer program applicable for simulating the chemical processes involving multicomponent multiphase equilibria was developed. The assemblage of the equilibrium phases and their compositions were determined from Gibbs energy minimization. The thermodynamic state of the system was specified by assigning the temperature and pressure. The algorithm of the optimization routine was based on the minimization of the Gibbs energy. The minimization method was performed using the Lagrange’s method of undetermined ...
Characterization and prediction of protein interfaces to infer protein-protein interaction networks
Keskin, Ozlem; Tunçbağ, Nurcan; GÜRSOY, Attila (2008-04-01)
Complex protein-protein interaction networks govern biological processes in cells. Protein interfaces are the sites where proteins physically interact. Identification and characterization of protein interfaces will lead to understanding how proteins interact with each other and how they are involved in protein-protein interaction networks. What makes a given interface bind to different proteins; how similar/different the interactions in proteins are some key questions to be answered. Enormous amount of prot...
Citation Formats
İ. Gürsel Dino, “Computational Design Emergence by Complexity and Morphogenesis,” 2016, p. 226, Accessed: 00, 2021. [Online]. Available: