Anthropocentric Biocybernetic Computing for Analysing the Architectural Design of House Façades and Cityscapes

By Stephan K. Chalup and Michael J. Ostwald.

Published by The Design Collection

Format Price
Article: Print $US10.00
Article: Electronic $US5.00

Research in artificial intelligence and autonomous agents envisions that future robots will accompany humans in their daily lives. The aim is to provide support not only for routine, challenging, or dangerous tasks, but also to improve quality of life through personal assistance and coaching. In order to allow artificial agents to communicate sensibly and to participate in human society, it is important to equip them with the ability to perceive and appreciate aesthetic features of design in a human-like manner.

The present study investigates how methods from anthropocentric biocybernetic computing (ABC) can be assembled in an intelligent control module for architectural design evaluation. Central to the system is an abstract model of aesthetic experience, which is established through statistical learning. For the experiments, a database of images of house façades is employed. The learning algorithm extracts line distributions, which characterise façade design, and represents them abstractly in the form of a non-linear manifold. Each point on the manifold corresponds to one façade. The proposed module includes two additional affective perceptual pathways, which are implemented using paradigms that are believed to reflect responses of the human emotional system. One paradigm involves concepts of facial expression recognition, and the other is based on calculating the fractal dimension of the skyline of cityscapes.

Future applicability of the proposed system for design evaluation will rely on suitable data preparation and calibration of the associated algorithms using test subjects. The article describes characteristic details of the system’s architecture and discusses whether it would be able to acquire the level of sophistication required to provide aesthetic judgment that is convincing for humans.

Keywords: Affective Computing, Architecture, Artificial Intelligence, Autonomous, Agents, Cityscapes, Façade Design, Face Recognition, Fractal Dimension, Manifold Learning, Robotics, Skyline, Statistical, Learning

Design Principles and Practices: An International Journal, Volume 3, Issue 5, pp.65-80. Article: Print (Spiral Bound). Article: Electronic (PDF File; 1.846MB).

Dr. Stephan K. Chalup

Senior Lecturer, Newcastle Robotics Laboratory, School of Electrical Engineering & Computer Science, The University of Newcastle, Newcastle, NSW, Australia

Dr. Stephan K. Chalup is director of the Newcastle Robotics Laboratory and a senior lecturer in computer science and software engineering at the University of Newcastle, Australia. He has a PhD in Computer Science/Machine Learning from Queensland University of Technology in Brisbane, Australia, and a Diplom in mathematics with biology from the University of Heidelberg in Germany. In his research he investigated applications of artificial neural networks, evolutionary algorithms, kernel machines, and techniques for dimensionality reduction in areas such as image processing, intelligent system design, language processing, and robo-tics.

Prof. Michael J. Ostwald

School of Architecture and Built Environment, The University of Newcastle, Newcastle, NSW, Australia

Dr. Michael J. Ostwald is Professor and Dean of Architecture at the University of Newcastle, Australia. He is a Visiting Fellow at SIAL and a Professorial Research Fellow at Victoria University Wellington. He has a PhD in architectural philosophy and a higher doctorate (DSc) in the mathematics of design. He is co-editor of the journal Architectural Design Research and on the editorial boards of Architectural Theory Review and the Nexus Network Journal. His recent books include The Architecture of the New Baroque (2006), Homo Faber: Modelling Design (2007) and Residue: Architecture as a Condition of Loss (2007).

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