CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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id cf2005_2_36_65
authors LIAO Kai and HAN Chia Y.
year 2005
title Collective Pavilions: A Generative Architectural Modelling for Traditional Chinese Pagoda
source Learning from the Past a Foundation for the Future [Special publication of papers presented at the CAAD futures 2005 conference held at the Vienna University of Technology / ISBN 3-85437-276-0], Vienna (Austria) 20-22 June 2005, pp. 129-138
summary This paper investigates generative architectural modelling for traditional Chinese architecture and aims to explore and extend the potential of adaptive computing for architectural design methods. The design manners analysis of traditional pagodas architectures is made in a holistic view and under historical perspective. We propose a descriptive model and generative system for the design of traditional Chinese pagodas, by which each pagoda is defined as a collection of style-matched and form-coordinated pavilions and described by both topological graphs and variant geometrical units. Our approach models both of the building geometry and space organization/spatial patterns of pagodas separately. The generative mechanism consists of a framework of grammar-based design and parametric, recursive shape computation. Accordingly, the generative algorithm is also made of two levels, the topology of spatial patterns and the shape geometrical parameters that characterize pavilion variations. The algorithm for computing the former is based on GP (Genetic Programming) and the latter GA (Genetic Algorithms). To explore the collective behaviour of a group of pavilions, multi-agent modelling approach is incorporated in composition patterns search. A prototype system, 'glPagoda', using the OpenGL graphics library for rendering and visualization, has been developed and implemented on PC windows platform.
keywords pagoda, grammar-based design, multi-agent modelling, generative design system
series CAAD Futures
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