CGA shape, a novel shape grammar for the procedural modeling of CG architecture, produces building shells with high visual quality and geometric detail. It produces extensive architectural models for computer games and movies, at low cost. Context sensitive shape rules allow the user to specify interactions between the entities of the hierarchical shape descriptions. Selected examples demonstrate solutions to previously unsolved modeling problems, especially to consistent mass modeling with volumetric shapes of arbitrary orientation. CGA shape is shown to efficiently generate massive urban models with unprecedented level of detail, with the virtual rebuilding of the archaeological site of Pompeii as a case in point.

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This paper presents a new method for the automatic modeling of architecture. Building designs are derived using split grammars, a new type of parametric set grammar based on the concept of shape. The paper also introduces an attribute matching system and a separate control grammar, which offer the ßexibility required to model buildings using a large variety of different styles and design ideas. Through the adaptive nature of the design grammar used, the created building designs can either be generic or adhere closely to a speciÞed goal, depending on the amount of data available.

Introduction Design is a purposeful knowledge-based human activity whose aim is to create form which, when realized, satisfies the given intended purposes. 1 Design may be categorized as routine or non-routine with the latter further categorized as innovative or creative. The lesser the knowledge about existing relationships between the requirements and the form to satisfy those requirements, the more a design problem tends towards creative design. Thus, for non-routine design, a knowledge-lean methodology is necessary. Natural evolution has produced a large variety of forms well-suited to their environment suggesting that the use of an evolutionary approach could provide meaningful design solutions in a non-routine design environment. This work investigates the possibilities of using an evolutionary approach based on a genotype which represents design grammar rules for instructions on locating appropriate building blocks. A decomposition/aggregation hierarc

This paper describes an approach to interactive design tasks based on Relational Grammars. Relational Grammars extend traditional one-dimensional string languages to higher dimensions through user-supplied domain relations. Design support takes the form of graphic inferences on partial input during design interaction with the user. Because of the nature of the rule definitions, design elements can be roughly "sketched " without concern for their specific details. During the interaction process, the system installs constraints, adds default attributes, and/or builds higher-level composite structures out of the original input. An example scenario of the use of this formalism is presented supporting the task of document design. A general algorithm for the integration of grammarbased parsing in an interactive design environment is presented.

This paper describes a design method based on constructing a genetic/evolutionarydesign model whose idea is borrowed from natural genetics. Two major issues from the modelling involve how to represent design knowledge for the evolutionary design model and the usefulness of the model for design problems. For the representation of design knowledge in the model, a schema concept is introduced. The utility of the model is based on its computational efficiency and its capability of producing satisfactory solutions for the given set of problem requirements. The design problem used to demonstrate the approach is a large office layout planning problem with its associated topological and geometrical arrangements of space elements. An example drawn from the literature is used.

Introduction This chapter presents two examples of work for evolving designs by generating useful complex gene structures. where the first example uses a genetic engineering approach whereas the other uses a growth model of form. Both examples have as their motivation to overcome the combinatorial effect of large design spaces by focussing the search in useful areas. This focussing is achieved by starting with design spaces defined by low-level basic genes and creating design spaces defined by increasingly more complex gene structures. In both cases the low-level basic genes represent simple design actions which when executed produce parts of design solutions. Both works are exemplified in the domain of architectural floor plans. Evolving Complex Design Genes Using a Genetic Engineering Approach Evolutionary systems are often superior to other search algorithms for problem consisting of large unstructured search spaces, where no heuristic exists to guide the

An exploration-based generatire model of design is proposed. Shape grammars are used as a framework for the lmowledge representation within this model. The routine

Abstract. We are here dealing with the problem of space layout planning. We present an approach based on an intermediate topological level with dynamic space ordering (dso) heuristics. Our software ARCHiPLAN proceeds through a number of steps. First, all the topologically different solutions, without presuming any precise dimension, are enumerated. Next, we may evolve in this topological solution space, and than refine some of them to form consistent geometrical solutions. For each topological solution chosen, the optimising geometrical solution is determined from a cost, useful surface or wall length. By using dynamic space ordering heuristics in the topological level the enumeration time has been reduced.