Approaches to Evolutionary Architectural Design Exploration Using Grammatical Evolution
Jonathan Byrne · 2012
The architectural design process is both subjective and objective in nature. The designer and end user judge a design not only by objective functionality but also by subjective form. Despite the ability of evolutionary algorithms to produce creative and novel designs, they have primarily been used to aid the design process by optimising the functionality of a design, once it has been instantiated. Designers should be able to express their subjective and objective intentions with a design tool. Grammatical evolution (GE) is a form of genetic programming that allows evolutionary techniques to be applied to systems that can be represented as a grammar. This thesis examines approaches that allow grammatical evolution to be used in the exploration phase of the architectural design process as well as optimising the design to maximise functionality. The primary focus of this thesis is to increase the amount of direct and indirect interaction available to the designer for evolutionary design exploration. The research gaps which this thesis investigates are the use of novel GE operators for active user intervention, the development of interfaces suitable for directing evolutionary search and the application of functional constraints for guiding aesthetic evolution. The contributions made by this thesis are the development of two component mutation operators, a novel animated interface for user-directed evolution and the implementation of a multi-objective finite element analysis fitness function in GE for the first time. An examination of fitness functions, operators and representations is carried out so that the designer’s input to the evolutionary algorithm can be enhanced. An extensive review of computer-generated architecture, interactive evolution and grammatical evolution is conducted. Initial investigations explore whether the constraints placed on architectural designs can be expressed as a multi-objective fitness function. The application of this technique, as a means of reducing the search space presented to the architect, is then evaluated. Broadening interaction beyond evaluation increases the amount of feedback and bias a user can apply to the search. A study is conducted to examine how integer mutation in GE explores the search space. Two novel and distinct behavioural components in GE mutation are shown to exist, nodal and structural mutation. The locality of the operations is examined at different levels of the derivation process. It is shown that nodal and structural mutation cause different magnitudes of change at the phenotypic level. An interface is designed that enables the architect to directly mutate design encodings that they find aesthetically pleasing. User trials are then conducted on an interface for making localised changes to an individual and evaluate whether it is capable of directing search. The results show that users initially apply structural mutations to explore the search space and then apply smaller nodal mutations to fine tune a solution. The novel interface is shown to enable directed evolutionary search.