Approaches to Evolutionary Architectural Design Exploration Using Grammatical Evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Jonathan Byrne",
  title =        "Approaches to Evolutionary Architectural Design
                 Exploration Using Grammatical Evolution",
  school =       "School of Computer Science and Informatics, University
                 College Dublin",
  year =         "2012",
  address =      "Ireland",
  month =        aug # " 6",
  keywords =     "genetic algorithms, genetic programming, Grammatical
  URL =          "",
  size =         "220 pages",
  abstract =     "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

                 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

                 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.",
  notes =        "Supervisor Michael


Genetic Programming entries for Jonathan Byrne