Conference report

Second international round-table conference on computational models of creative design 610 December 1992, Heron Island, Queens-

land, Australia

The announcement of this conference attracted a lot of international interest, not only because of its exotic location on the Great Barrier Reef, of course, but also because of its intellectually challenging mix of computation and creativity in a design context. The attendance was deliber- ately kept small (23 participants) in order to promote high-quality contributions, in-depth discussion and the commitment of the partici- pants. It certainly worked; this is the first con- ference that I have attended for a long time at which I actually attended all of the sessions, and this despite the exotic location. The conference organizer and chair, John Gero, is to be con- gratulated not only on the initial conception and planning of the conference, but also for the skilful way in which he kept discussion moving and focusing on fundamental issues during each of the separate presentations.

Ten presentations were made, covering topics such as evolution, genetic algorithms, mutation, emergence and analogy. In addition, two other papers were accepted, and included in the con- ference preprints. As well as Australia, partici- pants came from New Zealand, USA, UK, Switzerland, The Netherlands and Japan. Although engineering (machine and structural) design was the predominant practical domain of reference, architecture, product design and graphics were also covered. It is clear that there

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are still fundamental concepts in design re- search, particularly with respect to computation and creativity, that can be addressed produc- tively across different domains of practice.

An issue which arose early in discussion was whether this field of research was aimed at supporting creative design (i.e. through interac- tive systems that aid the designer’s creativity) or at emulating creative design (i.e. through com- putational machines that are themselves crea- tive). Examples of both were included, although it was not always clear what an author’s primary intention was, since work concerned with emu- lating creativity makes frequent reference to the cognitive behaviour of creative designers, just as does work concerned with supporting that be- haviour.

In the extreme, computational machines may not ‘emulate’ human creative cognitive proces- ses, but have their own processes that are quite distinct, just as flying machines do not ‘emulate’

the motion of birds. However, constant refer- ence to human cognitive behaviour may be inevitable, because it is the results of that be- haviour which set the standards for creativity against which to assess the progress of the computational machines, just as chess-playing machines are matched against human chess mas- ters. The highest standards for creative design that are (currently) available to us are those provided by the most creative human designers. There is still a gap in design research here, because we do not have a strong consensual view of the nature of this human creative design cognition. The danger is that computational

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research may be based on naive or reductionist things that human beings simply cannot do (e.g. views of the nature of this human cognitive to fly). Our design machines should do some ability. things that designers cannot do.

Where the goal of the computational research is to provide interactive systems that support crea- tive design work, then knowledge of the human designer’s cognitive behaviour is of fundamental importance, since the users of these systems (i.e. creative designers) must be able to use them in ways which are cognitively comfortable. That is, the systems must be designed on the basis of models of the normal cognitive be- haviour of the system users.

However, the instrumental goals of developing either interactive creative systems or auton- omous creative machines are not the only goals of this research field. For some an intrinsic goal is to further our understanding of human cogni- tive behaviour by attempting to model or emu- late it. The analogy might again be made with computational modelling of chess playing. The goals of such modelling are not simply to pro- duce machines that can (in some sense) ‘play’ chess, or fatuously to replace human chess players by machines. The goals include further- ance of our understanding of the nature of the ‘problem’ of the chess game itself, and of the nature of the human cognitive processes which are brought to bear in chess playing and in the resolution of chess problems. In such ways we further our understanding of ourselves.

Nevertheless, basing the model-building for Presentations concerned more with the develop- creative computational machines on human ment of interactive systems to support creative creative cognitive behaviour could ultimately be design were those by Edmonds (University of self-defeating. Chess-playing machines may Technology, Loughborough, UK), Smith and have learned some cognitive strategies from Faltings (both of the Federal Institute of Tech- human chess players, but they do not ‘think’ like nology, Lausanne, Switzerland). The latter was them. We want (at least some of) our machines the only author actually able to claim that a to do things that are not merely difficult or genuinely novel, creative design had resulted arduous for human beings to do, but to do from application of the research work - a new

The presentations by Maher (University of Syd- ney, Australia), Prabhakar (University of Tech- nology, Sydney), Lenart (University of Kassel, Germany) and Schmidt (Carnegie Mellon Uni- versity, Pittsburgh, USA) were mainly con- cerned with the goal of developing creative machines. Of these, Maher’s (a joint paper with Zhao) was perhaps the most interesting. It was based upon identifying the human cognitive strategies of analogy and mutation in creative problem solving, for example as developed in Gordon’s Synectics strategies. Two computa- tional operators have been developed by Maher and Zhao - SCALE for mutation and COM- BINE for analogy (combined with mutation). Although the theoretical work underlying this research is impressive, the actual practical ap- plications (in structural design) are so far very limited and rather forced. As with other papers in this category, it was not at all clear that any truly creative results had yet been attained. In general, they pursued theoretical computational problems and strategies, which may or may not have an ultimate creative pay-off. Prabhakar’s paper was concerned with identifying perform- ance factors in product design; Lenart discussed genetic algorithm applications in building de- sign; and Schmidt described the use of a ‘shape annealing’ approach to machine design.

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form of gearing system. Edmonds’ paper was interesting in that it was premised upon the importance of drawing as a creative act, and upon the recognition of ‘emergent’ forms that arise from the combination of other forms and are not themselves explicitly drawn. Smith used examples of the Walkman cassette player and the cable-stayed bridge as demonstrations of creative innovation through combination of ex- isting components and the redefinition of func- tional contexts, and his paper was concerned with the representation of functional context in computational models.

The other presentations, by Gero (University of Sydney), Sargent (University of Cambridge, UK) and Zhao (Florida International Universi- ty, Miami, USA) were more generalized in their approach. Zhao (a joint paper with Meyer and Fenves) described the use of adjacency struc- tures as a generalized representation for the design of structural systems of buildings, and how this representation may (in theory) support aspects of creative design such as expanding the search space, analogy and mutation. Sargent’s paper was concerned with the issue of creating new problem spaces that accommodate diffe- rent, perhaps incommensurate, world views. Gero’s paper presented the foundation-laying progress that is being made in evolutionary models of design, and with the concept of ‘emergence’ in particular.

In the concluding discussion session, emergence emerged as a key concept that is not only fundamental to computational models of crea- tive design, but also may be fundamental to design research more generally. In this respect, it was felt that work in computational modelling is helping to identify something that is charac- teristic of (creative) design, and thereby helping to define a distinctive feature of design research. Emergence is the concept of implicit structure arising from other, explicit structures, and is a matter not simply of pattern recognition but of pattern definition by the designer during the evolution of problem requirements and solution concepts. A similar distinctive feature of design was thought to be that of the exploration, rather than search, of problem spaces. Search is an easier concept to programme, since it is con- cerned to identify a particular solution whereas exploration is concerned with finding something that can only be identified as interesting or valuable once it has been found.

This was therefore a very successful conference which managed to combine the pursuit of a particular subset of design research activities with consideration of broader issues and the more general purposes or goals of the field of design research.

Niger Cross

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