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The Generation of Form Using an Evolutionary Approach

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Artificial Intelligence in Design ’96

Abstract

This paper presents an evolutionary approach to design using a hierarchical growth model. It argues that the evolutionary approach fits well to the well-known generate-and-test approach in design and is especially suited to design situations where the (inter)relationships between complex arrangements of elements and their behaviour are not known. The evolutionary approach is used as the computational method for the synthesis and evaluation stage of the design process. A hierarchical model of design is used to avoid the combinatorial problems involved in linear models. The concepts are exemplified in the context of the design of house plans.

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References

  • Beasley, D., Bull, D. R. and Martin R. R.: 1993, An overview of genetic algorithms: Part 1, fundamentals, University Computing, 15(2), 58–69.

    Google Scholar 

  • Coyne, R. D.: 1988, Logic Models of Design, Pitman, London.

    MATH  Google Scholar 

  • Cramer, N. L.: 1985, A representation for the adaptive generation of simple sequential programs, Proceedings of an International Conference on Genetic Algorithms and their Application, pp. 183–187.

    Google Scholar 

  • Dawkins, R.: 1986, The Blind Watchmaker, Penguin Books.

    Google Scholar 

  • Gero, J. S., Louis, S. J. and Kundu, S.: 1994, Evolutionary learning of novel grammars for design improvement, AIEDAM, 8(3), 83–94.

    Article  Google Scholar 

  • Goldberg, D. E.: 1989, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, Mass.

    MATH  Google Scholar 

  • Grefenstette, J. J. and Baker, J. E.: 1989, How genetic algorithms work; a critical look at implicit parallelism, in J. D. Schaffer (ed.), Proceedings of the Third International Conference on Genetic Algorithms, Morgan Kaufmann, San Mateo, CA, pp. 20–27.

    Google Scholar 

  • Holland, J. H.: 1975, Adaptation in Natural and Artificial Systems, The University of Michigan Press, Ann Arbor.

    Google Scholar 

  • Horn, J., Nafpliotis, N. and Goldberg, D. E.: 1994, A niched Pareto genetic algorithm for multiobjective optimization, Proceedings of the First IEEE Conference on Evolutionary Computation (ICEC’ 94), Vol 1, IEEE World Congress on Computational Intelligence, Pistcataway, NJ: IEEE Service Center, pp. 82–87.

    Google Scholar 

  • Jo, J. H.: 1993, A Computational Design Process Model using a Genetic Evolution Approach, PhD Thesis, Department of Architecural and Design Science, University of Sydney (unpublished).

    Google Scholar 

  • Jo, J. H. and Gero, J. S.: 1995, A genetic search approach to space layout planning, Architectural Science Review, 38(1), 37–46.

    Article  Google Scholar 

  • Koza, J. R.: 1992, Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press, Cambridge, Mass.

    MATH  Google Scholar 

  • Rosca, J. P. and Ballard, D. H.: 1994, Hierarchical self-organization in genetic programming, Proceedings of the Eleventh International Conference on Machine Learning, Morgan Kaufmann, San Mateo, CA, pp. 252–258.

    Google Scholar 

  • Rosenman, M. A.: 1995, An edge vector representation for the construction of 2-dimensional shapes, Environment and Planning B: Planning and Design, 22, 191–212.

    Article  Google Scholar 

  • Rosenman, M. A. and Gero, J. S.: 1994, The what, the how, and the why in design, Applied Artificial Intelligence, 8(2), 199–218.

    Article  Google Scholar 

  • Schnier, T. and Gero, J. S.: 1995, Learning representations for evolutionary computation, in X. Yao (ed.), AI’95 Eighth Australian Joint Conference on Artificial Intelligence, World Scientific, Singapore, pp. 387–394.

    Google Scholar 

  • Simon, H. A.: 1969, The Sciences of the Artificial, MIT Press, Cambridge, Mass.

    Google Scholar 

  • Stiny, G. and Mitchell, W.: 1978, The Palladian Grammar, Environment and Planning B, 5, 5–18.

    Article  Google Scholar 

  • Stiny, G.: 1980, Introduction to shape and shape grammars, Environment and Planning B, 7,343–351.

    Article  Google Scholar 

  • Todd, S. and Latham, W.: 1992, Evolutionary Art and Computers, Academic Press, London.

    MATH  Google Scholar 

  • Wilson, S. W. and Goldberg, D. E.: 1989, A critical review of classifier systems, in J. D. Schaffer (ed.), Proceedings of the Third International Conference on Genetic Algorithms, Morgan Kaufmann, San Mateo, CA, pp. 244–255.

    Google Scholar 

  • Woodbury, R. F.: 1993, A genetic approach to creative design, in J. S. Gero and M. L. Maher (eds), Modelling Creativity and Knowledge-Based Creative Design, Lawrence Erlbaum, Hillsdale, NJ, pp. 211–232.

    Google Scholar 

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© 1996 Kluwer Academic Publishers

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Rosenman, M.A. (1996). The Generation of Form Using an Evolutionary Approach. In: Gero, J.S., Sudweeks, F. (eds) Artificial Intelligence in Design ’96. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-0279-4_34

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  • DOI: https://doi.org/10.1007/978-94-009-0279-4_34

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-6610-5

  • Online ISBN: 978-94-009-0279-4

  • eBook Packages: Springer Book Archive

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