Automated Induction of General Grammars for Design

Conference paper


Grammars are useful for representing systems of design patterns, however formulating good grammars is not straightforward in many contexts due to challenges of representation and scope. This challenge has been identified as one of the 3 goals for computerized use of shape grammars: grammar inference. This work introduces a highly flexible mechanism for inducing viable general grammars from a computational representation of a designed context. This mechanism is evaluated with several common types of devised media of increasing complexity based on dimensionality: 1D (e.g., text), 2D (e.g., PCB layout, building plans), many dimensional (which in abstract can generally be used to represent product, system, platform or service designs), and, against a set of grammar properties necessary for a grammar acquisition method to be useful: accuracy, variability, repeatability and conciseness. This work shows complete enumeration over possible grammars in the 1D case and a continuum of approaches for higher dimension data sets that are demonstrative of grammars in design .


Graph Grammar General Grammar Grammar Rule Grammar Property Shape Grammar 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Ball JA (1978) Algorithms for RPN calculators, 1st edn. Wiley, Cambridge. ISBN 0-471-03070-8Google Scholar
  2. Benrós D, Eloy S, Duarte JP (2015) Re-inventing ceramic tiles: using shape grammars as a generative method and the impact on design methodology. In: Proceedings of the 16th International Conference CAAD Futures, pp 467–480Google Scholar
  3. Davies M (2008) The corpus of contemporary American English: 450 million words, 1990–present.
  4. Ding Y, Martha P (2005) Machine translation using probabilistic synchronous dependency insertion grammars. In: Proceedings of the 43rd annual meeting on Association for Computational Linguistics. Association for Computational LinguisticsGoogle Scholar
  5. Ehrig H, Michael P, Hans JS (1973) Graph-grammars: an algebraic approach. In: IEEE conference record of 14th annual symposium on switching and automata theory, 1973. SWAT’08. IEEEGoogle Scholar
  6. Evans TG (1971) Grammatical inference techniques in pattern analysis. Softw Eng 2:183–202Google Scholar
  7. Gips J, Stiny G (1972) Shape grammars and the generative specification of painting and sculpture. In: Freiman CV (ed) Information processing, vol 71. North-Holland, Amsterdam, pp 1460–1465Google Scholar
  8. Gips J (1999) Computer implementation of shape grammars. In: NSF/MIT workshop on shape computation, vol 55Google Scholar
  9. Königseder C, Kristina S (2015) A method for visualizing the relations between grammar rules, performance objectives and search space exploration in grammar-based computational design synthesis. In: ASME 2015 international design engineering technical conferences and computers and information in engineering conference. American Society of Mechanical EngineersGoogle Scholar
  10. NetworkX (2015) networks.orgGoogle Scholar
  11. Orsborn S, Cagan J, Boatwright P (2008) A methodology for creating a statistically derived shape grammar composed of non-obvious shape chunks. Res Eng Des 18(4):163–180CrossRefGoogle Scholar
  12. Slisenko AO (1982) Context-free grammars as a tool for describing polynomial-time subclass of hard problems. Inf Process Lett 14(2):52–56Google Scholar
  13. Stiny G (1980) Introduction to shape and shape grammars. Environ Plann B 7:343–351CrossRefGoogle Scholar
  14. Stiny G, Mitchell WJ (1978) The Palladian grammar. Environ Plann B 5:5–18CrossRefGoogle Scholar
  15. Stolcke A, Omohundro S (1994) Inducing probabilistic grammars by Bayesian model merging. Grammatical inference and applications. Springer, Berlin, pp 106–118CrossRefGoogle Scholar
  16. Suh NP (1990) The principles of design. New York: Oxford University Press. pp 147–188Google Scholar
  17. Talton J et al (2012) Learning design patterns with bayesian grammar induction. In: Proceedings of the 25th annual ACM symposium on user interface software and technology. ACMGoogle Scholar
  18. Yue K, Krishnamurti R (2013) Tractable shape grammars. Environ Plan 40(4):576–594CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Carnegie Mellon UniversityPittsburghUSA

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