Abstract
A new interactive evolutionary 3D design system is presented. The representation is based on graph grammars, a fascinating and powerful formalism in which nodes and edges are iteratively rewritten by rules analogous to those of context-free grammars and shape grammars. The nodes of the resulting derived graph are labelled with Euclidean coordinates: therefore the graph fully represents a 3D beam design. Results from user-guided runs are presented, demonstrating the flexibility of the representation. Comparison with results using an alternative graph representation demonstrates that the graph grammar search space is more rich in organised designs. A set of numerical features are defined over designs. They are shown to be effective in distinguishing between the designs produced by the two representations, and between designs labelled by users as good or bad. The features allow the definition of a non-interactive fitness function in terms of proximity to target feature vectors. In non-interactive experiments with this fitness function, the graph grammar representation out-performs the alternative graph representation, and evolution out-performs random search.
Similar content being viewed by others
References
S. Bergen, B. Ross, in Aesthetic 3D Model Evolution, ed. by P. Machado, J. Romero, A. Carballal. Proceedings of the 1st International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design, EvoMUSART 2012. LNCS, vol. 7247 (Springer, Malaga, 2012), pp. 11–22
J. Byrne, M. Fenton, E. Hemberg, J. McDermott, M. O’Neill, E. Shotton, C. McNally, in Combining Structural Analysis and Multi-objective Criteria for Evolutionary Architectural Design. EvoWorkshops (Springer, Torino, 2011)
J. Cagan, in Engineering Shape Grammars: Where We Have Been and Where We are Going. Formal engineering design synthesis (Cambridge University Press, Cambridge, 2001), p. 92
J. Cagan, C.M. Vogel, Creating Breakthrough Products: Innovation from Product Planning to Program Approval (Prentice Hall, Upper Saddle River, 2001)
N. Chomsky, Three models for the description of language. Trans. Inf. Theory 2(3), 113–124 (1956)
J. Clune, H. Lipson, in Evolving Three-Dimensional Objects with a Generative Encoding Inspired by Developmental Biology. Proceedings of the European Conference on Artificial Life (2011). URL http://endlessforms.com
J. Clune, K.O. Stanley, R.T. Pennock, C. Ofria, On the performance of indirect encoding across the continuum of regularity. IEEE Trans. Evol. Comput. 15(3), 346–367 (2011)
R. Dawkins, The Blind Watchmaker (Longman Scientific and Technical, Harlow, 1986)
H. Ehrig, M. Korff, M. Löwe, in Tutorial Introduction to the Algebraic Approach of Graph Grammars Based on Double and Single Pushouts. Graph Grammars and Their Application to Computer Science (Springer, Berlin, 1991), pp. 24–37
L. Fogel, P. Angeline, D. Fogel, in An Evolutionary Programming Approach to Self-Adaptation on Finite State Machines. Proceedings of the Fourth International Conference on Evolutionary Programming (1995), pp. 355–365
E. Galván-López, J. McDermott, M. O’Neill, A. Brabazon, Defining locality as a problem difficulty measure in genetic programming. Genet. Program. Evolv. Mach. 12(4), 365–401 (2012)
E. Gilbert, Random graphs. Ann. Math. Stat. 30(4), 1141–1144 (1959)
J. Gips, in Computer Implementation of Shape Grammars. NSF/MIT Workshop on Shape Computation (1999). URL: http://www.shapegrammar.org/nsfmit.html
F. Gruau, in Neural Network Synthesis Using Cellular Encoding and the Genetic Algorithm. PhD thesis, Laboratoire de l’Informatique du Parallilisme, Ecole Normale Supirieure de Lyon, France (1994). URL: ftp://ftp.ens-lyon.fr/pub/LIP/Rapports/PhD/PhD1994/PhD1994-01-E.ps.Z
Z. Gu, M. Xi Tang, J. Frazer, Capturing aesthetic intention during interactive evolution. Comput. Aided Des. 38(3):224–237 (2006)
A.A. Hagberg, D.A. Schult, P.J. Swart, Exploring Network Structure, Dynamics, and Function Using NetworkX. Proceedings of the 7th Python in Science Conference (SciPy2008) (Pasadena, CA, USA, 2008), pp. 11–15
E. den Heijer, A. Eiben, in Evolving Art with Scalable Vector Graphics. Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation (ACM, Dublin, 2011), pp. 427–434
M. Hemberg, U.M. O’Reilly, A. Menges, K. Jonas, M. da Costa Goncalves, S. Fuchs, in Genr8: Architect’s Experience Using an Emergent Design Tool, ed. by P. Machado, J. Romero. The Art of Artificial Evolution (Springer, Berlin, 2007)
G.S. Hornby, J.D. Lohn, D.S. Linden, Computer-automated evolution of an X-band antenna for NASA’s space technology 5 mission. Evol. Comput. 19(1), 1–23 (2011)
G.S. Hornby, J.B. Pollack, in The Advantages of Generative Grammatical Encodings for Physical Design. Proceedings of the CEC (IEEE 2001), pp. 600–607
D. Jackson, in A New, Node-Focused Model for Genetic Programming, ed. by A. Moraglio, S. Silva, K. Krawiec, P. Machado, C. Cotta. Proceedings of the 15th European Conference on Genetic Programming (EuroGP 2012). LNCS, vol. 7244 (Springer, Malaga, 2012), pp. 49–60
C.G. Johnson, in Fitness in Evolutionary Art and Music: What has Been Used and What Could Be Used?, ed. by P. Machado, J. Romero, A. Carballal. Proceedings of the 1st International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART 2012). LNCS, vol. 7247 (Springer, Malaga, 2012), pp. 129–140
H. Keles, M. Özkar, S. Tari, Embedding shapes without predefined parts. Environ. Plan. B. Plan. Des. 37(4), 664–681 (2010)
T. Knight, Computing with emergence. Environ. Plan. B. Plan. Des. 30(2) (2003)
T.W. Knight, The generation of Hepplewhite-style chair-back designs. Environ. Plan. B 7(2), 227–238 (1980)
T.W. Knight, Transformations of De Stijl art: the paintings of Georges Vantongerloo and Fritz Glarner. Environ. Plan. B. Plan. Des. 16(1), 51–98 (1989)
H. Koning, J. Eizenberg, The language of the prairie: Frank Lloyd Wright’s prairie houses. Environ. Plan. B 8, 295–323 (1981)
Y. Li, C. Hu, M. Chen, J. Hu, in Investigating Aesthetic Features to Model Human Preference in Evolutionary Art, ed. by P. Machado, J. Romero, A. Carballal. Proceedings of the 1st International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART 2012). LNCS, vol. 7247 (Springer, Malaga, 2012), pp. 153–164
M.H. Luerssen, D.M.W. Powers, in Graph Design by Graph Grammar Evolution. Proceedings of the CEC. (IEEE, 2007), pp. 386–393
S. Luke, L. Spector, in Evolving Graphs and Networks with Edge Encoding: Preliminary Report, ed. by J.R. Koza. Late Breaking Papers at the Genetic Programming 1996 Conference Stanford University July 28–31, 1996 (Stanford Bookstore, Stanford University, CA, USA, 1996), pp. 117–124. URL: http://www.cs.gmu.edu/sean/papers/graph-paper.pdf
J. McCormack, J. Cagan, Curve-based shape matching: supporting designers’ hierarchies through parametric shape recognition of arbitrary geometry. Environ. Plan. B Plan. Des. 33(4), 523 (2006)
J. McDermott, in Graph Grammars As a Representation for Interactive Evolutionary 3D Designed. by P. Machado, J. Romero, A. Carballal. Proceedings of the 1st International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART 2012). LNCS, vol. 7247 (Springer, Malaga, 2012), pp. 199–210
J. McDermott, J. Byrne, J.M. Swafford, M. Hemberg, C. McNally, E. Shotton, E. Hemberg, M. Fenton, M. O’Neill, String-rewriting grammars for evolutionary architectural design. Environ. Plan. B Plan. Des. 39(4), 713–731 (2012). URL: http://www.envplan.com/abstract.cgi?id=b38037
J. McDermott, J. Byrne, J.M. Swafford, M. O’Neill, A. Brabazon, in Higher-Order Functions in Aesthetic EC Encodings. CEC 2010: Proceedings of the 12th Annual Congress on Evolutionary Computation. (IEEE Press, Barcelona, 2010), pp. 3018–3025
J.F. Miller, P. Thomson, in Cartesian Genetic Programming. EuroGP (Springer, Berlin, 2000), pp. 121–132
M. Nicolau, I. Dempsey, in Introducing Grammar Based Extensions for Grammatical Evolution. Proceedings of the CEC (IEEE, Vancouver, 2006), pp. 2663–2670
M. O’Neill, C. Ryan. Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language (Kluwer, Dordrecht, 2003)
U.M. O’Reilly, M. Hemberg, Integrating generative growth and evolutionary computation for form exploration. Genet. Program. Evolv. Mach. 8(2), 163–186 (2007)
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, E. Duchesnay, Scikit-learn: Machine learning in python. J.Mach. Learn. Res. 12, 2825–2830 (2011)
U. Piazzalunga, P. Fitzhorn, Note on a three-dimensional shape grammar interpreter. Environ. Plan. B 25, 11–30 (1998)
R. Poli, in Parallel Distributed Genetic Programming, ed. by D. Corne, M. Dorigo, F. Glover. New Ideas in Optimization, Advanced Topics in Computer Science, chap. 27 (McGraw-Hill, Maidenhead, 1999), pp. 403–431
J. Pollack, H. Lipson, G. Hornby, P. Funes, Three generations of automatically designed robots. Artif. Life 7(3), 215–223 (2001)
M. Pugliese, J. Cagan, Capturing a rebel: modeling the Harley–Davidson brand through a motorcycle shape grammar. Res. Eng. Des. 13(3) (2002). doi:10.1007/s00163-002-0013-1
G. Reddy, J. Cagan, An improved shape annealing algorithm for truss topology generation. J. Mech. Des. 117, 315 (1995)
F. Rothlauf, Representations for Genetic and Evolutionary Algorithms, 2nd edn (Physica-Verlag, Heidelberg, 2006)
F. Rothlauf, On the bias and performance of the edge-set encoding. IEEE Trans. Evol. Comput., 13(3), 486–499 (2009)
K. Sims, in Artificial Evolution for Computer Graphics. Proceedings of the 18th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH ’91) (ACM, New York, 1991), pp. 319–328
K. Stanley, R. Miikkulainen, Evolving neural networks through augmenting topologies. Evol. Comput., 10(2), 99–127 (2002)
S.S. Stevens, On the psychophysical law. Psychol. Rev., 64(3), 153–181 (1957)
G. Stiny, J. Gips, in Shape Grammars and the Generative Specification of Painting and Sculpture, ed. by O.R. Petrocelli. The Best Computer Papers of 1971, pp. 125–135. Originally published in: C. V. Freiman (ed.), Information Processing 71: Proceedings of the 1971 Congress of the International Federation for Information Processing, Ljubljana, Yugoslavia
M. Suchorzewski, J. Clune, in A Novel Generative Encoding for Evolving Modular, Regular and Scalable Networks. Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation (ACM, 2011), pp. 1523–1530
H. Takagi, Interactive evolutionary computation: Fusion of the capabilities of EC optimization and human evaluation. Proc. IEEE, 89(9), 1275–1296 (2001)
M. Tapia, A visual implementation of a shape grammar system. Environ. Plan. B, 26, 59–74 (1999)
E. Whiting, J. Ochsendorf, F. Durand, Procedural modeling of structurally-sound masonry buildings. ACM Trans. Graph., 28(5), 112 (2009)
Acknowledgments
The author was funded during this research by the Irish Research Council under the Inspire scheme. Thanks to Jonathan Byrne and Erik Hemberg of the NCRA for providing GUI code. Thanks to Terry Knight of MIT and the MIT Visual Computing class. Thanks to the anonymous reviewers for constructive comments.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
McDermott, J. Graph grammars for evolutionary 3D design. Genet Program Evolvable Mach 14, 369–393 (2013). https://doi.org/10.1007/s10710-013-9190-0
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10710-013-9190-0