Graph Grammars as a Representation for Interactive Evolutionary 3D Design

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

  author =       "James McDermott",
  title =        "Graph Grammars as a Representation for Interactive
                 Evolutionary {3D} Design",
  booktitle =    "Proceedings of the 1st International Conference on
                 Evolutionary and Biologically Inspired Music, Sound,
                 Art and Design, EvoMUSART 2012",
  year =         "2012",
  month =        "11-13 " # apr,
  editor =       "Penousal Machado and Juan Romero and 
                 Adrian Carballal",
  series =       "LNCS",
  volume =       "7247",
  publisher =    "Springer Verlag",
  address =      "Malaga, Spain",
  pages =        "199--210",
  organisation = "EvoStar",
  isbn13 =       "978-3-642-29141-8",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution, graph grammars, 3D design, interactive
                 evolutionary computation",
  DOI =          "doi:10.1007/978-3-642-29142-5_18",
  abstract =     "A new interactive evolutionary 3D design system is
                 presented. The representation is based on graph
                 grammars, a fascinating and powerful formalism in which
                 sub-graphs, 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 reported,
                 demonstrating the flexibility of the representation.
                 Comparison with results using an alternative graph
                 representation demonstrates that the graph grammar
                 search space is rich in appealing, organised designs. A
                 set of numerical graph features are defined in an
                 attempt to computationally distinguish between good and
                 bad areas of the search space, leading to the
                 definition of a computational fitness function and
                 non-interactive runs.",
  notes =        "See also \cite{McDermott:2013:GPEM} Part of
                 \cite{Machado:2012:EvoMusArt_proc} EvoMUSART'2012 held
                 in conjunction with EuroGP2012, EvoCOP2012 EvoBIO2012
                 and EvoApplications2012",
  affiliation =  "EvoDesignOpt,CSAIL, MIT, USA",

Genetic Programming entries for James McDermott