Graph grammars for evolutionary 3D design

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  author =       "James McDermott",
  title =        "Graph grammars for evolutionary {3D} design",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2013",
  volume =       "14",
  number =       "3",
  pages =        "369--393",
  month =        sep,
  note =         "Special issue on biologically inspired music, sound,
                 art and design",
  keywords =     "genetic algorithms, genetic programming, Grammatical
                 evolution, Graph grammars, 3D design, Indirect
  ISSN =         "1389-2576",
  DOI =          "doi:10.1007/s10710-013-9190-0",
  size =         "25 pages",
  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.",
  notes =        "This paper is an expanded and improved version of
                 Graph Grammars as a Representation for Interactive
                 Evolutionary 3D Design, presented at EvoMUSART, Malaga,
                 Spain, 2012, \cite{McDermott:2012:EvoMUSART}",

Genetic Programming entries for James McDermott