Creating Complex Building Blocks through Generative Representations

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{hornby:2003:aaaiS,
  author =       "Gregory S. Hornby",
  title =        "Creating Complex Building Blocks through Generative
                 Representations",
  booktitle =    "Computational Synthesis: From Basic Building Blocks to
                 High Level Functionality: Papers from the 2003 AAAI
                 Spring Symposium",
  year =         "2003",
  editor =       "Hod Lipson and Erik K. Antonsson and John R. Koza",
  series =       "AAAI technical report SS-03-02",
  pages =        "98--105",
  address =      "Stanford, California, USA",
  publisher =    "AAAI Press",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "1-57735-179-7",
  URL =          "http://citeseer.ist.psu.edu/cache/papers/cs/30633/http:zSzzSzic.arc.nasa.govzSzpeoplezSzhornbyzSzpaperszSzhornby_ascs03.pdf/hornby03creating.pdf",
  URL =          "http://citeseer.ist.psu.edu/693104.html",
  URL =          "http://www.aaai.org/Press/Reports/Symposia/Spring/ss-03-02.html",
  URL =          "http://ic.arc.nasa.gov/people/hornby/papers/abstracts.html#pollack_alife01",
  abstract =     "One of the main limitations for the functional
                 scalability of computer automated design systems is the
                 representation used for encoding designs. Using
                 computer programs as an analogy, representations can be
                 thought of as having the properties of combination,
                 control-flow and abstraction. We define generative
                 representations as those which have the ability to
                 reuse elements in an encoding through either iteration
                 or abstraction and argue that reuse improves functional
                 scalability by allowing the representation to construct
                 building-blocks and capture design dependencies. Next
                 we describe GENRE, an evolutionary design system for
                 evolving a variety of different types of designs. Using
                 this system we compare the generative representation
                 against a non-generative representation on evolving
                 tables and robots and show that designs evolved with
                 the generative representation have higher fitness than
                 designs created with the non-generative representation.
                 Further, we show that designs evolved with the
                 generative representation are constructed in a modular
                 way through the reuse of discovered building blocks.",
  notes =        "TR SS-03-02",
}

Genetic Programming entries for Gregory S Hornby

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