A Genome Compiler for High Performance Genetic Programming   [GP]

by

Fukunaga, A., Stechert, A. and Mutz, D.

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Info: Genetic Programming 1998: Proceedings of the Third Annual Conference (Conference proceedings), 1998, p. 86-94
Keywords:genetic algorithms, genetic programming
Notes:
GP-98 Thu, 25 Jun 1998 10:31:36 PDT We've recently developed a gp system based on lil-gp which evolves s-expressions and compiles it to machine code (specifically, Sparc machine code) to speed up evaluation. In our system, we've found that the overhead of compilation is negligible, since the vast majority of the time spent in execution in an s-expression interpreter (in our case, the lil-gp interpreter) is consumed by the recursive traversal of the tree. A full description, comparisons with previous GP-compiler systems and some experimental results with symbolic regression and image compression are described
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BibTex:
@InProceedings{fukunaga:1998:gchpGP,
  author =       "Alex Fukunaga and Andre Stechert and Darren Mutz",
  title =        "A Genome Compiler for High Performance Genetic
                 Programming",
  booktitle =    "Genetic Programming 1998: Proceedings of the Third
                 Annual Conference",
  year =         "1998",
  editor =       "John R. Koza and Wolfgang Banzhaf and Kumar
                 Chellapilla and Kalyanmoy Deb and Marco Dorigo and
                 David B. Fogel and Max H. Garzon and David E. Goldberg
                 and Hitoshi Iba and Rick Riolo",
  pages =        "86--94",
  address =      "University of Wisconsin, Madison, Wisconsin, USA",
  publisher_address = "San Francisco, CA, USA",
  month =        "22-25 " # jul,
  publisher =    "Morgan Kaufmann",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "1-55860-548-7",
  URL =          "http://www-aig.jpl.nasa.gov/public/home/fukunaga/publications/compile-camera.ps",
  notes =        "GP-98

                 Thu, 25 Jun 1998 10:31:36 PDT We've recently developed
                 a gp system based on lil-gp which evolves s-expressions
                 and compiles it to machine code (specifically, Sparc
                 machine code) to speed up evaluation. In our system,
                 we've found that the overhead of compilation is
                 negligible, since the vast majority of the time spent
                 in execution in an s-expression interpreter (in our
                 case, the lil-gp interpreter) is consumed by the
                 recursive traversal of the tree.

                 A full description, comparisons with previous
                 GP-compiler systems and some experimental results with
                 symbolic regression and image compression are
                 described",
}