NEAT in HyperNEAT Substituted with Genetic Programming

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

@InProceedings{Buk:2009:ICANNGA,
  author =       "Zdenek Buk and Jan Koutni and Miroslav Snorek",
  title =        "NEAT in HyperNEAT Substituted with Genetic
                 Programming",
  year =         "2009",
  booktitle =    "9th International Conference on Adaptive and Natural
                 Computing Algorithms, ICANNGA 2009",
  editor =       "Mikko Kolehmainen and Pekka Toivanen and 
                 Bartlomiej Beliczynski",
  series =       "Lecture Notes in Computer Science",
  volume =       "5495",
  pages =        "243--252",
  address =      "Kuopio, Finland",
  month =        "23-25 " # apr,
  publisher =    "Springer",
  note =         "Revised selected papers",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-642-04920-0",
  DOI =          "doi:10.1007/978-3-642-04921-7_25",
  abstract =     "In this paper we present application of genetic
                 programming (GP) [1] to evolution of indirect encoding
                 of neural network weights. We compare usage of original
                 HyperNEAT algorithm with our implementation, in which
                 we replaced the underlying NEAT with genetic
                 programming. The algorithm was named HyperGP. The
                 evolved neural networks were used as controllers of
                 autonomous mobile agents (robots) in simulation. The
                 agents were trained to drive with maximum average
                 speed. This forces them to learn how to drive on roads
                 and avoid collisions. The genetic programming lacking
                 the NEAT complexification property shows better
                 exploration ability and tends to generate more complex
                 solutions in fewer generations. On the other hand, the
                 basic genetic programming generates quite complex
                 functions for weights generation. Both approaches
                 generate neural controllers with similar abilities.",
  notes =        "ICANNGA 2009",
}

Genetic Programming entries for Zdenek Buk Jan Koutni Miroslav Snorek

Citations