Evolving Digital Circuits Using Complex Building Blocks

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@InProceedings{Bremner:2010:ICES,
  author =       "Paul Bremner and Mohammad Samie and 
                 Gabriel Dragffy and Tony Pipe and James Alfred Walker and 
                 Andy M. Tyrrell",
  title =        "Evolving Digital Circuits Using Complex Building
                 Blocks",
  booktitle =    "Proceedings of the 9th International Conference
                 Evolvable Systems: From Biology to Hardware, ICES
                 2010",
  year =         "2010",
  editor =       "Gianluca Tempesti and Andy M. Tyrrell and 
                 Julian F. Miller",
  series =       "Lecture Notes in Computer Science",
  volume =       "6274",
  pages =        "37--48",
  address =      "York",
  month =        sep # " 6-8",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-642-15322-8",
  doi =          "doi:10.1007/978-3-642-15323-5_4",
  size =         "12 pages",
  abstract =     "This work is a study of the viability of using complex
                 building blocks (termed molecules) within the
                 evolutionary computation paradigm of CGP; extending it
                 to MolCGP. Increasing the complexity of the building
                 blocks increases the design space that is to be
                 explored to find a solution; thus, experiments were
                 undertaken to find out whether this change affects the
                 optimum parameter settings required. It was observed
                 that the same degree of neutrality and (greedy) 1+4
                 evolution strategy gave optimum performance. The
                 Computational Effort used to solve a series of
                 benchmark problems was calculated, and compared with
                 that used for the standard implementation of CGP.
                 Significantly less Computational Effort was exerted by
                 MolCGP in 3 out of 4 of the benchmark problems tested.
                 Additionally, one of the evolved solutions to the 2-bit
                 multiplier problem was examined, and it was observed
                 that functionality present in the molecules, was
                 exploited by evolution in a way that would be highly
                 unlikely if using standard design techniques.",
  affiliation =  "Bristol Robotics Laboratory, University of the West of
                 England, Bristol, BS16 1QY",
}

Genetic Programming entries for Paul Bremner Mohammad Samie Gabriel Dragffy Anthony Pipe James Alfred Walker Andrew M Tyrrell