Semantic Building Blocks in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  title =        "Semantic Building Blocks in Genetic Programming",
  author =       "Nicholas Freitag McPhee and Brian Ohs and 
                 Tyler Hutchison",
  bibdate =      "2008-04-15",
  bibsource =    "DBLP,
  booktitle =    "Proceedings of the 11th European Conference on Genetic
                 Programming, EuroGP 2008",
  address =      "Naples",
  month =        "26-28 " # mar,
  publisher =    "Springer",
  year =         "2008",
  volume =       "4971",
  editor =       "Michael O'Neill and Leonardo Vanneschi and 
                 Steven Gustafson and Anna Isabel {Esparcia Alcazar} and 
                 Ivanoe {De Falco} and Antonio {Della Cioppa} and 
                 Ernesto Tarantino",
  isbn13 =       "978-3-540-78670-2",
  pages =        "134--145",
  series =       "Lecture Notes in Computer Science",
  DOI =          "doi:10.1007/978-3-540-78671-9_12",
  size =         "12 pages",
  abstract =     "We present a new mechanism for studying the impact of
                 subtree crossover in terms of semantic building blocks.
                 This approach allows us to completely and compactly
                 describe the semantic action of crossover, and provide
                 insight into what does (or doesn't) make crossover
                 effective. Our results make it clear that a very high
                 proportion of crossover events (typically over
                 75percent in our experiments) are guaranteed to perform
                 no immediately useful search in the semantic space. Our
                 findings also indicate a strong correlation between
                 lack of progress and high proportions of fixed
                 contexts. These results then suggest several new,
                 theoretically grounded, research areas.",
  keywords =     "genetic algorithms, genetic programming",
  notes =        "Table 3: Function set Binary AND, OR, NAND, and NOR.
                 Terminal set x0,x1, . . . ,xn-1, where n is the number
                 of variables. Initialisation PTC2
                 \cite{luke:2000:2ftcaGP}, with equal proportions of
                 sizes 50, 70, and 100 nodes and maximum initial depth
                 of 10 Number of generations 500. Tournament size 2. XO
                 Probability 1. XO bias away from leaves None (all nodes
                 are equally likely). Maximum size after XO 500 (If the
                 resulting child is too large, then new parents are
                 chosen independently and process begins again.). See
                 also \cite{mcphee:2007:wps32}.

                 Part of \cite{conf/eurogp/2008} EuroGP'2008 held in
                 conjunction with EvoCOP2008, EvoBIO2008 and

Genetic Programming entries for Nicholas Freitag McPhee Brian Ohs Tyler Hutchison