Shortcomings with Tree-Structured Edge Encodings for Neural Networks

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Hornby:SwT:gecco2004,
  author =       "Gregory S. Hornby",
  title =        "Shortcomings with Tree-Structured Edge Encodings for
                 Neural Networks",
  booktitle =    "Genetic and Evolutionary Computation -- GECCO-2004,
                 Part II",
  year =         "2004",
  editor =       "Kalyanmoy Deb and Riccardo Poli and 
                 Wolfgang Banzhaf and Hans-Georg Beyer and Edmund Burke and 
                 Paul Darwen and Dipankar Dasgupta and Dario Floreano and 
                 James Foster and Mark Harman and Owen Holland and 
                 Pier Luca Lanzi and Lee Spector and Andrea Tettamanzi and 
                 Dirk Thierens and Andy Tyrrell",
  series =       "Lecture Notes in Computer Science",
  pages =        "495--506",
  address =      "Seattle, WA, USA",
  publisher_address = "Heidelberg",
  month =        "26-30 " # jun,
  organisation = "ISGEC",
  publisher =    "Springer-Verlag",
  volume =       "3103",
  ISBN =         "3-540-22343-6",
  ISSN =         "0302-9743",
  DOI =          "doi:10.1007/b98645",
  URL =          "http://ic.arc.nasa.gov/people/hornby/papers/hornby_gecco04.ps",
  size =         "12 pages",
  keywords =     "genetic algorithms, genetic programming, neural
                 networks, graphs, representation",
  abstract =     "In evolutionary algorithms a common method for
                 encoding neural networks is to use a tree-structured
                 assembly procedure for constructing them. Since node
                 operators have difficulties in specifying edge weights
                 and these operators are execution-order dependent, an
                 alternative is to use edge operators. Here we identify
                 three problems with edge operators: in the
                 initialisation phase most randomly created genotypes
                 produce an incorrect number of inputs and outputs;
                 variation operators can easily change the number of
                 input/output (I/O) units; and units have a connectivity
                 bias based on their order of creation. Instead of
                 creating I/O nodes as part of the construction process
                 we propose using parameterised operators to connect to
                 pre-existing I/O units. Results from experiments show
                 that these parameterized operators greatly improve the
                 probability of creating and maintaining networks with
                 the correct number of I/O units, remove the
                 connectivity bias with I/O units and produce better
                 controllers for a goal-scoring task.",
  notes =        "GECCO-2004 A joint meeting of the thirteenth
                 international conference on genetic algorithms
                 (ICGA-2004) and the ninth annual genetic programming
                 conference (GP-2004)

                 football",
}

Genetic Programming entries for Gregory S Hornby

Citations