Solving Knapsak Problems with Attribute Grammars

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

@InProceedings{oneill:2004:gew:mone,
  author =       "Michael O'Neill and Robert Cleary and Nikola Nikolov",
  title =        "Solving Knapsak Problems with Attribute Grammars",
  editor =       "R. Poli and S. Cagnoni and M. Keijzer and E. Costa and 
                 F. Pereira and G. Raidl and S. C. Upton and 
                 D. Goldberg and H. Lipson and E. {de Jong} and J. Koza and 
                 H. Suzuki and H. Sawai and I. Parmee and M. Pelikan and 
                 K. Sastry and D. Thierens and W. Stolzmann and 
                 P. L. Lanzi and S. W. Wilson and M. O'Neill and C. Ryan and 
                 T. Yu and J. F. Miller and I. Garibay and G. Holifield and 
                 A. S. Wu and T. Riopka and M. M. Meysenburg and 
                 A. W. Wright and N. Richter and J. H. Moore and 
                 M. D. Ritchie and L. Davis and R. Roy and M. Jakiela",
  booktitle =    "GECCO 2004 Workshop Proceedings",
  year =         "2004",
  month =        "26-30 " # jun,
  address =      "Seattle, Washington, USA",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco2004/WGEW003.pdf",
  abstract =     "We present a work in progress describing attribute
                 grammar approaches to Grammatical Evolution, which
                 allow us to encode context-sensitive and semantic
                 information. Performance of the different grammars
                 adopted are directly compared with a more traditional
                 GA representation on five instances of an NP-hard
                 knapsack problem. The results presented are
                 encouraging, demonstrating that Grammatical Evolution
                 in conjunction with alternative grammar representations
                 can provide an improvement over the standard
                 context-free grammar, and allow Grammatical Evolution
                 to drive a constraint based search.",
  notes =        "attributes (information, integers or list) can be
                 assigned to any symbol of the (recursive) grammar and
                 are defined (given meaning) by functions associated
                 with the grammar's productions. Attribute values from
                 child nodes (synthesised) or from parent nodes
                 (inherited). Information (constants) starts from root
                 (eg maxim weight) or leafs (weight of individual
                 items). Conditions (eg if(notinknapsack) and
                 if(usage+item < limit) ) are added to grammar
                 productions plus functions to calculate them (eg
                 limit=limit, usage=usage). Figure 1, page 8. pop=50,
                 gens<=2000.

                 Cited by \cite{Ortega:2007:ieeeTEC}. GECCO-2004WKS
                 Distributed on CD-ROM at GECCO-2004",
}

Genetic Programming entries for Michael O'Neill Robert Cleary Nikola S Nikolov