Sensitive ants are sensible ants

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@InProceedings{Karim:2012:GECCO,
  author =       "Muhammad Rezaul Karim and Conor Ryan",
  title =        "Sensitive ants are sensible ants",
  booktitle =    "GECCO '12: Proceedings of the fourteenth international
                 conference on Genetic and evolutionary computation
                 conference",
  year =         "2012",
  editor =       "Terry Soule and Anne Auger and Jason Moore and 
                 David Pelta and Christine Solnon and Mike Preuss and 
                 Alan Dorin and Yew-Soon Ong and Christian Blum and 
                 Dario Landa Silva and Frank Neumann and Tina Yu and 
                 Aniko Ekart and Will Browne and Tim Kovacs and 
                 Man-Leung Wong and Clara Pizzuti and Jon Rowe and Tobias Friedrich and 
                 Giovanni Squillero and Nicolas Bredeche and 
                 Stephen L. Smith and Alison Motsinger-Reif and Jose Lozano and 
                 Martin Pelikan and Silja Meyer-Nienberg and 
                 Christian Igel and Greg Hornby and Rene Doursat and 
                 Steve Gustafson and Gustavo Olague and Shin Yoo and 
                 John Clark and Gabriela Ochoa and Gisele Pappa and 
                 Fernando Lobo and Daniel Tauritz and Jurgen Branke and 
                 Kalyanmoy Deb",
  isbn13 =       "978-1-4503-1177-9",
  pages =        "775--782",
  keywords =     "genetic algorithms, genetic programming, Grammatical
                 Evolution",
  month =        "7-11 " # jul,
  organisation = "SIGEVO",
  address =      "Philadelphia, Pennsylvania, USA",
  DOI =          "doi:10.1145/2330163.2330271",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "This paper introduces an approach to evolving computer
                 programs using an Attribute Grammar (AG) extension of
                 Grammatical Evolution (GE) to eliminate ineffective
                 pieces of code with the help of context-sensitive
                 information.

                 The standard Context-Free Grammars (CFGs) used in GE,
                 Genetic Programming (GP) (which uses a special type of
                 CFG with just a single non-terminal) and most other
                 grammar-based system are not well-suited for codifying
                 information about context. AGs, on the other hand, are
                 grammars that contain functional units that can help
                 determine context which, as this paper demonstrates, is
                 key to removing ineffective code.

                 The results presented in this paper indicate that, on a
                 selection of grammars, the prevention of the appearance
                 of ineffective code through the use of context analysis
                 significantly improves the performance of and
                 resistance to code bloat over both standard GE and GP
                 for both Santa Fe Trail (SFT) and Los Altos Hills (LAH)
                 trail version of the ant problem with same amount of
                 energy used.",
  notes =        "Also known as \cite{2330271} GECCO-2012 A joint
                 meeting of the twenty first international conference on
                 genetic algorithms (ICGA-2012) and the seventeenth
                 annual genetic programming conference (GP-2012)",
}

Genetic Programming entries for Muhammad Rezaul Karim Conor Ryan

Citations