Reflective Grammatical Evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Christopher Timperley and Susan Stepney",
  title =        "Reflective Grammatical Evolution",
  booktitle =    "Proceedings of the Fourteenth International Conference
                 of the Synthesis and Simulation of Living Systems,
                 ALIFE 14",
  year =         "2014",
  editor =       "Hiroki Sayama and John Rieffel and Sebastian Risi and 
                 Rene Doursat and Hod Lipson",
  series =       "Complex Adaptive Systems",
  pages =        "71--78",
  address =      "New York",
  month =        "30 " # jul # "-2 " # aug,
  organisation = "International Society for Artificial Life",
  publisher =    "MIT Press",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution, reflection, open-ended evolution,
  isbn13 =       "9780262326216 ?",
  URL =          "",
  DOI =          "doi:10.7551/978-0-262-32621-6-ch013",
  size =         "8 pages",
  abstract =     "Our long term goal is to develop an open-ended
                 reflective software architecture to support open-ended
                 evolution. Here we describe a preliminary experiment
                 using reflection to make simple programs evolved via
                 Grammatical Evolution robust to mutations that result
                 in coding errors.

                 We use reflection in the domain of grammatical
                 evolution (GE) to achieve a novel means of robustness
                 by autonomously repairing damaged programs, improving
                 continuity in the search and allowing programs to be
                 evolved effectively using soft grammars. In most
                 implementations of GE, individuals whose programs
                 encounter errors are assigned the worst possible
                 fitness; using the techniques described here, these
                 individuals may be allowed to continue evolving.

                 We describe two different approaches to achieving
                 robustness through reflection, and evaluate their
                 effectiveness through a series of experiments carried
                 out on benchmark regression problems. Results
                 demonstrate a statistically significant improvement on
                 the fitness of the best individual found during
  notes =        "REVAC

                 ALIFE 14

Genetic Programming entries for Christopher Timperley Susan Stepney