Finding Semi-Quantitative Physical Models Using Genetic Programming

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

@InProceedings{khoury:2006:UKCI,
  author =       "Mehdi Khoury and Frank Guerin and 
                 George Macleod Coghill",
  title =        "Finding Semi-Quantitative Physical Models Using
                 Genetic Programming",
  booktitle =    "The 6th annual UK Workshop on Computational
                 Intelligence",
  year =         "2006",
  editor =       "Xue Z. Wang and Rui Fa Li",
  pages =        "245--252",
  address =      "Leeds, UK",
  month =        "4-6 " # sep,
  keywords =     "genetic algorithms, genetic programming, fuzzy,
                 qualitative modelling, semi quantitative modelling",
  URL =          "http://www.csd.abdn.ac.uk/~mkhoury/fuzzy%20evolution2.pdf",
  size =         "8 pages",
  abstract =     "Model learning often implies exploring a vast search
                 space of possible hypotheses in the hope of finding a
                 solution. Qualitative model learners are mostly based
                 on Inductive Logic Programming (ILP), which is a
                 systematic method which tends to be well fitted for
                 exploring solutions in a narrow search space. We
                 present a semi-quantitative model learner that uses
                 Genetic Programming (GP), which is well suited for
                 exploring a broad search space. We learn simple
                 physical systems based on a formalism involving both
                 crisp numbers and fuzzy quantity spaces. We use the ECJ
                 framework,1 and the fitness of a model is set to be
                 optimal when it covers all positive examples. Several
                 experiments are performed to learn and reuse models of
                 physical systems of increasing complexity; firstly a
                 u-tube, then coupled tanks, and finally cascading
                 tanks. Results show that the system can approximate the
                 target models in reasonably good conditions, and that
                 there is still scope for optimisation.",
}

Genetic Programming entries for Mehdi Khoury Frank Guerin George M Coghill

Citations