Learning Sets of Sub-Models for Spatio-Temporal Prediction

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Bennett:2007:SGAI,
  author =       "Andrew Bennett and Derek Magee",
  title =        "Learning Sets of Sub-Models for Spatio-Temporal
                 Prediction",
  booktitle =    "AI-2007 Twenty-seventh SGAI International Conference
                 on Artificial Intelligence",
  year =         "2007",
  editor =       "Max Bramer and Richard Ellis",
  address =      "Cambridge, UK",
  month =        "10-12 " # dec,
  organisation = "British Computer Society's Specialist Group on
                 Artificial Intelligence (SGAI)",
  keywords =     "genetic algorithms, genetic programming, card game
                 playing",
  URL =          "http://www.bcs-sgai.org/ai2007/admin/papers2.php?f=techpapers",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.150.6694",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/download/10.1.1.150.6694.pdf",
  size =         "14 page",
  abstract =     "In this paper we describe a novel technique which
                 implements a spatio-temporal model as a set of
                 sub-models based on first order logic. These sub-models
                 model different, typically independent, parts of the
                 dataset; for example different spatio or temporal
                 contexts. To decide which sub-models to use in
                 different situations a context chooser is used. By
                 separating the sub-models from where they are applied
                 allows greater flexibility for the overall model. The
                 sub-models are learnt using an evolutionary technique
                 called Genetic Programming. The method has been applied
                 to spatio-temporal data. This includes learning the
                 rules of snap by observation, learning the rules of a
                 traffic light sequence, and finally predicting a
                 person's course through a network of CCTV cameras.",
  notes =        "University of Leeds, UK",
}

Genetic Programming entries for Andrew Bennett Derek Magee

Citations