Learning Sets of Sub-Models for Spatio-Temporal Prediction

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@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