Learning Sets of Sub-Models for Spatio-Temporal Prediction
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @InProceedings{Bennett:2007:SGAI,
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author = "Andrew Bennett and Derek Magee",
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title = "Learning Sets of Sub-Models for Spatio-Temporal
Prediction",
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booktitle = "AI-2007 Twenty-seventh SGAI International Conference
on Artificial Intelligence",
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year = "2007",
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editor = "Max Bramer and Richard Ellis",
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address = "Cambridge, UK",
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month = "10-12 " # dec,
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organisation = "British Computer Society's Specialist Group on
Artificial Intelligence (SGAI)",
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keywords = "genetic algorithms, genetic programming, card game
playing",
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URL = "http://www.bcs-sgai.org/ai2007/admin/papers2.php?f=techpapers",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.150.6694",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/download/10.1.1.150.6694.pdf",
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size = "14 page",
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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