Introducing Graphical Models to Analyze Genetic Programming Dynamics
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Hemberg:2013:foga,
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author = "Erik Hemberg and Kalyan Veeramachaneni and
Constantin Berzan and Una-May O'Reilly",
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title = "Introducing Graphical Models to Analyze Genetic
Programming Dynamics",
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booktitle = "Foundations of Genetic Algorithms",
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year = "2013",
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editor = "Frank Neumann and Kenneth {De Jong}",
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pages = "75--86",
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address = "Adelaide, Australia",
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month = "16-20 " # jan,
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organisation = "SigEvo",
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publisher = "ACM",
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keywords = "genetic algorithms, genetic programming, Bayesian
networks, graphical models",
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isbn13 = "978-1-4503-1990-4",
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URL = "http://doi.acm.org/10.1145/2460239.2460247",
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DOI = "doi:10.1145/2460239.2460247",
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acmid = "2460247",
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size = "12 pages",
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abstract = "We propose graphical models as a new means of
understanding genetic programming dynamics. Herein, we
describe how to build an unbiased graphical model from
a population of genetic programming trees. Graphical
models both express information about the conditional
dependency relations among a set of random variables
and they support probabilistic inference regarding the
likelihood of a random variable's outcome. We focus on
the former information: by their structure, graphical
models reveal structural dependencies between the nodes
of genetic programming trees. We identify graphical
model properties of potential interest in this regard -
edge quantity and dependency among nodes expressed in
terms of family relations. Using a simple symbolic
regression problem we generate a graphical model of the
population each generation. Then we interpret the
graphical models with respect to conventional knowledge
about the influence of subtree crossover and mutation
upon tree structure.",
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notes = "Also known as \cite{Hemberg:2013:IGM:2460239.2460247}
http://www.sigevo.org/foga-2013/index.html",
- }
Genetic Programming entries for
Erik Hemberg
Kalyan Veeramachaneni
Constantin Berzan
Una-May O'Reilly
Citations