Generative Representations for Artificial Architecture and Passive Solar Performance
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{Harrington:2013:CEC,
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article_id = "1561",
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author = "Adrian Harrington and Brian J. Ross",
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title = "Generative Representations for Artificial Architecture
and Passive Solar Performance",
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booktitle = "2013 IEEE Conference on Evolutionary Computation",
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volume = "1",
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year = "2013",
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month = jun # " 20-23",
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editor = "Luis Gerardo {de la Fraga}",
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pages = "537--545",
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address = "Cancun, Mexico",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-1-4799-0453-2",
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DOI = "doi:10.1109/CEC.2013.6557615",
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annote = "The Pennsylvania State University CiteSeerX Archives",
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bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
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language = "en",
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oai = "oai:CiteSeerX.psu:10.1.1.419.3502",
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rights = "Metadata may be used without restrictions as long as
the oai identifier remains attached to it.",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.419.3502",
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URL = "http://www.cosc.brocku.ca/sites/all/files/downloads/research/cs1302.pdf",
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size = "9 pages",
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abstract = "This paper explores how the use of generative
representations influences the quality of solutions in
evolutionary design problems. A genetic programming
system is developed with individuals encoded as
generative representations. Two research goals motivate
this work. One goal is to examine Hornby's features and
measures of modularity, reuse and hierarchy in new and
more complex evolutionary design problems. In
particular, we consider a more difficult problem domain
where the generated 3D models are no longer constrained
by voxels. Experiments are carried out to generate 3D
models which grow towards a set of target points. The
results show that the generative representations with
the three features of modularity, regularity and
hierarchy performed best overall. Although the measures
of these features were largely consistent with those of
Hornby, a few differences were found. Our second
research goal is to use the best performing encoding on
some 3D modeling problems that involve passive solar
performance criteria. Here, the system is challenged
with generating forms that optimize exposure to the
Sun. This is complicated by the fact that a model's
structure can interfere with solar exposure to itself;
for example, protrusions can block Sun exposure to
other model elements. Furthermore, external
environmental factors (geographic location, time of the
day, time of the year, other buildings in the
proximity) may also be relevant. Experimental results
were successful, and the system was shown to scale well
to the architectural problems studied.",
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notes = "also known as \cite{6557615}.
See also technical report CS-13-02 March 2013
cs1302.pdf
CEC 2013 - A joint meeting of the IEEE, the EPS and the
IET.",
- }
Genetic Programming entries for
Adrian Harrington
Brian J Ross
Citations