HFC: A Continuing EA Framework for Scalable Evolutionary Synthesis
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{Jianjun-Hu:2003:AAAI,
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author = "Jianjun Hu and Erik D. Goodman and Kisung Seo and
Zhun Fan and Ronald C. Rosenberg",
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title = "{HFC:} A Continuing {EA} Framework for Scalable
Evolutionary Synthesis",
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booktitle = "Proceedings of the 2003 {AAAI} Spring Symposium -
Computational Synthesis: From Basic Building Blocks to
High Level Functionality",
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year = "2003",
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pages = "106--113",
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address = "Stanford, California",
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publisher_address = "445 Burgess Drive. Menlo park, CA, 94025, USA",
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publisher = "AAAI press",
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month = "24" # Mar,
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organisation = "AAAI",
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email = "hujianju@msu.edu, goodman@egr.msu.edu",
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keywords = "genetic algorithms, genetic programming, scalability,
sustainability, HFC",
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URL = "http://www-rcf.usc.edu/~jianjunh/paper/stanford_hfc.pdf",
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abstract = "The scalability of evolutionary synthesis is impeded
by its characteristic discrete landscape with high
multimodality. It is also impaired by the convergent
nature of conventional EAs. A generic framework, called
Hierarchical Fair Competition (HFC), is proposed for
formulation of continuing evolutionary algorithms. This
framework features a hierarchical organisation of
individuals by different fitness levels. By maintaining
repositories of intermediate-fitness individuals and
ensuring a continuous supply of raw genetic material
into an environment in which it can be exploited, HFC
is able to transform the convergent nature of current
EAs into a sustainable evolutionary search framework.
It is also well suited for the special demands of
scalable evolutionary synthesis. An analog circuit
synthesis problem, the eigenvalue placement problem, is
used as an illustrative case study.",
- }
Genetic Programming entries for
Jianjun Hu
Erik Goodman
Kisung Seo
Zhun Fan
Ronald C Rosenberg
Citations