HFC: A Continuing EA Framework for Scalable Evolutionary Synthesis

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@InProceedings{Jianjun-Hu:2003:AAAI,
  author =       "Jianjun Hu and Erik D. Goodman and Kisung Seo and 
                 Zhun Fan and Ronald C. Rosenberg",
  title =        "{HFC:} A Continuing {EA} Framework for Scalable
                 Evolutionary Synthesis",
  booktitle =    "Proceedings of the 2003 {AAAI} Spring Symposium -
                 Computational Synthesis: From Basic Building Blocks to
                 High Level Functionality",
  year =         "2003",
  pages =        "106--113",
  address =      "Stanford, California",
  publisher_address = "445 Burgess Drive. Menlo park, CA, 94025, USA",
  publisher =    "AAAI press",
  month =        "24" # Mar,
  organisation = "AAAI",
  email =        "hujianju@msu.edu, goodman@egr.msu.edu",
  keywords =     "genetic algorithms, genetic programming, scalability,
                 sustainability, HFC",
  URL =          "http://www-rcf.usc.edu/~jianjunh/paper/stanford_hfc.pdf",
  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