Evolving Effective Incremental Solvers for SAT with a Hyper-Heuristic Framework Based on Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InCollection{Bader-El-Den:2008:GPTP,
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author = "Mohamed Bader-El-Den and Riccardo Poli",
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title = "Evolving Effective Incremental Solvers for {SAT} with
a Hyper-Heuristic Framework Based on Genetic
Programming",
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booktitle = "Genetic Programming Theory and Practice {VI}",
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year = "2008",
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editor = "Rick L. Riolo and Terence Soule and Bill Worzel",
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series = "Genetic and Evolutionary Computation",
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chapter = "11",
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pages = "163--179",
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address = "Ann Arbor",
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month = "15-17 " # may,
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming,
hyper-heuristic, HH, Inc, SAT, heuristics",
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isbn13 = "978-0-387-87622-1",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.206.3331.pdf",
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DOI = "doi:10.1007/978-0-387-87623-8_11",
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size = "16 pages",
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abstract = "Hyper-heuristics could simply be defined as heuristics
to choose other heuristics. In other words, they are
methods for combining existing heuristics to generate
new ones. we use a grammar-based genetic programming
hyper-heuristic framework. The framework is used for
evolving effective incremental solvers for SAT. The
evolved heuristics perform very well against well-known
local search heuristics on a variety of benchmark SAT
problems.",
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notes = "part of \cite{Riolo:2008:GPTP} published in 2009.
Also known as \cite{El-den:2008:GPTP}
\cite{Bader-el-den_evolvingeffective}
Department of Computing and Electronic Systems,
University of Essex",
- }
Genetic Programming entries for
Mohamed Bahy Bader-El-Den
Riccardo Poli
Citations