Towards Automated Strategies in Satisfiability Modulo Theory
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- @InProceedings{GalvezRamirez:2016:EuroGP,
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author = "Nicolas {Galvez Ramirez} and Youssef Hamadi and
Eric Monfroy and Frederic Saubion",
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title = "Towards Automated Strategies in Satisfiability Modulo
Theory",
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booktitle = "EuroGP 2016: Proceedings of the 19th European
Conference on Genetic Programming",
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year = "2016",
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month = "30 " # mar # "--1 " # apr,
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editor = "Malcolm I. Heywood and James McDermott and
Mauro Castelli and Ernesto Costa and Kevin Sim",
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series = "LNCS",
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volume = "9594",
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publisher = "Springer Verlag",
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address = "Porto, Portugal",
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pages = "230--245",
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organisation = "EvoStar",
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keywords = "genetic algorithms, genetic programming, genetic
improvement, SBSE, hyper heuristic, SMT, Strategy, Z3,
Learning algorithm",
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isbn13 = "978-3-319-30668-1",
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DOI = "doi:10.1007/978-3-319-30668-1_15",
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size = "16 pages",
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abstract = "SMT solvers include many heuristic components in order
to ease the theorem proving process for different
logics and problems. Handling these heuristics is a
non-trivial task requiring specific knowledge of many
theories that even a SMT solver developer may be
unaware of. This is the first barrier to break in order
to allow end-users to control heuristics aspects of any
SMT solver and to successfully build a strategy for
their own purposes. We present a first attempt for
generating an automatic selection of heuristics in
order to improve SMT solver efficiency and to allow
end-users to take better advantage of solvers when
unknown problems are faced. Evidence of improvement is
shown and the basis for future works with evolutionary
and/or learning-based algorithms are raised.",
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notes = "Part of \cite{Heywood:2016:GP} EuroGP'2016 held in
conjunction with EvoCOP2016, EvoMusArt2016 and
EvoApplications2016",
- }
Genetic Programming entries for
Nicolas Galvez Ramirez
Youssef Hamadi
Eric Monfroy
Frederic Saubion
Citations