Towards Automated Strategies in Satisfiability Modulo Theory

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@InProceedings{GalvezRamirez:2016:EuroGP,
  author =       "Nicolas {Galvez Ramirez} and Youssef Hamadi and 
                 Eric Monfroy and Frederic Saubion",
  title =        "Towards Automated Strategies in Satisfiability Modulo
                 Theory",
  booktitle =    "EuroGP 2016: Proceedings of the 19th European
                 Conference on Genetic Programming",
  year =         "2016",
  month =        "30 " # mar # "--1 " # apr,
  editor =       "Malcolm I. Heywood and James McDermott and 
                 Mauro Castelli and Ernesto Costa and Kevin Sim",
  series =       "LNCS",
  volume =       "9594",
  publisher =    "Springer Verlag",
  address =      "Porto, Portugal",
  pages =        "230--245",
  organisation = "EvoStar",
  keywords =     "genetic algorithms, genetic programming, SBSE, hyper
                 heuristic, SMT, Strategy, Z3, Learning algorithm",
  isbn13 =       "978-3-319-30668-1",
  DOI =          "doi:10.1007/978-3-319-30668-1_15",
  size =         "16 pages",
  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.",
  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