Grammar-guided evolutionary automatic system for autonomously building biological oscillators

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@InProceedings{Font:2010:cec,
  author =       "Jose M. Font and Daniel Manrique",
  title =        "Grammar-guided evolutionary automatic system for
                 autonomously building biological oscillators",
  booktitle =    "IEEE Congress on Evolutionary Computation (CEC 2010)",
  year =         "2010",
  address =      "Barcelona, Spain",
  month =        "18-23 " # jul,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-1-4244-6910-9",
  abstract =     "This paper presents a grammar-guided evolutionary
                 automatic system (GGEAS) that is capable of
                 autonomously building special-purpose problem-solving
                 programs. GGEAS uses a grammar-guided genetic
                 programming (GGGP) core that generates solutions to a
                 given problem from scratch, evolving them via
                 selection, crossover and replacement to obtain the
                 near-optimal solution to that problem. The GGGP core
                 solves the closure problem and avoids code bloat. This
                 core only outputs valid solutions and is able to freely
                 determine their size and architecture. GGEAS is
                 supplemented by three external modules that can be
                 configured for any application domain: context-free
                 grammar (CFG) generator, semantic checker and fitness
                 module. The context-free grammar (CFG) generator
                 creates the context-free grammar used by the GGEAS core
                 to formalise the problem constraints. The semantic
                 checker ensures the validity of the solutions created.
                 Finally, the fitness module directs the population
                 evolution towards an optimal solution to the problem.
                 In order to test the effectiveness and the scope of the
                 system, GGEAS has been applied to generate oscillatory
                 biological programs codified in the BlenX language. The
                 results show that GGEAS is effective at creating
                 biological oscillators in silico from scratch without
                 any prior knowledge about the solution and under a
                 range of environmental conditions.",
  DOI =          "doi:10.1109/CEC.2010.5586377",
  notes =        "WCCI 2010. Also known as \cite{5586377}",
}

Genetic Programming entries for Jose M Font Daniel Manrique Gamo

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