Learning Programs in Different Paradigms using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{wong:1995:lpdpGP,
  author =       "Man Leung Wong and Kwong Sak Leung",
  title =        "Learning Programs in Different Paradigms using Genetic
                 Programming",
  booktitle =    "Proceedings of the Fourth Congress of the Italian
                 Association for Artificial Intelligence",
  year =         "1995",
  publisher_address = "Berlin, Germany",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://cptra.ln.edu.hk/~mlwong/conference/aiia1995.pdf",
  abstract =     "Genetic Programming (GP) is a method of automatically
                 inducing programs by representing them as parse trees.
                 In theory, programs in any computer languages can be
                 translated to parse trees. Hence, GP should be able to
                 handle them as well. In practice, the syntax of Lisp is
                 so simple and uniform that the translation process can
                 be achieved easily, programs evolved by GP are usually
                 expressed in Lisp. This paper presents a flexible
                 framework that programs in various programming
                 languages can be acquired. This framework is based on a
                 formalism of logic grammars. To implement the
                 framework, a system called LOGENPRO (The LOgic grammar
                 based GENetic PROgramming system) has been developed.
                 An experiment that employs LOGENPRO to induce a
                 S-expression for calculating dot product has been
                 performed. This experiment illustrates that LOGENPRO,
                 when used with knowledge of data types, accelerates the
                 learning of programs. Other experiments have been done
                 to illustrate the ability of LOGENPRO in inducing
                 programs in difference programming languages including
                 Prolog and C. These experiments prove that LOGENPRO is
                 very flexible.",
}

Genetic Programming entries for Man Leung Wong Kwong-Sak Leung

Citations