Learning programs in different paradigms using Genetic Programming

Man Leung WONG, Kwong Sak LEUNG

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

3 Citations (Scopus)


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.
Original languageEnglish
Title of host publicationTopics in Artificial Intelligence. AI*IA 1995. Lecture Notes in Computer Science
EditorsMarco GORI, Giovanni SODA
ISBN (Electronic)9783540474685
ISBN (Print)978354060437
Publication statusPublished - 1995
Externally publishedYes
Event4th Congress of the Italian Association for Artificial Intelligence AI*IA '95 - Florence, Italy
Duration: 11 Jan 199513 Jan 1995

Publication series

NameTopics in Artificial Intelligence
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference4th Congress of the Italian Association for Artificial Intelligence AI*IA '95
OtherThe Italian Association for Artificial Intelligence. Springer-Verlag.


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