• DocumentCode
    3392632
  • Title

    ProloGA: a Prolog implementation of a genetic algorithm

  • Author

    Medsker, Carl ; Song, Yeol, II

  • Author_Institution
    Coll. of Inf. Studies, Drexel Univ., Philadelphia, PA, USA
  • fYear
    1993
  • fDate
    29-31 Mar 1993
  • Firstpage
    77
  • Lastpage
    84
  • Abstract
    This paper describes ProloGA, a Prolog implementation of a genetic algorithm. Chromosomes and associated parameters were stored in a Prolog database. The genetic operators of crossover, mutation, and population fitness were encoded in Prolog clauses. The test application demonstrated the feasibility of developing genetic algorithms in Prolog. The advantages of Prolog over conventional languages include database functionality, built-in `don´t care´ operator, compact, declarative code, and use of heuristic knowledge. It is suggested that genetic algorithms may enhance Prolog applications by adding flexibility and adaptive rule discovery to the heuristic knowledge approach of Prolog. The combination may prove to be synergistic when applied to combinatorially large, complex, fuzzy problems
  • Keywords
    PROLOG; cellular biophysics; expert systems; genetic algorithms; ProloGA; Prolog database; Prolog implementation; adaptive rule discovery; cellular biophysics; chromosomes; crossover; database functionality; declarative code; fuzzy problems; genetic algorithm; heuristic knowledge; mutation; population fitness; Biological cells; Computer networks; Databases; Encoding; Expert systems; Genetic algorithms; Genetic mutations; Humans; Neural networks; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Developing and Managing Intelligent System Projects, 1993., IEEE International Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    0-8186-3730-7
  • Type

    conf

  • DOI
    10.1109/DMISP.1993.248633
  • Filename
    248633