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.
Cite
CITATION STYLE
Medsker, C., & Song, I. Y. (1993). ProloGA: A Prolog implementation of a genetic algorithm. In Proceedings - IEEE International Conference on Developing and Managing Intelligent System Projects, DMISP 1993 (pp. 77–84). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/DMISP.1993.248633
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