Title :
Genetic logic programming
Author :
Osborn, T.R. ; Charif, Adib ; Lamas, Ricardo ; Dubossarsky, Eugene
Author_Institution :
Sch. of Comput. Sci., Univ. of Technol., Sydney, NSW, Australia
fDate :
29 Nov-1 Dec 1995
Abstract :
Genetic logic programming (GLP) is a new method which applies the genetic algorithm paradigm to declarative programming-specifically to evolve populations of Prolog programs. This paper examines GLP applied to natural language understanding to illustrate the power, issues and limitations of GLP. Populations of Prolog query interpreters evolve to respond more correctly to queries about Aesop´s fable “The Fox and the Crow”. The interpreters process parsed text and consult a general knowledge-base. The gene pool consists of a large set of Prolog rules and facts which are tentatively proposed as being `useful´ for interpretation. Essentially, interpreters act as an interface between queries, knowledge bases and the text. Closure and termination are addressed at the level of design of the gene pool, and various Prolog options. Fitness amounts to a score on a high-school-like “comprehension test”, with special care needed to deal with redundant and dependent answers, and with an eye to rewarding correct higher-level abstractions
Keywords :
PROLOG; deductive databases; genetic algorithms; grammars; knowledge based systems; logic programming; natural languages; program interpreters; query processing; redundancy; Aesop´s fable; Prolog program population evolution; Prolog query interpreters; Prolog rules; The Fox and the Crow; closure; comprehension test; declarative programming; dependent answers; facts; fitness; gene pool design; genetic algorithms; genetic logic programming; higher-level abstractions; interpretation; knowledge base consultation; natural language understanding; parsed text; redundant answers; termination; Australia; Educational institutions; Genetic algorithms; Genetic programming; Humans; Logic programming; Natural languages; Pattern matching; Testing; Vehicles;
Conference_Titel :
Evolutionary Computation, 1995., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2759-4
DOI :
10.1109/ICEC.1995.487475