Title :
Grammatical evolution
Author :
O´Neill, Michael ; Ryan, Conor
Author_Institution :
Dept. of Comput. Sci. & Inf. Syst., Limerick Univ., Ireland
fDate :
8/1/2001 12:00:00 AM
Abstract :
We present grammatical evolution, an evolutionary algorithm that can evolve complete programs in an arbitrary language using a variable-length binary string. The binary genome determines which production rules in a Backus-Naur form grammar definition are used in a genotype-to-phenotype mapping process to a program. We demonstrate how expressions and programs of arbitrary complexity may be evolved and compare its performance to genetic programming
Keywords :
automatic programming; computational complexity; genetic algorithms; grammars; neural nets; Backus-Naur form; automatic programming; binary genome; complexity; degenerate code; evolutionary algorithm; grammatical evolution; neural networks; variable-length binary string; Bioinformatics; Biological information theory; Evolution (biology); Evolutionary computation; Genetic mutations; Genetic programming; Genomics; Law; Legal factors; Production;
Journal_Title :
Evolutionary Computation, IEEE Transactions on
DOI :
10.1109/4235.942529
