DocumentCode :
412591
Title :
Chemical genetic algorithms - coevolutionary genotype-phenotype mapping by modelling of metabolism in cell
Author :
Sawai, Hidefumi ; Suzuki, Hideaki
Author_Institution :
Commun. Res. Lab., Kobe, Japan
Volume :
1
fYear :
2003
fDate :
8-12 Dec. 2003
Firstpage :
639
Abstract :
A chemical genetic algorithm (CGA) in which several types of molecules (information units) react with each other in a cell is proposed. Translation from codons (short substrings of bits) in DNA to amino acids (real value units) is specified by a particular set of translation molecules created by the reaction between RNA units and amino acid units. This adaptively changes and optimizes the fundamental genotype-phenotype mapping during evolution. Through the struggle between cells containing a DNA unit and a small molecular units, the codes in DNA and the translation table described by the small molecular coevolve, and a specific output function (protein), which is used to evaluate the cells´ fitness, is optimized. To demonstrate the effectiveness of the CGA, the algorithm is applied to a set of deceptive problems and the Shekel´s foxholes problem with epistasis, and the results by using the CGA are compared to those by using a simple GA. It is shown that the CGA becomes a powerful strategy for optimizing functions that are hard to solve with the conventional GA.
Keywords :
DNA; biology computing; genetic algorithms; genetics; physiological models; proteins; DNA; RNA units; Shekel foxholes problem; amino acid; amino acids; cells fitness; chemical genetic algorithms; codons; coevolutionary mapping; deceptive problems; epistasis; functions optimization; genotype-phenotype mapping; information units; metabolism modelling; translation molecules; Amino acids; Biochemistry; Biological cells; Biological information theory; Chemicals; DNA; Evolution (biology); Genetic algorithms; Organisms; Proteins;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
Print_ISBN :
0-7803-7804-0
Type :
conf
DOI :
10.1109/CEC.2003.1299636
Filename :
1299636
Link To Document :
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