DocumentCode :
1021382
Title :
Context-Dependent DNA Coding With Redundancy and Introns
Author :
Xiao, Peng ; Vadakkepat, Prahlad ; Lee, Tong Heng
Author_Institution :
Huazhong Univ. of Sci. & Technol., Wuhan
Volume :
38
Issue :
2
fYear :
2008
fDate :
4/1/2008 12:00:00 AM
Firstpage :
331
Lastpage :
341
Abstract :
Deoxyribonucleic acid (DNA) coding methods determine the meaning of a certain character in individual chromosomes by the characters surrounding it. The meaning of each character is context dependent, not position dependent. Although position-dependent coding is most commonly used in genetic algorithms (GAs), a context-dependent coding formation is in fact more closer to the natural DNA chromosome. With the context dependency, the DNA coding methods allow intron parts, redundancy, and variable string length in encoded strings while remaining compatible with the standard genetic operations. This paper tries to explicitly explore the influence of those special features of the DNA coding scheme. Two fundamental DNA coding methods (with and without the use of introns) are constructed and compared with the integer coding method, which lacks the features of interest. The performance of the proposed DNA coding methods is analyzed through the robot soccer role assignment problem. The context-dependent coding exhibits the advantages in handling the negative effect of epistasis. The redundancy and intron parts are helpful in preventing useful schemata from disruption and in increasing the population diversity. The variable length of the individual string enables GAs to evolve both the size and the structure of the fuzzy rule base.
Keywords :
evolutionary computation; redundancy; context-dependent DNA coding; deoxyribonucleic acid coding; genetic algorithms; introns; position-dependent coding; redundancy; Behavior-based architecture; deoxyribonucleic acid (DNA) coding; fuzzy control; genetic algorithm (GA); robotic soccer; Algorithms; Base Sequence; Evolution, Molecular; Genetic Code; Introns; Molecular Sequence Data; Pattern Recognition, Automated; Repetitive Sequences, Nucleic Acid; Sequence Analysis, DNA; Variation (Genetics);
fLanguage :
English
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
1083-4419
Type :
jour
DOI :
10.1109/TSMCB.2007.912741
Filename :
4410450
Link To Document :
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