Abstract
A genetic algorithm is developed to find an optimal solution in a large search space using selection, crossover, and mutation. Some researchers have studied techniques for analysis of evolution process in genetic algorithm. In most cases, they were applied to only simple problem or they used schema theorem and numerical statistics to examine the process. These techniques are mostly developed because tracing schemas and interpreting semantics of the schemas require much effort and time. In this paper, we propose modular encoding of gene, which is used to facilitate the interpretation of the gene, identification of important parts of genetic code using evolutionary activity statistics, and analysis of the schemas. Also, we show the feasibility of the proposed method by tracing the evolution process of fuzzy robot controller.
| Original language | English |
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| Title of host publication | 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 |
| DOIs | |
| Publication status | Published - 2010 Dec 1 |
| Event | 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 - Barcelona, Spain Duration: 2010 Jul 18 → 2010 Jul 23 |
Publication series
| Name | 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 |
|---|
Other
| Other | 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 |
|---|---|
| Country | Spain |
| City | Barcelona |
| Period | 10/7/18 → 10/7/23 |
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All Science Journal Classification (ASJC) codes
- Computational Theory and Mathematics
- Applied Mathematics
Cite this
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Analysis of evolutionary process using evolutionary activity and modular schema analysis. / Lee, Young Seol; Cho, Sung Bae.
2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010. 2010. 5585996 (2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Analysis of evolutionary process using evolutionary activity and modular schema analysis
AU - Lee, Young Seol
AU - Cho, Sung Bae
PY - 2010/12/1
Y1 - 2010/12/1
N2 - A genetic algorithm is developed to find an optimal solution in a large search space using selection, crossover, and mutation. Some researchers have studied techniques for analysis of evolution process in genetic algorithm. In most cases, they were applied to only simple problem or they used schema theorem and numerical statistics to examine the process. These techniques are mostly developed because tracing schemas and interpreting semantics of the schemas require much effort and time. In this paper, we propose modular encoding of gene, which is used to facilitate the interpretation of the gene, identification of important parts of genetic code using evolutionary activity statistics, and analysis of the schemas. Also, we show the feasibility of the proposed method by tracing the evolution process of fuzzy robot controller.
AB - A genetic algorithm is developed to find an optimal solution in a large search space using selection, crossover, and mutation. Some researchers have studied techniques for analysis of evolution process in genetic algorithm. In most cases, they were applied to only simple problem or they used schema theorem and numerical statistics to examine the process. These techniques are mostly developed because tracing schemas and interpreting semantics of the schemas require much effort and time. In this paper, we propose modular encoding of gene, which is used to facilitate the interpretation of the gene, identification of important parts of genetic code using evolutionary activity statistics, and analysis of the schemas. Also, we show the feasibility of the proposed method by tracing the evolution process of fuzzy robot controller.
UR - http://www.scopus.com/inward/record.url?scp=79959455148&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79959455148&partnerID=8YFLogxK
U2 - 10.1109/CEC.2010.5585996
DO - 10.1109/CEC.2010.5585996
M3 - Conference contribution
AN - SCOPUS:79959455148
SN - 9781424469109
T3 - 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
BT - 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
ER -