Title :
Epigenetic programming: an approach of embedding epigenetic learning via modification of histones in genetic programming
Author :
Tanev, Ivan ; Yuta, Kikuo
Author_Institution :
ATR Human Inf. Sci. Labs., Kyoto, Japan
Abstract :
Extending the notion of inheritable genotype in genetic programming (GP) from the common model of DNA into chromatin (DNA and histones), we propose epigenetic programming as an approach, embedding an explicitly controlled gene expression via modification of histones in GP. We propose double cell representation of the simulated individuals, comprising somatic cell and germ cell, both represented by their respective chromatin structures. Following biologically plausible concepts, we regard the plastic phenotype of the somatic cell, achieved via controlled gene expression owing to modifications to histones (epigenetic learning, EL) as relevant for fitness evaluation, while the genotype of the germ cell - to the phylogenesis of the individuals. The approach is verified on evolution of social behavior of team of predator agents in predator-prey pursuit problem. The empirically obtained performance evaluation results indicate that EL contributes to more than 2-fold improvement of computational effort of the phylogenesis via GP. We view the cause for that in the cumulative effect of polyphenism and epigenetic stability. The former allows for phenotypic diversity of genotypically similar individuals, while the latter robustly preserves the individuals from the destructive effects of crossover by silencing of certain genotypic combinations and explicitly activating them only when they are most likely to be expressed in corresponding beneficial phenotypic traits.
Keywords :
DNA; biology computing; genetic algorithms; molecular biophysics; predator-prey systems; software agents; statistical analysis; DNA; chromatin structures; double cell representation; epigenetic learning; epigenetic programming; genotypic combinations; germ cell; histone modification; phylogenesis; predator-prey pursuit problem; somatic cell; Biological control systems; Biological system modeling; Cells (biology); DNA; Evolution (biology); Gene expression; Genetic programming; Plastics; Robustness; Stability;
Conference_Titel :
Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
Print_ISBN :
0-7803-7804-0
DOI :
10.1109/CEC.2003.1299413