Epigenetic Programming: an Approach of Embedding Epigenetic Learning via Modification of Histones in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Tanev:2003:CEC,
  author =       "Ivan Tanev and Kikuo Yuta",
  title =        "Epigenetic Programming: an Approach of Embedding
                 Epigenetic Learning via Modification of Histones in
                 Genetic Programming",
  booktitle =    "Proceedings of the 2003 Congress on Evolutionary
                 Computation CEC2003",
  year =         "2003",
  editor =       "Ruhul Sarker and Robert Reynolds and 
                 Hussein Abbass and Kay Chen Tan and Bob McKay and Daryl Essam and 
                 Tom Gedeon",
  pages =        "2580--2587",
  publisher =    "IEEE Press",
  address =      "Canberra",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  month =        "8-12 " # dec,
  organisation = "IEEE Neural Network Council (NNC), Engineers Australia
                 (IEAust), Evolutionary Programming Society (EPS),
                 Institution of Electrical Engineers (IEE)",
  keywords =     "genetic algorithms, genetic programming, epgenesis,
                 histone code, Biological control systems, Biological
                 system modelling, Cells (biology), DNA, Evolution
                 (biology), Gene expression, Plastics, Robustness,
                 Stability, DNA, biology computing, 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",
  ISBN =         "0-7803-7804-0",
  DOI =          "doi:10.1109/CEC.2003.1299413",
  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 behaviour 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.",
  notes =        "CEC 2003 - A joint meeting of the IEEE, the IEAust,
                 the EPS, and the IEE.",
}

Genetic Programming entries for Ivan T Tanev Kikuo Yuta

Citations