1.1 Biological Background Evolutionary Algorithms in Theory and Practice 1.1 Biological Background 발표자 : 김정집

1.Organic Evolution and Problem Solving interdisciplinary research field biology, artificial intelligence, numerical optimization, and decision support organic evolution collective learning process within a population of individuals individual a search point container of current knowledge about the “laws” of the environment fitness value, recombination, mutation, and selection

Different Mainstreams three different Mainstreams Evolution Strategies (ESs) Genetic Algorithms (GAs) Evolutionary Programming(EP) Index sec 1.1 biological background sec 1.2 impact on AI, and ML sec 1.3 a global optimization algorithm as random search algorithm sec 1.4 overview of the history of Eas

1.1 Biological Background Darwinian theory of evolution(Charles Darwin) natural selection mutation on phentypes -> selection under limited environmental conditions -> advantageous organisms survives

Neodarwinism synthetic theory of evolution genes population transfer units of heredity changed by mutations population evolving unit consists of a common gene pool indirect fitness natural selection as no active driving force What is mapping from genotype to phenotype?

Adaptation denotes a general advantage in ecological or physiological efficiency nongenetic-somatic adaptation genetic adaptation “To What” any major kind of environment (adaptive zone) ecological niche ( the set of possible environments that permit survival of a species)

Adaptive surface possible biological trait combinations natural analogy to the optimization problem climbing the hill nearest to the starting point genetic drift random decrease or increase of biological trait frequencies dynamically changing by means of environment-population interactions

Schematic diagram of an adaptive surface

1.1.1 Life and Information Processing DNA: 2strands nucleotide base Adenine(A), Thymine(T), Cytosine(C), Guanine(G) purine base (A or G) pyrimidine base ( T or C)

creates the phenotype from the genotype protein biosynthesis mapping genotype to phenotype polygeny - m:1 pleiotropy - 1:m epistasis alphabet of amino acids : 20 different one mRNA(1 strand):transcription,nucleus->ribosomes tRNA:translation in ribosome

the genetic code

protein biosynthesis

central dogma of molecular genetics DNA->RNA->Protein the proof of the incorrectness of Lamarckism

Hierarchy of the genetic information

1.1.2 Meiotic Heredity mitosis phylogeny(evolution) cell division with identical genetic material phylogeny(evolution) meiotic cell division

Meiosis(I)

Meiosis(II)

crossover position(s) at random in nature, 1~8 points haploid case(*) haploid gameter->diploid zygote->haploid cell recombination and mutaion occur in zygote

one-point crossover

characteristics of meiosis

1.1.3 mutations DNA-replication is overwhelmingly exact but not perfect for a specific gene of the human genome, Pm=6*10-6~8*10-6 by origin normal-in the replication process exogenous factors

classes of mutations by location usual deviations somatic generative gene mutations chromosome mutations genome mutations

gene , genome mutations gene mutations genome mutations small mutations little variation-do not negatively effect large mutations cause phenotype deviations progressive(constructive) mutations cause crossings of boundaries between species genome mutations not been tested as an extension of EAs

chromosome mutations losses of chromosome regions deficiencies and deletions doubling of chromosome regions duplications reorganization of chromosomes translocations and inversions

terminal and internal segment losses

duplication event

inversion event

1.1.4 Molecular Darwinism human genome consists of one billion nucleotide bases 4^1,000,000,000 possibilities random emergence of self-reproducing units can be called impossible explain the efficiency of biological evolution

necessary conditions for Darwinian selection Metabolism Self-reproduction Mutation

Eigen’s equations Eigen’s equations for the dynamical behavior of species : build-up term resulting from self-replication : term incorporating destruction : transition probability from class k to I : growth and shrinking processes of the total number of individuals

Under the assumption of a constant overall organization buffering the concentrations Ai of energy-rich substances, s.t. AiQi=const total size of the system is limited excess productivity excess productivity must be compensated by transportation through the flow

Average excess productivity Eigen’s eq. Can be transferred to where , selective value of a species I

only those species having Wi above E(t) will grow the number shifting E(t) to an optimum representing Maximum selective value of all species

The selection criterion allow growing of a new species m to become the dominant one the quasi-species the currently dominant species together with its stationary distribution of mutants emerging from this species

A maximum length s.t. the information can be preserved by reproduction the ratio of the wild-type(dominant species) reproduction rate to the average reproduction rate of the rest

Eigen’s concept of a hypercycle Experimental results lmax is no longer than hundred nucleotide bases Darwinian selection N=kN In principle, any new species can grow and become the dominant ones. Eigen’s concept of a hypercycle N=kN2 does not allow for diversity of species

Summary of experiments coexistent evolution according to the principle of Darwiniam selection Hypercyclic system stabilized. Hypercuclic selection optimizes the system. Only one universal genetic code is produced The first biological cells emerge Darwiniam evolution leads to the development of the known variety of species

Using a birth and death model, an approximate analytical expression for the dependence of the error threshold more approximated form