1.1 Biological Background

1.1 Biological Background

발표자 : 김정집

Evolutionary Algorithms in Theory and Practice

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

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->riboso

mes 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 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 somatic generative

usual deviations gene mutations chromosome mutations genome mutations

gene , genome mutations

gene 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 subs

tances, 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

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

Summary of experiments coexistent evolution according to the principle of D

arwiniam selection Hypercyclic system stabilized. Hypercuclic selection optimizes the system. Only o

ne universal genetic code is produced The first biological cells emerge Darwiniam evolution leads to the development of t

he known variety of species

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

more approximated form