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The 2005 IEEE International Conference on Neural Networks and Brain ICNN&B'05 Special Session 1 (Workshop) Artificial Life

[IEEE 2005 International Conference on Neural Networks and Brain - Beijing, China (13-15 Oct. 2005)] 2005 International Conference on Neural Networks and Brain - Reproduction Mechanism

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Page 1: [IEEE 2005 International Conference on Neural Networks and Brain - Beijing, China (13-15 Oct. 2005)] 2005 International Conference on Neural Networks and Brain - Reproduction Mechanism

The 2005 IEEE International Conference on Neural Networks and Brain

ICNN&B'05

Special Session 1(Workshop)

Artificial Life

Page 2: [IEEE 2005 International Conference on Neural Networks and Brain - Beijing, China (13-15 Oct. 2005)] 2005 International Conference on Neural Networks and Brain - Reproduction Mechanism

Reproduction Mechanism of Digital lifeAi Dongmei

School ofApplied ScienceUniversity of science and technology Beijing

Beijing [email protected]

Abstract-Digital life, the creation and study of man-made systems that exhibits characteristics of life, offers amethod of investigation into essent`al properties of life.Digital life system SEBRED, which extends upon previoussystem avida, was designed to help in investigations into thesexual reproduction. The sexual reproduction mechanism ofdigital life is designed by utilizing the genetic programmingprinciple in this paper, the cross breeding mechanism ofnatural life is introduced into digital life, and the crossbreeding mechanism of digital life is designed, so as to avoidthe disadvantage of inbreeding reproduction and improve thelife feature of digital life.

I. INTRODUCTION

Digital life research platform is a system usingcomputer as tool and medium, utilizing software to emulatelife features [1]. Tierra, developed by Thomas S. Ray, is therepresentative of this field. He introduced the concept oforganism evolution in biology into computer science [2][3].Every cell in computer multiplies, mutates, and evolves.They all keep to survival of the fittest in Charles Darwin'sEvolutionism and fight for the resource in computer. Theseso-called cells characterized by life features are in factprograms. Therefore these cells are also called digital life.Afterwards, inspired by the ideas in Tierra, some otherdigital life research platforms are developed [4], amongwhich Avida is the most influential one.

In Avida system [5], digital life is asexual reproductive.They self-replicate and mutate in the process ofreproduction so as to form life with different genes. Theykeep to survival of the fittest; fight for the memory and theresource of CPU in the same environment. But whetheramong animals or plants in nature, sexual reproduction isthe most common way. Biologically, asexual reproduction isa primitive reproduction. Sexual reproduction, on the otherhand, synthesizes both the advantages and disadvantagesfrom both parents, so that it could partly conceal thehereditary defects. Compared to the life produced byasexual reproduction, life from sexual reproduction is moreadaptable and has stronger vitality [6]. Based on sexualreproductive, digital life system SEBRED is developed. Itbrings sexual reproduction and cross breeding mechanismThe paper is supported by NSFC(No:60374032,60375038)

Ban Xiaojuan,Yin Yixin,Tu XuyanSchool of Information Engineering

University of science and technology BeijingBeijing 100083

into digital life. This digital life research platform aims atimproving the fitness of populations, and further improvingthe life features of digital life in the digital life system. Thesexual reproduction mechanism of digital life and the crossbreeding mechanism of digital life in SEBRED aredescribed in this paper.

II The GENETIC OPERATE DESIGN OF DIGITAL LIFE INSEBRED

There are various multiply methods to raise up seed innature life. Primitive monad usually raises up seed byasexual reproduction. But, most of plants and animals andhuman beings raises up seed by sexual reproduction. Insexual reproduction, the creature individual is divided intomale and female. The offspring reproduced by sexualreproduction have more mutations. The offspring fromsexual reproduction become more fit the environment thanthose offspring from asexual reproduction. In naturalselection, sexual reproduction is beneficial mutations and fitenvironment.

As the calculating model of biological evolution,genetic algorithm considers natural selection, crossover andmutation as the models of transmitting and handling geneticinformation. This highly ideal model may probably discoverthe essential feature of the natural evolution system. Sogenetic algorithm is one of the basic theories which study ondigital life.

A The Reproduction Model ofPrimitive Digital Lifein SEBRED

In SEBRED, digital life is divided into primitive digitallife and advanced digital life. First of all, an ancestor ofdigital life begins to self-replicate and many offspring comeinto being. In the process of reproduction, the mutations ofgene result in the different genes of the offspring. Theoffspring also reproduce a large number of offspring as theirancestors do. Of course different digital life has differentfitness that even changes in different periods. Those digitallives with strong fitness reproduce more offspring, and thosewith low fitness reproduce less.

In the reproduction process of these primitive digitallives, improved genetic algorithm is used. In this process

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digital life has experienced three evolutionalmodels-digitally set fitness and natural selection, mutation,and self-replicate. These lives have experienced 100generations, so their fitness has improved; their life structurebecomes more complicated compared to their ancestors.This is the evolutional process of primitive digital life. Weregard this biological species as the preliminary species ofadvanced digital life, and those lives after 100 generationsas the advanced digital life. Biologic experiments turn out inbiology that sexual cross is not beneficial to simple life butbeneficial to the complicated life developed from simplelife. Digital lives before the I00t generation have neverexperienced sexual reproduction (cross or exchange), sothey have the same way of reproduction as in Avida. But thedifference is that in SEBRED, although lives before 100Igeneration have no sexual reproduction, when each lifecomes into being, its sex property randomly has two sexdivisions-female and male.

B The Sexual Reproduction Algorithm of AdvancedDigital Life Based on Genetic Programming

In SEBRED, after running 100 generations, there willbe 3600 organisms. They have very different genotypes andchromosomes, so the programs (or lives) length are alsodifferent. In this system, the hereditary individuals have twosex divisions: female and male. That is to say some sexuallives have come into being at random in this system. Afterthe 100 generations, the reproduction mechanism hasbecome sexual reproduction. So in SEBRED, theintercrossed digital lives have different sizes (programs withdifferent length). Moreover, during the process of evolution,program (life) will change it's size according to theenvironment [7]. But the string with set length whichfrequently used by genetic algorithm to illustrate questionshas restrained the application of genetic algorithm.The major disadvantages ofgenetic algorithm are:1) Incapable of describing the hiberarchy questions;2) Incapable of describing the computer programs.

Because genetic algorithm can only change the form ofstring through evolution and heredity, but cannot formthe hiberarchy computer program;

3) Lacking of dynamic changeability. String with setlength of genetic algorithm has no dynamicchangeability, so once the length of string is set, it isvery hard to dynamically express the change of thestate or the behavior. Restrained the express ofquestion.So the copulation mechanism of digital life in

SEBRED adopts genetic programming to make two livesexchange. The predominant feature of genetic programmingis to adopt hiberarchy structure to express questions. This issimilar to computer program, which describes questions insubsections. This generalized computer program is able toautomatically change its structure and size according to thestate of environment. Genetic programming has three kinds

of structures [8]: the dendriform structure, the linear structureand the retiform structure, among which the linear structureexpresses the hiberarchy structure of genetic programmingwith catenulate fonn. The linear structure of geneticprogramming usually enforces direction one item by anotherfrom top to bottom. Only when it receives direction likeremove or jump, does it depart from this kind of order. Sothe linear structure is more flexible while performingprogram directions.

In SEBRED, the advanced digital life structure adoptslinear structure. Every digital life performs the program ofits own chromosome during the process of evolution. Whentwo digital lives copulate, the length of their chromosomesis different. With the evolution of the species, the length ofdigital life' chromosomes will change. The following part isabout the principles and methods of digital life' copulation.A)Principle ofAdvanced Digital Life' Sexual Mating(1 ) . Life with same sex cannot mate up; the female

individual can only mate up with the male individualrandomly.(2) . Each individual mates up with the individual

around with opposite sex. If two or more qualifiedindividuals participate in the copulation, the individualshould choose the one with the highest fitness. But if theyeven have the same fitness, the individual should choose theyounger one.B)The Exchanging Method Based on the Linear

Structure ofGenetic Programming(1) According to the previous selection principle, two

paternal individuals are selected at random. In Figure. 1, thepaternal individuals are on the left, and letters Fl, F2,Ml, M2, ...are symbolizing different directions.

(2) Randomly choose one section of directions inpaternal individuals as exchanging part. In Figure.l, thedark panes represent the exchanging part.

(3) Exchange paternal individual and generate twofilial individuals as the individuals on the right of the

Father

Fl4|F2

F5tF6F7F8::

Mother

MlM2M3M4

Offspring

FlF2

Offspring

M2 |M3|M4

F6_F7 M7F8 M8

M91MlJ

Figure. 1

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Page 4: [IEEE 2005 International Conference on Neural Networks and Brain - Beijing, China (13-15 Oct. 2005)] 2005 International Conference on Neural Networks and Brain - Reproduction Mechanism

Fig. 1. The Mating Operation ofAdvanced Digital Life'

C) The Improved Mating MethodExchange is the main arithmetic operator of generating

new individuals in genetic programming and the mainmotivity to promote the evolution of species. However,exchange has positive effect on evolution, but meanwhile italso has negative effect. In SEBRED, the copulation ofsexual digital life improves some life' fitness as well asreduces other life' fitness. The destroying effect as exchangehas, it is still the main motivity to push the geneticprogramming to develop in a positive way. In SEBRED, theimproved exchanging method is adopted. This method is tomate up the male and female individuals at random, andafter many times of copulation, there will be many filialindividuals. Then choose two best ones as the filialindividuals and add them into the environment, and this issitting combination.

The specific operating steps are:(1) In the species group, the male individual randomly

choose the female individual;(2) The male and female individuals have 4 times of

copulation, and generate 8 filial individuals;(3) Choose the best two individuals from the eight as the

new filial individuals, add them into the environmentand abandon the other six. In Figure.2, lozengerepresents male individual and trianglerepresents female individual.

|four-time copulations|

Produce eight filial° A n individuals

g\ + Select two individualswith the strongest fitness

Figure.2. Choose the filial generation with strong fitness

m THE CROSS BREEDING MECHANISM OF DIGITAL LIFE INSEBRED

Sexual reproduction is the common way of biologicalreproduction and its manifestation is the copulation amongindividuals. Copulation can be divided into many typesaccording to the individuals' consanguinity and hereditarybuildup. But the basic types are inbreeding and cross

breeding. Inbreeding is harmful to offspring, while crossbreeding has its heterosis [9]*

In every natural population, many diploidicindividuals' genomes keep high proportion ofheterozygosity. The hereditary diversities usually arerecessive instead of dominant, so it is beneficial to thesurvival of the species and makes it more adaptable to theenvironment. Just like the biological system of nature,inbreeding also produces bad offspring. Therefore theprogram ofjudging the qualifications of both parents is veryessential to the selection process [10]

In SEBRED, the digital life involving the sexualcopulation have to be compared. Tracing back 4 generationsof each side, if they have the same father or mother in thefour generations, then this copulation has to be abandonedand select other mating objects once again. But if theselection fails more than 10 times, select another digital lifearound this pair with force and conduct the copulation, asshown in Figure.3.

I

Figure.3 Four-Generation Pedigree

IV CONCLUSIONS

This thesis is based on the digital life platform Avida;using genetic algorithm and genetic programming prnciples,combining the sexual reproduction of advanced life inbiology, builds up the sexual reproduction mechanism ofdigital life; enriches and improves the life features of digitallife. Experiments turn out that the fitness of digital life aftersexual reproduction is higher than that of asexualreproduction.

REFERENCES

[1] Chen HongJuan.: The Research of Theory and Method onSelf-Reproduction of Digital Fish. The Doctorial Thesis of USTB,2002

[2] Wu Jianbing,Yang Jie,Wu Yuehua.: Digital Life and DigitalIntelligence. Pattern Recognition and Digital Intelligence (1998)274-279

[3] Ray,T.S.: An evolutionary approach to synthetic biology: Zen and theart of creating life. In Digital Life Journal, The MIT Press (1994)179-209

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[4] A.N.Pargellis.In: Digital Life Behavior in the Amoebaworld.ArtificalLife MY .Cambridge, MA:MIT Press (2001) 63-75

[5] Adami,C.: Introduction to Digital Life. Springer, New York (1998)[6] Liu Zudong: Genetics. The Higher Education Press (1990)[7] Wang zhengzhi, Bo Tao.: Evolutionary Computation. Changsha:

National University ofDefense Technology Press (2000)[8] Yun Qingxia.: Evolutionary Algorithm. Metallurgical Industry Press

(2000)[9] Yang Yehua.: Common Genetics. Beijing: Higher Education Press

(1999)[10] Lin Yuan,He Lin,Xu JinLin.: Sex Evolution. Origin and

Maintenance. Life Science (2002) 197-200

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