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Computer Science Dept, San Jose State University, CA Self Reproducing CA’s and Programs Shruti Parihar May 06, 2003

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Page 1: Computer Science Dept, San Jose State University, CA Self Reproducing CA’s and Programs Shruti Parihar May 06, 2003

Computer Science Dept, San Jose State University, CA

Self Reproducing CA’s and Programs

Self Reproducing CA’s and Programs

Shruti Parihar

May 06, 2003

Page 2: Computer Science Dept, San Jose State University, CA Self Reproducing CA’s and Programs Shruti Parihar May 06, 2003

AgendaAgendaAgendaAgenda

Introduction to ALife

Father of ALife – John von Neumann

Significance of Neumann’s Discovery

Langton’s Contributions Loops Concept of Death Cell-Lab demo of Langton’s Loops

Viruses : Self Replicating Programs

Conclusions

Page 3: Computer Science Dept, San Jose State University, CA Self Reproducing CA’s and Programs Shruti Parihar May 06, 2003

Introduction to ALifeIntroduction to ALifeIntroduction to ALifeIntroduction to ALife

What is Alife? Extracting mechanics of evolution Understanding “Rules of life”

Significant work done John von Neumann Chris Langton Others

Page 4: Computer Science Dept, San Jose State University, CA Self Reproducing CA’s and Programs Shruti Parihar May 06, 2003

Father of ALife – John von Father of ALife – John von NeumannNeumannFather of ALife – John von Father of ALife – John von NeumannNeumann

Assumptions Computation universality Construction universality

Characteristics 29 states, 2D Cellular automata Environment of infinite resources Self Reproduction into identical copy Input tape with data and instructions Evolution explained as well

Significance – precursor to DNA discovery

Neumann’s AutomataNeumann’s Automata

Page 5: Computer Science Dept, San Jose State University, CA Self Reproducing CA’s and Programs Shruti Parihar May 06, 2003

Father of ALife – John von Father of ALife – John von NeumannNeumannFather of ALife – John von Father of ALife – John von NeumannNeumann

Neumann’s UTMNeumann’s UTM

Page 6: Computer Science Dept, San Jose State University, CA Self Reproducing CA’s and Programs Shruti Parihar May 06, 2003

Contributions of Chris LangtonContributions of Chris LangtonContributions of Chris LangtonContributions of Chris Langton

Assumptions Computation universality not required

Characteristics 8 states, 2D Cellular automata Needed CA grid of 100 cells Self Reproduction into identical copy Input tape with data and instructions Concept of Death

Significance – Could be modeled through computer programs

LoopsLoops

Page 7: Computer Science Dept, San Jose State University, CA Self Reproducing CA’s and Programs Shruti Parihar May 06, 2003

Contributions of Chris LangtonContributions of Chris LangtonContributions of Chris LangtonContributions of Chris Langton

Langton’s LoopLangton’s Loop

0 – Background cell state 3, 5, 6 – Phases of reproduction

1 – Core cell state 4 – Turning arm left by 90 degrees

2 – Sheath cell state state

7 – Arm extending forward cell state

Page 8: Computer Science Dept, San Jose State University, CA Self Reproducing CA’s and Programs Shruti Parihar May 06, 2003

Contributions of Chris LangtonContributions of Chris LangtonContributions of Chris LangtonContributions of Chris Langton

Loop ReproductionLoop Reproduction

Page 9: Computer Science Dept, San Jose State University, CA Self Reproducing CA’s and Programs Shruti Parihar May 06, 2003

Contributions of Chris LangtonContributions of Chris LangtonContributions of Chris LangtonContributions of Chris Langton

Loop DeathLoop Death

Page 10: Computer Science Dept, San Jose State University, CA Self Reproducing CA’s and Programs Shruti Parihar May 06, 2003

Other ContributionsOther ContributionsOther ContributionsOther Contributions

Dyson Resource utilization of self-replicators

Holland Invented Genetic Algorithms (GA) in 1973 Tried to imitate mechanics of evolution by applying genetic

operators

E.F. Codd Simplified Neumann’s automata by reducing number of

states to 8 Automaton required 100 million cells

John Devore Simplified Codd’s automata to occupy 94, 794 cells

Page 11: Computer Science Dept, San Jose State University, CA Self Reproducing CA’s and Programs Shruti Parihar May 06, 2003

Viruses: Self Replicating ProgramsViruses: Self Replicating ProgramsViruses: Self Replicating ProgramsViruses: Self Replicating Programs

Virus is Latin for Poison

Computer virus vs Biological virus Both viruses attack a larger host entity Host entity turns into a factory reproducing more viruses Spread to other hosts

John Inglis defines “virus” as a piece of code with two characteristics At least a partially automated capability to reproduce A method of transfer which is dependent on its ability to

attach itself to other computer entities like programs, disk sectors etc

Page 12: Computer Science Dept, San Jose State University, CA Self Reproducing CA’s and Programs Shruti Parihar May 06, 2003

Viruses: A form of Artificial Life?Viruses: A form of Artificial Life?Viruses: A form of Artificial Life?Viruses: A form of Artificial Life?

Life is a pattern of events in time and space Virus algorithms are a pattern in time Electric and magnetic pulses in space

Self Reproduction Replication in viruses in host entity

Metabolism - converting matter from environment to energy Consumption of electric energy of computer system for

sustenance Metabolism by virus or computer? Metabolism in other Self Replicating Systems

Page 13: Computer Science Dept, San Jose State University, CA Self Reproducing CA’s and Programs Shruti Parihar May 06, 2003

Viruses: A form of Artificial Life?Viruses: A form of Artificial Life?Viruses: A form of Artificial Life?Viruses: A form of Artificial Life?

Information storage representing the living organism DNA strands in living organisms Data and instructions on input tape (Neumann and Langton) Viruses use themselves as data

Ability to grow and evolve Darwin’s Evolution Theory Evolution in Viruses?

Stability under environmental perturbations Living organisms survive harsh weather, natural calamities Viruses “adapt” to changes in host system Attribute stability to virus or programmer?

Page 14: Computer Science Dept, San Jose State University, CA Self Reproducing CA’s and Programs Shruti Parihar May 06, 2003

Conclusions and Future ScopeConclusions and Future ScopeConclusions and Future ScopeConclusions and Future Scope

Neumann’s theories of Self reproduction lay foundations

Langton’s contributed by materializing the automata theory through programs allowing for experimentation and improvement

Viruses are self replicating programs which don’t quite qualify as a form of artificial life

Future of Self Replicating systems holds promise NASA proposes Lunar factories Self reproducing robots are not too far ahead

Page 15: Computer Science Dept, San Jose State University, CA Self Reproducing CA’s and Programs Shruti Parihar May 06, 2003

Questions?Questions?Questions?Questions?