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Thomas S. Ray: An approach to the synthesys of life

Thomas S. Ray: An approach to the synthesys of life. presenting: Ady Ecker. Contents. Introduction Tierra system description Mac-tierra Results Discussion. Introduction. Introduction. Exploration of life in general is limited

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Thomas S. Ray: An approach to the synthesys of life

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  1. Thomas S. Ray: An approach to the synthesys of life presenting: Ady Ecker

  2. Contents • Introduction • Tierra system description • Mac-tierra • Results • Discussion

  3. Introduction

  4. Introduction • Exploration of life in general is limited • Tierra is an artificial life model to explore the origin of diversity

  5. What Is Life? • “I would consider a system to be living if it is • Self-replicating and • Capable of open-ended evolution • Synthetic life should self replicate, and evolve structures or processes that were not designed in or preconceived by the creator.”

  6. Tierra sytem description

  7. The Tierra Simulator • Virtual parallel computer • Cellularity: each program gets its own memory and CPU time. Each cell can read and execute every instruction but has write permission to its own or its daughter cell • The operating system executes the code of each cell in the computer’s memory

  8. operating system fetch - decode - execute main memory daughter cell instruction codes cells

  9. The Language • Special machine language to be portable and secure • Small instruction set (32 instructions, operands included), that is less fragile when the code is mutated • Jumps: addressing by templates

  10. The Operating System • The slicer: processor time sharing mechanism • Control time for large/small creatures • The reaper: kills cells when the memory is full from the top of a queue • The creature starts at the bottom of the queue • It moves up the queue when it fails to execute instructions (because its algorithm is flawed), and stays where it is, or moves down when it succeeds • The genebank saves information about each genome

  11. Mutation • Cosmic mutations cause the flipping of random bits in the soup at a low frequency • Copy errors result in replication errors • Flaws can occur during execution. The result is off by 1 at some low frequency • Creatures activity scramble the soup

  12. The Digital Environment: Self-replicating computer programs (colored geometric objects) occupy the RAM memory of the computer (orange background). Mutations (lightning) cause random changes in the code. Death (the skull) eliminates old or defective programs.

  13. Natural life Tierra Energy CPU time Territory Memory Abiotic environment Operating system Amino acids Assembler instructions Genome Program

  14. The ancestor • The simulation start with one simple self replicating ancestor - 80 instructions. • This ancestor evolve communities of interacting “living” creatures, due to mutations.

  15. Ancestor’s Genome 01 (nop_1) 01 (nop_1) 01 (nop_1) 01 (nop_1) 04 (zero) 02 (or1) 03 (shl) 03 (shl) 18 (mov_cd) 1c (adrb) 00 (nop_0) 00 (nop_0) 00 (nop_0) 00 (nop_0) 07 (sub_ac) 19 (mov_ab) 1d (adrf) 00 (nop_0) 00 (nop_0) 00 (nop_0) 01 (nop_1) 08 (inc_a) 06 (sub_ab) 01 (nop_1) 01 (nop_1) 00 (nop_0) 01 (nop_1) 1e (mal) 16 (call) 00 (nop_0) 00 (nop_0) 01 (nop_1) 01 (nop_1) 1f (divide) 14 (jmp) 00 (nop_0) 00 (nop_0) 01 (nop_1) 00 (nop_0) 05 (if_cz) 01 (nop_1) 01 (nop_1) 00 (nop_0) 00 (nop_0) 0c (push_ax) 0d (push_bx) 0e (push_cx) 01 (nop_1) 00 (nop_0) 01 (nop_1) 00 (nop_0) 1a (mov_iab) 0a (dec_c) 05 (if_cz) 14 (jmp) 00 (nop_0) 01 (nop_1) 00 (nop_0) 00 (nop_0) 08 (inc_a) 09 (inc_b) 14 (jmp) 00 (nop_0) 01 (nop_1) 00 (nop_0) 01 (nop_1) 05 (if_cz) 01 (nop_1) 00 (nop_0) 01 (nop_1) 01 (nop_1) 12 (pop_cx) 11 (pop_bx) 10 (pop_ax) 17 (ret) 01 (nop_1) 01 (nop_1) 01 (nop_1) 00 (nop_0) 05 (if_cz)

  16. Ancestor 1111 1100 self exam find 0000 [start] bx find 0001 [end]  ax calculate size  cx copy procedure Save registers to stack 1010 move |bx|  |ax| decrement cx if cx==0 jump 0100 increment ax & bx 1101 jump 0101 reproduction loop Allocate daughter  ax 1011 call 0011 (copy procedure) restore registers cell division return 1110 jump 0010

  17. The Ancestral Program - consists of three “genes” (green solid objects). The CPU (green sphere) is executing code in the first gene, which causes the program to measure itself.

  18. Mac Tierra

  19. Results

  20. The Parasite • Uses the ancestor’s copy procedure to copy himself • The host is not affected by the parasite • Superior competitor • 45 instructions • Population cycles

  21. 1111 Ancestor & parasite self exam find 0000 [start] bx find 0001 [end]  ax calculate size  cx 1111 self exam find 0000 [start] bx find 0001 [end]  ax calculate size  cx 1101 reproduction loop Allocate daughter  ax call 0011 (copy procedure) cell division jump 0010 1100 copy procedure Save registers to stack 1101 reproduction loop Allocate daughter  ax 1010 move |bx|  |ax| decrement cx call 0011 (copy procedure) if cx==0 jump 0100 increment ax & bx cell division jump 0101 jump 0010 1011 restore registers return 1110 1110

  22. A Parasite (blue, two piece object) uses its CPU (blue sphere) to execute the code in the third gene of a neighboring host organism (green) to replicate itself, producing daughter parasite (two-piece wire frame object).

  23. The Hyper-Parasite • Robust self-replicate program by itself • When a parasite tries to use the hyper-parasite, the hyper-parasite cause the parasite to replicate the hyper-parasite • Drive the parasites to extinction

  24. Hyper-parasite 1100 1111 copy procedure 1101 self exam find 0000 [start] bx find 0001 [end]  ax calculate size  cx 1010 reproduction loop Allocate daughter  ax move |bx|  |ax| decrement cx if cx==0 jump 1100 call 0011 increment ax & bx cell division jump 0101 jump 0000 1110 parasite 1101 reproduction loop Allocate daughter  ax 1111 self exam find 0000 [start] bx find 0001 [end]  ax calculate size  cx call 0011 (copy procedure) cell division jump 0010 1110

  25. A Hyper-parasite (red, three piece object) steals the CPU from a parasite (blue sphere). Using the stolen CPU, and its own CPU (red sphere) it is able to produce two daughters (wire frame objects on left and right) simultaneously.

  26. Symbionts • Manually created • One contains the self-exam and copy procedure • The other contains the self-exam and reproduction loop • 46 and 64 instructions

  27. symbionts 1111 1111 self exam find 0000 [start] bx find 0001 [end]  ax calculate size  cx jump 0010 self exam find 0000 [start] bx find 0001 [end]  ax calculate size  cx jump 0010 1100 copy procedure Save registers to stack 1010 1101 reproduction loop Allocate daughter  ax move |bx|  |ax| decrement cx call 0011 (copy procedure) if cx==0 jump 0100 cell division increment ax & bx jump 0010 jump 0101 1110 1011 restore registers return 1110

  28. Social Hyper-Parasites • Appear when there is genetic uniformity • Cooperate with the previous social hyper-parasite cell • 61 instructions • Jumping templates of size 3

  29. Cheaters: Hyper Hyper Parasites • Invade the social system • Position themselves between aggregating hyper parasites to capture the instruction pointer • 27 instructions

  30. Experiments (Simulations) Hosts, red, are very common. Parasites, yellow, have appeared but are still rare.

  31. Hosts, are now rare because parasites have become very common. Immune hosts, blue, have appeared but are rare.

  32. Immune hosts are increasing in frequency, separating the parasites into the top of memory.

  33. Immune hosts now dominate memory, while parasites and susceptible hosts decline in frequency. The parasites will soon be driven to extinction.

  34. Experiments (Simulations) • Changing parameters: • Mutation rate • Selection for small/large cells • Exploring the ecology in controlled environment • Run two competing cells without mutation • Run a fixed population of cells • Micro/macro scales

  35. Discussion

  36. Emergence • Cariani defined emergence relative to the expected model as the state when the model no longer describes the system • Emergence types: • Syntactic • Semantic • Pragmatic

  37. AL and Biology Theory AL experimental study test biological theories suggest the model suggest the factors Biology

  38. Biological Factors of Diversity • Adaptation to biologic evolving environment vs. To physical environment • Emergent fitness function • Size, shape, distribution, fragmentation, heterogeneity

  39. Possible Extensions • Predators • Multi-cellular organs • Introducing energy costs • Separating genotype from phenotype

  40. Summary • A framework for synthesis of life was presented • Natural-like behavior was detected in the system • This system opens the way for inter-disciplinary future research

  41. Resources • The Tierra homepage - Thomas Ray www.hip.atr.co.jp/~ray/tierra/tierra.html • Mac Tierra - Simon Fraser www.santfe.edu/~smfr/mactierra.html • Core life - Erik de Neve www.xs4all.nl/~alife/corelife.htm

  42. The END

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