3. Contents Introduction Tierra system description Mac-tierra Results Discussion

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

6. 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.”

8. 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

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

10. 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

11. 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

12. 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

13. 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.

14. Energy Territory Abiotic environment Amino acids Genome Natural life Program Assembler instructions Operating system Memory CPU timeTierra

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

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

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

18. 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.

21. 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

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

23. 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).

24. 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

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

26. 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.

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

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

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

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

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

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

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

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

35. 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

37. 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

38. AL and Biology Theory BiologyBiology ALAL suggest the model suggest the factors experimental study test biological theories experimental study test biological theories

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

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

41. 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

42. 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