Introduction to Natural Computation. Lecture 19. Artificial Life. Alberto Moraglio

Transcription

1 Introduction to Natural Computation Lecture 19 Artificial Life Alberto Moraglio

2 Part I Introduction to Artificial Life

3 What is life? The physiologicaldefinition centres on certain functions performed by organisms, such as breathing, moving, etc. The metabolicdefinition centres on the exchange of materials between the organism and its surroundings. The biochemicalapproach defines living systems by their capability to store hereditary information in nucleic acids. The evolutionarydefinition focuses on the process of evolution as the central defining characteristic of living systems.

4 Definition of Artificial Life Artificial Life (A-life)is the study of man-made systems that exhibit behaviors characteristic of natural living systems (Langton) Why Artificial Life? Biology is restricted to study a specific instance of life, life on Earth: all life forms we know are carbonbased. A more universal understanding of life: are the essential ingredients of living organisms independent from the underlying material they are made of? A-life is the study of life-as-it-could-be

5 Non-carbon-based media Wetware: synthetic self-reproducing chemical systems, etc. Hardware: some autonomous robots Software: electronic life forms living in a computer s memory

6 Empirical-Analytical vs. Synthetic Traditional Biology: start with a whole organism, deconstruct it into its component parts (for example organs, tissues, cells, genes, molecules, and so on), and then try to derive its fundamental principles. Artificial Life: reverse engineer life and synthesise real organisms, cookbook style, from their basic ingredients.

7 Artificial Life: Challenges How does life arise from the non-living? What is the cause of the richness of living forms? How do complex living forms arise? How do intelligent living forms emerge? How do sociality and language arise?

8 Emergence The appearance of macroscopic patterns, properties, or behaviors that are not simply the sum of the microscopicproperties or behaviors of the components A-life embraces emergence: start with a system of locally interacting elements according to simple rules that spontaneously give rise to emergent properties

9 A-Life vsartificial Intelligence Both seem to approach similar problems, but Artificial Life Concept : Late 1980s Grounded in Biology, Physics, Chemistry, Mathematics. Studies Intelligence as part of Life itself Bottom-Up approach - study synthesis Artificial Intelligence Concept : 1960s Pursued primarily in Comp. Sci, Engineering & Psychology. Studies Intelligent behavior in isolation Top-Down approach - focus is on results

10 A-Life : Current research areas Cellular Automata Neural Networks Evolutionary Algorithms Origin, Self-organization, Repair and Replication Evolutionary / Adaptive Dynamics Autonomous, Adaptive and Evolving Robots Software Agents Emergent Collective Behaviors, Swarms. Synthetic/Artificial Chemistry/Biology/Materials Applications: Finance, Economics, Gaming, MEMS etc Mathematical, Philosophical, Biological foundations, Social and Ethical implications of A-Life

11 Weak vs. Strong A-Life Weak A-life: which claims that simulations of evolving systems may help us understand biological life, is relatively uncontroversial, especially when the simulations relate closely to natural systems. Strong A-life: which claims that replicating programs inside computers really are alive, is far more controversial. This is partly because the examples of biological life we are all familiar with are orders of magnitude more complex and partly because the claimed similarities with biological evolution tend to be rather abstract.

12 Part II An Approach to the Synthesis of Life

13 They are both alive! Tom Ray Tierra

14 Artificial vs. Natural Does a car run? Yes, but not like a horse Does an airplane fly? Yes, but not like a bird Does a submarine swim? Yes, but not like a fish Can a computer play chess? Yes, but not like a human Can software be alive? Yes, but not like a living being!?

15 Working definition of 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 Synthetic life should self replicate, and evolve structures or processes that were not designed in or preconceived by the creator.

16 Evolution in a Nutshell Ingredients of evolution: Self-replication (inheritance) Errors in the copy (variation) Competition for limited resources (selection) Outcome of evolution: adaptation to the environment Co-evolution: environment changes continuously as it is made up of evolving (changing) organisms

17 Are evolutionary algorithms alive? EAs are not open-ended. They are designed to solve a given problem. Each genome has a predefined set of genes and each a predefined set of alleles. Mutation, recombination, replication and selection are designed and fixed. The genome does not contain the mechanism for its own replication, it is copied by the control program. Selection criteria are pre-determined (externally imposed artificial selection), the organisms are not free to invent their fitness function (natural selection).

18 Are self-rep cellular automata alive? Chris Langton's cellular automaton ' loops ' is self-replicating. Beginning from a single organism, the loops form a colony. As the loops on the outer fringes reproduce, the inner loops --blocked by their daughters --can no longer produce offspring. This self-organizing behaviour emerges spontaneously, from the bottom up --a key characteristic of artificial life. This is like growth in crystals. It is not alive because of the lack of variation and evolution.

19 Are computer viruses alive? Evolution of Computer Viruses: 1. Simple 2. Self-recognition 3. Stealth 4. Armoured 5. Polymorphic Viruses replicate inside computers (inheritance), their natural enemies are antivirus programs that eradicate them (natural selection). In response to the introduction of more sophisticated antivirus programs, virus programmers modify their creations (variation by the action of the programmer, not by random mutation) to overcome them using more sophisticated tricks. Then the antivirus is updated. This is an evolutionary arm-race that created whole families of viruses adapted to harm your computers in a varieties of ways!

20 Are Core Warriors alive? In Core War players write programs in Redcode, the assembly language of themars virtual computer. The aim of the game is to survive while causing all opponents to terminate. There are three basic strategies: 1. programs spawn off new copies in the hope at least one survives. 2. programs search for opponents and attempt to disable them. 3. programs drops instructions at random hoping to hit the opponent. There is an annual international tournament, only the strongest programs survive. Every year new stronger programs are created. Evolution with Human in the loop: every year new improved versions of programs compete for survival. The variation mechanism is not random mutation but the programmer ingenuity (i.e., directed change).

21 Redcode

22 Core World Aim: emergence of self-replicating programs from a primordial soup of instructions to study how life could emerge from the non-living. It uses a virtual computer and the Redcode language Self-rep programs can be easily written in Redcode Variation: the MOV command, which copy instructions from a place to another, is flawed with some probability Outcomes: Self-rep programs could emerge BUT they soon die out as they cannot withstand a noisy environment (a single error can be fatal) Interesting dynamics emerged BUT evolution never started off Identified problem: brittlenessof Redcodelanguage under mutation

23 Tierra Aim: emergence of a spontaneous open-ended evolutionary process that gives rise to the richness of life from a simple self-replicating ancestor. It uses a virtual computer with a language robustto mutations with features inspired by biological mechanisms. Variation is injected in the system by intentional flaws in the instructions and by random changes in memory. Memory space and CPU time are scarce resources programs need to replicate themselves. Only those programs that are better at getting these resources survive and reproduce (competition and natural selection). The others die. Outcome: new adapted programs continually emerge able at getting resources to self-replicate more effectively than previously adapted programs. Evolutionary arm race and co-evolution. Many types of biological behaviours observed in nature emerge spontaneously.

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

25 Mutation Cosmic mutationscause the flipping of random bits in the soup at a low frequency Copy errors result in replication errors Flawscan occur during execution. The result is off by ±1 at some low frequency Creatures activity scramble the soup

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

27 Tierra Language Special machine language designed to be robust Small but computational complete instruction set (32 instructions) No operands: it uses stack (push and pop) and registers Jumps: addressing by templates To find the right place to jump to, a search is made for the nearest complementary template to that following the jump instruction

28 Instruction Set nop_0 no op pop_ax pop into ax nop_1 pop_bx or1 flip bit of cx pop_cx sh1 shift left cx pop_dx zero zero cx jmp to template if_cz if zero jmpb backward sub_ab call call procedure sub_ac ret return inc_a mov_cd inc_b mov_ab dec_c mov_iab mov instrn inc_c adr adrs of templ push_ax onto stack adrb search backwd push_bx adrf search fwd push_cx mal alloc memory push_dx divide 'SPLIT'

29 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 Ancestor 1100 copy procedure Save registers to stack 1010 move bx ax decrement cx if cx==0 jump 0100 increment ax & bx jump restore registers return 1110

30 What happened Memory filled up with copies, mutants appeared. Smaller self-replicating mutants were favoured, because of the way CPU time was shared. Then parasites appeared --only 45 instructions long, not capable of self-replication but manage to 'borrow' the replication code of their neighbours (-- organisms can read or execute others code).

31 Parasites and hyper-parasites parasites An ecology of different organism types builds up. Some immunity to parasites appears in some selfreplicators Hyper-parasites 'steal the instruction pointers from parasites Social parasites... hyper-hyper-parasites... etc etc...

32 Experiments Hosts, red, are very common. Parasites, yellow, have appeared but are still rare.

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

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

35 Macro-dynamics Tierra is a rich experimental domain for watching a diverse ecology grow, possible parallels to situations in the real world. For each organism, the 'physical world' consists of 'energy' (CPU time = sunlight) and 'space' in memory, which is limited. But above all, the environment which affects their fitness includes the other organismsaround. Creatures invent they own fitness function by adaptation to the biotic environment. Emergent features: open-ended evolution affecting fitness function, size, shape, distribution, fragmentation, heterogeneity of programs (every aspects of programs is subject to evolution). Emergent ecology and explosion of diversity of behaviors.

36 Tierra Summary A framework for synthesis of life was presented Open-ended evolution arises from an initial self- replicating ancestor Emergence of Natural-like Ecology was observed This work has been a fruitful source of ideas, has spawned a whole industry!

37 Is Tierra Alive? IT S ALIVE!!

38 References Tierra Tierra publications More general on Tierra

39 References Artificial Life