1. The Black Art of Evolution. Chrisantha Fernando Collegium Budapest 2005

2. Part 1: Understanding evolution as an engineering tool. Part 2: Understanding how living systems facilitate evolution.

3. Requirements for Evolution. Units must replicate. Units must show heredity across generations (like begets like). Heredity. Heredity should not be exact. Variability. Some variants must produce more offspring than others. Selection. Selection can be artificial or natural.

4. Consequences of Evolution. Over many generations, the make-up of the population changes. Without the need for any individual to change, successive generations change, and in some sense (usually) adapts to the conditions. Evolution can be seen as a search within a many-dimensional, search space, a fitness landscape, with a population moving to the mountain tops of high fitness.

6. Can We Do Evolution Ourselves? Yes. Make a genotype: 01111010001101000101 Interpret/Translate the genotype into a phenotype: E.g. the neural network (nervous system) controller for a robot. A simple example. Evolving paper gliders.

7. Fold TL to BR towards you Fold horiz middle away Fold vertical middle towards Fold TR to BL towards you Fold horiz middle away Fold vertical middle away I. Harvey.

8. 1.Generate 20 random sequences of folding instructions 2.Fold each piece of paper according to instructions written on them 3.Throw them all out of the window 4.Pick up the ones that went furthest, look at the instrns 5.Produce 20 new pieces of paper, writing on each bits of sequences from parent pieces of paper 6.Repeat from (2) on.

11. Some real examples of things artificially evolved. TABLES Fitness function rewarded structures for maximizing: height; surface area; stability/volume; and minimizing the number of cubes. Hornby et al

12. Locomotion etc… Hornby et al Karl Sims

13. Evolving Nervous Systems for Robots. Dario Floreano et al http://asl.epfl.ch/

15. The Black Art. A lot of prior knowledge about the problem went into the design of the genetic algorithm. What was this prior knowledge? How can real evolution have worked without someone putting this prior knowledge in?

16. The Black Art of Evolution. We programmed in replication, heredity, variation and selection explicitly. 1.We had to invent the genotype-phenotype map ourselves. 2.We had to make the paper gliders with our own hands, they did not self-replicate. 3. We had to define the genetic operators, i.e. how mutation and recombination works. 4. We had to specify the unit of evolution (glider) ourselves. 5.We had to define the criteria for selection (fitness function) and define the selection algorithm ourselves. Real fitness is determined ecologically, co-evolution occurs. Artificial co-evolution is v. tricky to get right. The ‘black art’ is not trivial, and in fact is crucial for any artificial evolution to work. How has natural evolution done the ‘black art’ itself?

17. 1. The Genotype-Phenotype Map. Artificial Evolution. How can I sensibly encode different phenotypes (possible solutions) as genotypes (artificial DNA, strings of symbols) ? For heredity and variation to work properly, as far as possible, small changes in G (mutations) should make small changes in P. And inheriting bits of G from different parents should ideally result in inheriting bits of each parent’s phenotypic characteristics. Direct Encodings: Does not scale up to large phenotypes. Indirect/Generative/Developmental Encodings: Difficult to design by hand. Requires prior knowledge of solution space. Too computationally expensive to search through space of possible encodings. Are often brittle.

18. 1. The Genotype-Phenotype Map. Biological Evolution. How does information coded in the genotype make the phenotype? Biological Principles (Self-Similarity, Modularity, Neutrality). Self-Similarity.

19. How does the genotype-phenotype map work in real organisms? GENE REGULA- TORY NETWORK

20. Josh Bongard Block Pushing using a Gene Regulatory Network Controled Morphology.

21. Neutrality. ’Constant innovation’ -- You never get stuck !

23. Examples of Neutrality of GP Map. RNA Sequence --> RNA Structure. Evolvable Hardware.

25. 2. Can we make self-replicating things? Non-chemical self-replicating systems have not been evolvable. Formal Self-Replicating Systems. Chris Langton

26. 2. Von Neumann’s Self Replicating Automata. Able to copy any tape. But not robust to mutation. Also takes ages to work!

27. Template Replication (from Breivik).

29. 3. We had to choose the genetic operators, i.e. type of variation. Mutation: Rate, vector, point. Recombination: Single point, double, random. Complex structured operators acting on larger genetic units. Real evolution has ‘tuned’ and evolved the genetic operators themselves.

30. 4 & 5. Emergent Units of Evolution in an Ecology. Tierra is a finite world in computer memory. Organisms are blocks of memory (space). They reproduce by allocating memory for a daughter and giving it access to its own instruction pointer. A reaper kills organisms randomly leaving their dead code in the soup. ‘Cosmic rays’ flip bits of memory so replication errors occur. At the start a hand-designed self-replicating ‘ancestor’ 80 instructions long, is inserted and allowed to replicate.

32. Evolutionary Dynamics in Tierra. Smaller self-replicating mutants require less CPU time (energy/resource), so replicate faster. Parasites appeared 45 instructions long, able to use the code of their neighbors. Hyperparasites appear that are even smaller and faster at replicating.

33. I wanted to understand how evolution could bootstrap itself to produce more and more complex phenotypes. Current evolutionary robotics is limited by decisions about the g-p map and phenotypic dynamics. I found that John Maynard-Smith and Eörs Szathmáry had written the book The Major Transitions in Evolution about the details of biological emergence of higher levels of organisation. I wished to find the proper framework to explore how open-ended evolution could work.

34. None of the things we evolved were alive! Units of LifeUnits of Evolution

35. What is Life? You land on Mars and find a strange object. You have to decide whether it is alive or not. Briefly state your methods.

36. Tibor Ganti Absolute Life Criteria: 1.Inherent individual unit. 2.Perform metabolism. 3.Inherently stable. 4.Subsystem carrying information which is useful to the whole system. 5.Processes must be regulated and controlled. Potential Life Criteria: 1.Capable of growth and multiplication. 2.Capacity for hereditary change and evolution. Capacity to produce increasingly complex forms over successive generations. 3.Mortality.

37. Evolution has acted on Fluid Machines. Living systems are chemical machines, using chemical energy and matter to construct themselves, and producing waste. The production of self-reproducing (autocatalytic) machines in chemical state space is much easier than in mechanical automata, because these systems are free of geometric constraints. Ganti showed how a metabolic cycle, a template replication system, and a compartment (boundary) system can satisfy all life criteria.

38. The Fundamental Unit of Life. The Chemoton.

39. The Chemoton consists of 3 coupled self-replicating systems. EACH WITH ITS OWN DYNAMICS.

40. Autocatalytic Metabolism.

41. Autocatalytic Non-Enzymatic Template Replication.

42. Autocatalytic Membrane Replication

43. The clever part is how they are coupled. The genes do not encode all the dynamical properties of the phenotype. Instead they regulate and control phenotypic dynamics. There is epigenetic inheritance.

44. The Origin of Long Template Replication. Long template replication can allow unlimited heredity. Can we explain how this is possible without enzymes? We are running simulations of the templates now to see if in chemoton like conditions, long templates could replicate.

47. The Origin of the Chemoton. But how could the chemoton form? How can its metabolism be stable without enzymes? We are running simulations now to understand the conditions under which large autocatalytic metabolic systems can be both evolvable and stable.

48. The Origin of Autocatalytic Metabolic Systems. How is it possible to obtain a self-sustaining interesting organisation (autocatalytic system) from an initially random set of chemicals. How probable are such conditions? Experiments so far. –System reached a point attractor of tar. –Experiments did not keep the system out of equilibrium. How can selection act at this chemical level, where there are no well defined spatial units of evolution, but where the unit exists in chemical ‘space’?

49. Conclusion. How can a complex metabolism arise without enzymes to direct it? How can that metabolism form an informational control system (genes) and a boundary? How did selection act on chemotons?

50. Acknowledgements Eörs Szathmáry Simon McGregor Andy Ballam Sampsa Sojakka Rob Vickerstaff Phil Husbands Inman Harvey Ezequiel Di Paolo