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The Black Art of Evolution.
Chrisantha Fernando
Collegium Budapest
2005
Part 1: Understanding evolution
as an engineering tool.
Part 2: Understanding how living
systems facilitate evolution.
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.
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.
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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.
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.
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.
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
Locomotion etc…
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Karl Sims
Hornby et al
Evolving Nervous Systems for Robots.
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Dario Floreano et al
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http://asl.epfl.ch/
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?
The Black Art of Evolution.
We programmed in replication, heredity, variation and selection
explicitly.
1.
2.
3.
4.
5.
We had to invent the genotype-phenotype map ourselves.
We had to make the paper gliders with our own hands, they did not
self-replicate.
We had to define the genetic operators, i.e. how mutation and
recombination works.
We had to specify the unit of evolution (glider) ourselves.
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?
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.
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.
How does the genotype-phenotype map work in real organisms?
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GENE REGULATORY NETWORK
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Block Pushing using a
Gene Regulatory Network
Controled Morphology.
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Josh Bongard
Neutrality.
’Constant innovation’ -- You never get stuck !
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Examples of Neutrality of GP
Map.
• RNA Sequence --> RNA Structure.
• Evolvable Hardware.
2. Can we make self-replicating
things?
Non-chemical self-replicating systems have not been evolvable.
Chris Langton
Formal Self-Replicating Systems.
2. Von Neumann’s Self
Replicating Automata.
Able to copy any tape.
But not robust to mutation.
Also takes ages to work!
Template Replication (from Breivik).
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.
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.
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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.
• 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.
None of the things we evolved
were alive!
Units of Evolution
Units of Life
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.
Tibor Ganti
Absolute Life Criteria:
1.
2.
3.
4.
5.
Inherent individual unit.
Perform metabolism.
Inherently stable.
Subsystem carrying information which is useful to the whole system.
Processes must be regulated and controlled.
Potential Life Criteria:
1.
2.
3.
Capable of growth and multiplication.
Capacity for hereditary change and evolution. Capacity to produce increasingly
complex forms over successive generations.
Mortality.
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.
The Fundamental Unit of Life.
The Chemoton.
The Chemoton consists of 3 coupled self-replicating systems.
EACH WITH ITS OWN DYNAMICS.
Autocatalytic Metabolism.
Autocatalytic Non-Enzymatic Template Replication.
Autocatalytic Membrane
Replication
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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.
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.
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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.
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’?
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?
Acknowledgements
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Eörs Szathmáry
Simon McGregor
Andy Ballam
Sampsa Sojakka
Rob Vickerstaff
Phil Husbands
Inman Harvey
Ezequiel Di Paolo