Download Emergent Evolution allows Meta Evolution

Emergent Evolution allows
Meta Evolution
Adam Nellis
University of York
Emergent Evolution allows Meta Evolution – Adam Nellis – EmergeNet 4: Engineering Emergence – 19th April 2010
Evolutionary Algorithms
How many?
How do they
solve the
problem?
Initialise a population
of individuals
How?
Assess fitness of
individuals
How many?
Using what
method?
Select some
individuals to survive
How?
Reproduce these
individuals, with
variation
What
variation?
How much
variation?
Emergent Evolution allows Meta Evolution – Adam Nellis – EmergeNet 4: Engineering Emergence – 19th April 2010
Parts of an Evolutionary Algorithm
Initialise a population
of individuals
Assess fitness of
individuals
Select some
individuals to survive
1. A problem to solve
2. A population of candidate
solutions to the problem
3. A way of improving the quality
of solutions in the population
Reproduce these
individuals, with
variation
Emergent Evolution allows Meta Evolution – Adam Nellis – EmergeNet 4: Engineering Emergence – 19th April 2010
Evolution is not Evolutionary Algorithms
• Evolution is just:
– Variation, inheritance and selection
• It happens because:
– Individuals reproduce
– Reproduction is not perfect
– Resources are limited (so there is selection)
• Over time, this makes fitter individuals
– But what is an “individual”?
Emergent Evolution allows Meta Evolution – Adam Nellis – EmergeNet 4: Engineering Emergence – 19th April 2010
Emergent Evolution
Solutions to
problems
evolve
Evolutionary
Algorithm
parameters
Evolution
emergence
selection
Organisms
living, dying and reproducing
evolve
Evolutionary
Algorithm
parameters
evolve ?
produce
Solutions to
problems
?
Emergent Evolution allows Meta Evolution – Adam Nellis – EmergeNet 4: Engineering Emergence – 19th April 2010
Evolutionary Algorithm in the phenotype
Phenotype
Fitness
evaluate
Phenotype
inform
Evolutionary
Algorithm
develop
Genotype
Individual
Problem-solving
machinery
Expression
machinery
Copying
machinery
change
express
Genotype
copy
Emergent Evolution allows Meta Evolution – Adam Nellis – EmergeNet 4: Engineering Emergence – 19th April 2010
How? Individuals that are alive!
1. Perform a task (solve the application problem)
2. Metabolise food to gain energy
3. Use energy to express genes to do points 1 and 2
4. Copy my genes (imperfectly), to reproduce
5. Encode all of the above functionality in the genes
Emergent Evolution allows Meta Evolution – Adam Nellis – EmergeNet 4: Engineering Emergence – 19th April 2010
Example – Stringmol
A self-copying machine
Evolving over time
Emergent Evolution allows Meta Evolution – Adam Nellis – EmergeNet 4: Engineering Emergence – 19th April 2010
Large-scale mutation
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31:
BBOSEOLHHHRLUEUOBLROORE$BLUBOˆB>C$=?>$$BLUBO%}OYHOB
09: OBEQBX...UOBLROORE$BLUBOˆB>C$=?>$$BLUBO%}OYHOB
29: OBEQBX...UOBLROORE$BLUBPˆB>C$=?>$$BLUBO%}OYHOB
30:
OBEQBXUUUDYGRHBBOSEOLHHHRLUEUOBLR
OORE$BLUBPˆB>C$=?>$$BLUBO%}OYHO
OBEQBXUUUDYGRHBBOSEOLHHHRLUEUOBLR
OORE$BLUBOˆB>C$=?>$$BLUBO%}OYHOB
Emergent Evolution allows Meta Evolution – Adam Nellis – EmergeNet 4: Engineering Emergence – 19th April 2010
Summary
• Meta evolution via emergent evolution
– Not by evolving parameters in a hardcoded
algorithm
• Richer individuals
– That have the Evolutionary Algorithm as part
of their phenotype
• Example of large-scale-mutation
– Strings copying each other with per-character
mutation
– Evolved a large-scale macro-mutation
Emergent Evolution allows Meta Evolution – Adam Nellis – EmergeNet 4: Engineering Emergence – 19th April 2010