Genetic Engineering and Creative Design

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Genetic Engineering and Creative Design Background genes, genotype, phenotype, fitness Connecting genes to performance in fitness Emergent gene clusters evolved genes MIT Class 4.208 Spring 2002

Evolution Crossover Points A Parents B C Offspring D MIT Class 4.208 Spring 2002

Parents Offspring A A B A B C B B C B A B Crossover point MIT Class 4.208 Spring 2002

Parents Offspring A A B A A C B B C B B B Crossover point MIT Class 4.208 Spring 2002

Total Population bad good x x x x good genotypes x x bad genotypes MIT Class 4.208 Spring 2002

a rule 1 a b a rule 2 a b a rule 3 a b a rule 4 b a a rule 5 a a rule 6 b b a a rule 7 b a a rule 8 b a MIT Class 4.208 Spring 2002

design 1 design 2 design 3 good {1,12,2,8,5,4,4,2,8,5,7} good {1,2,1,8,2,8,5,5,6,6,8,1} bad {3,2,2,6,5,8,2,1,4,4,3,1} design 4 design 5 design 6 good {6,4,1,2,8,5,4,2,8,5,3,3} bad {3,4,8,2,8,1,6,5,7,3} neutral {2,3,2,3,4,3,5,6,5,1,6,2} design 7 design 8 design 9 design 10 good {3,1,8,5,5,6,4,6,1,1,3,3} bad {1,6,4,2,7,3,4,8,6,1,6,2} neutral bad {6,4,1,2,3,4,5,2,1,7,4} {2,3,7,5,1,2,8,3,1,6,2,1} Composite building block A {2,8,5} MIT Class 4.208 Spring 2002

Evolving genes First step: evolve coding One prototype case Start with simple coding Modified evolutionary system Second step: use coding New design task Use evolved coding Reduced search-space Usage of design knowledge from prototype MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

Example task Phenotypes are parts of drawing Higher fitness for better fit Turtle coding: 00 line 01 step 10 turn right 11 turn left MIT Class 4.208 Spring 2002

Coding of evolved genes Two basic genes Basic gene +evolved gene Two evolved genes 0 0 + 0 0 > 1 0 0 + 1 > 2 1 + 2 > 3 MIT Class 4.208 Spring 2002

Modification to evolutionary system Goal is high variety of fit individuals, not single optimal solution Convergence avoided: Growing population: Only duplicate and non-fitting individuals removed Evolving fitness, proportional to number of individuals in same region: Low fitness in densely populated regions High fitness in unpopulated regions Niching MIT Class 4.208 Spring 2002

Gene extraction Evolved genes composed of two (basic or evolved) sub-genes Most common pair of sub-genes identified and extracted Pairs have to occur in at least N different individuals Genes replaced throughout population Number of evolved genes kept at 5% of number of individuals in population MIT Class 4.208 Spring 2002

The set of evolved genes Gene families Every gene represents a larger group of similar genes (8 28 genes) 1 44 76 191 115 167 37 176 Genes are numbered in order of generation MIT Class 4.208 Spring 2002

Special genes Every gene is special or occurs only in a small number of variations 206 197 83 106 139 169 110 185 180 88 Genes are numbered in order of generation MIT Class 4.208 Spring 2002

Example of Evolved Coding 164 53 10 54 189 160 10 4 2 3 1 42 4 3 15 9 0 69 1 0 0 0 1 3 0 2 3 MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

3-complexity 2-complexity 1-complexity 0-complexity g 2 g10 g 1 (a) g 8 g0 g 3 (b) g 11 g9 g8 g 1 g 0 MIT Class 4.208 Spring 2002

Percentage of genes evolved Percentage of genes evolved Generations Complexity of evolved genes MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

base representation prototype case evolved genes adapted result integration of knowledge into representation use of knowledge MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

Genetic Engineering of Bad Genes locate bad gene groups remove bad gene groups radiation therapy for bad gene groups through high mutation rates gene therapy for bad gene groups through replacement with good genes cloning to increase percentage of good genes MIT Class 4.208 Spring 2002

Total Fraction of Bad Genes in Population Gene therapy Radiation therapy MIT Class 4.208 Spring 2002

Total Fraction of Evolved Genes in Population Gene evolution Gene therapy Bad genes after gene therapy MIT Class 4.208 Spring 2002

Genotype Form In form of a tree Each node has four variables direction of rectangular split (4 values) fraction of the split (15 values) colour of split area (10 values) line width (3 values) MIT Class 4.208 Spring 2002

Fitnesses for Representation offset between actual and required positions of dissection lines number of lines with correct line width, normalised number of correct colour panels, normalised number of lines assigned, normalised number of unassigned lines, normalised MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

Flondrians Mondrian painting genetically engineered genes: M-genes Frank Lloyd Wright windows genetically engineered genes in same representation: F-genes Flondrians are the genetic product of mating M-genes with F-genes MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002

MIT Class 4.208 Spring 2002