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![Page 1: University of Rostock Institute of Applied Microelectronics and Computer Engineering 1 Mutation at Evolution Strategy by Guido Moritz SoftComputingMethods.](https://reader035.fdocuments.us/reader035/viewer/2022070305/55144c8b550346284e8b4efd/html5/thumbnails/1.jpg)
University of Rostock Institute of Applied Microelectronics and Computer Engineering
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Mutation at Evolution StrategyMutation at Evolution Strategy
by
Guido Moritz
SoftComputingMethods 2006
![Page 2: University of Rostock Institute of Applied Microelectronics and Computer Engineering 1 Mutation at Evolution Strategy by Guido Moritz SoftComputingMethods.](https://reader035.fdocuments.us/reader035/viewer/2022070305/55144c8b550346284e8b4efd/html5/thumbnails/2.jpg)
University of Rostock Institute of Applied Microelectronics and Computer Engineering
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Target of Evolution Strategy Target of Evolution Strategy
Find a solution for BlackBoxProblems (no explicit solution) wich is exactly enough.
INPUT OUTPUT
EXAMPLE: FIND AN INPUT WHERE THE OUTPUT IS MAXIMUM
![Page 3: University of Rostock Institute of Applied Microelectronics and Computer Engineering 1 Mutation at Evolution Strategy by Guido Moritz SoftComputingMethods.](https://reader035.fdocuments.us/reader035/viewer/2022070305/55144c8b550346284e8b4efd/html5/thumbnails/3.jpg)
University of Rostock Institute of Applied Microelectronics and Computer Engineering
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Target of Evolution StrategyTarget of Evolution Strategy
Regler Strecke
Stellgröße y Regelgröße xSollwert w
Störgröße z
P I D
Proportionalanteil
Integralanteil
Differentialanteil
x (t)
AktionReaktion
Regelgröße
by Ingo Rechenberg
![Page 4: University of Rostock Institute of Applied Microelectronics and Computer Engineering 1 Mutation at Evolution Strategy by Guido Moritz SoftComputingMethods.](https://reader035.fdocuments.us/reader035/viewer/2022070305/55144c8b550346284e8b4efd/html5/thumbnails/4.jpg)
University of Rostock Institute of Applied Microelectronics and Computer Engineering
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Evolution Strategy – how toEvolution Strategy – how to
• Genererating new elements by recombination/variation of existing elements
• Choose good and bad elements (because of difference between OUTPUTS)
• Take good ones for next generation (recombination/variation) - > creating new INPUTS
![Page 5: University of Rostock Institute of Applied Microelectronics and Computer Engineering 1 Mutation at Evolution Strategy by Guido Moritz SoftComputingMethods.](https://reader035.fdocuments.us/reader035/viewer/2022070305/55144c8b550346284e8b4efd/html5/thumbnails/5.jpg)
University of Rostock Institute of Applied Microelectronics and Computer Engineering
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Evolution Strategy – how toEvolution Strategy – how to
• Creating elements randomly• Select parents (by random)• Recombination of parents• Mutation• Choose because of fitness• Generating new generation
Xneu=Xalt+∂*N(0,σ)
![Page 6: University of Rostock Institute of Applied Microelectronics and Computer Engineering 1 Mutation at Evolution Strategy by Guido Moritz SoftComputingMethods.](https://reader035.fdocuments.us/reader035/viewer/2022070305/55144c8b550346284e8b4efd/html5/thumbnails/6.jpg)
University of Rostock Institute of Applied Microelectronics and Computer Engineering
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Mutation – how toMutation – how to
• Changing a value by f.e. adding or substracting a small normal distributed (avarage=0) value with a standard variance (dt. standartabweichung)
• How big changing-decided by ∂ and standart variance of N()
• Xneu=Xalt+∂*N(0,σ)
![Page 7: University of Rostock Institute of Applied Microelectronics and Computer Engineering 1 Mutation at Evolution Strategy by Guido Moritz SoftComputingMethods.](https://reader035.fdocuments.us/reader035/viewer/2022070305/55144c8b550346284e8b4efd/html5/thumbnails/7.jpg)
University of Rostock Institute of Applied Microelectronics and Computer Engineering
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Mutation – how toMutation – how to
GALTONs Nailboard(Nails vertical of wall)
by Ingo Rechenberg
Leakage=distance between nails
![Page 8: University of Rostock Institute of Applied Microelectronics and Computer Engineering 1 Mutation at Evolution Strategy by Guido Moritz SoftComputingMethods.](https://reader035.fdocuments.us/reader035/viewer/2022070305/55144c8b550346284e8b4efd/html5/thumbnails/8.jpg)
University of Rostock Institute of Applied Microelectronics and Computer Engineering
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Selfadapting Leakage (StepSize) - Selfadapting Leakage (StepSize) - WhyWhy
∆x1
∆h1
∆x2∆h2
∆x1=∆x2BUT
∆h1!=∆h2
∆
![Page 9: University of Rostock Institute of Applied Microelectronics and Computer Engineering 1 Mutation at Evolution Strategy by Guido Moritz SoftComputingMethods.](https://reader035.fdocuments.us/reader035/viewer/2022070305/55144c8b550346284e8b4efd/html5/thumbnails/9.jpg)
University of Rostock Institute of Applied Microelectronics and Computer Engineering
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Rechenberg 1/5 RuleRechenberg 1/5 Rule
If 1/5 of mutations are better (better fitness) decrease leakage!
If sucess<1/5∂= ∂*1,5;
Else if (sucess>1/5) ∂= ∂/1,5;
Else ∂= ∂;
![Page 10: University of Rostock Institute of Applied Microelectronics and Computer Engineering 1 Mutation at Evolution Strategy by Guido Moritz SoftComputingMethods.](https://reader035.fdocuments.us/reader035/viewer/2022070305/55144c8b550346284e8b4efd/html5/thumbnails/10.jpg)
University of Rostock Institute of Applied Microelectronics and Computer Engineering
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ProblemsProblems
• Rechenbergs Rule is static and depends not on problem itself (maybe only local optimum)
Schwefel enhanced Rechenbergs Rule (∂ takes part at evolution): σ neu := σ alt e^N(0,Δ)⋅
xneu := xalt + ∂ *N(0, ∂ σ neu)• σ can addapt itself to problem• Δ-factor how strong is selfadapting of leakage
http://www.evocomp.de/themen/evolutionsstrategien/evostrat.html
![Page 11: University of Rostock Institute of Applied Microelectronics and Computer Engineering 1 Mutation at Evolution Strategy by Guido Moritz SoftComputingMethods.](https://reader035.fdocuments.us/reader035/viewer/2022070305/55144c8b550346284e8b4efd/html5/thumbnails/11.jpg)
University of Rostock Institute of Applied Microelectronics and Computer Engineering
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Random NumbersRandom Numbers
• Constant allocated (same chance)• Gauß allocated
![Page 12: University of Rostock Institute of Applied Microelectronics and Computer Engineering 1 Mutation at Evolution Strategy by Guido Moritz SoftComputingMethods.](https://reader035.fdocuments.us/reader035/viewer/2022070305/55144c8b550346284e8b4efd/html5/thumbnails/12.jpg)
University of Rostock Institute of Applied Microelectronics and Computer Engineering
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Random NumbersRandom Numbers
• Take quadratic values– Gaußnarrow/higher– Constandbigger values
• Group numbers– Constand getting closer to avarage
• Effect of both (quadrativ&group)– Difference between values and avarage is
getting smaller