1 / 12

Mutation at Evolution Strategy

Mutation at Evolution Strategy. by Guido Moritz SoftComputingMethods 2006. 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. Target of Evolution Strategy.

asis
Download Presentation

Mutation at Evolution Strategy

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Mutation at Evolution Strategy • by • Guido Moritz • SoftComputingMethods 2006

  2. 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

  3. Target of Evolution Strategy Aktion Integralanteil Reaktion Differentialanteil Proportionalanteil I P D x(t) Regelgröße by Ingo Rechenberg

  4. Evolution 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

  5. Evolution 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)

  6. Mutation – 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)

  7. Mutation – how to GALTONs Nailboard (Nails vertical of wall) Leakage=distance between nails by Ingo Rechenberg

  8. Selfadapting Leakage (StepSize) - Why ∆x2 ∆h2 ∆x1 ∆ ∆x1=∆x2 BUT ∆h1!=∆h2 ∆h1

  9. Rechenberg 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 • ∂= ∂;

  10. Problems • 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, ∂ σneu) • σ can addapt itself to problem • Δ-factor how strong is selfadapting of leakage • http://www.evocomp.de/themen/evolutionsstrategien/evostrat.html

  11. Random Numbers • Constant allocated (same chance) • Gauß allocated

  12. Random Numbers • Take quadratic values • Gaußnarrow/higher • Constandbigger values • Group numbers • Constand  getting closer to avarage • Effect of both (quadrativ&group) • Difference between values and avarage is getting smaller

More Related