Population Sizing as an Emergent Behavior
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Transcript of Population Sizing as an Emergent Behavior
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Population Sizing as Population Sizing as an Emergent an Emergent Behavior Behavior Jason CookJason Cook
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MotivationMotivation
Ease of useEase of use Limit necessary manual tuningLimit necessary manual tuning Potentially improve performancePotentially improve performance
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Problem StatementProblem Statement
Remove the population size parameterRemove the population size parameter Introduce no new parametersIntroduce no new parameters Maintain useful level of accuracyMaintain useful level of accuracy
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Solution MethodSolution Method
Set up the population size as an Set up the population size as an emergent behavioremergent behavior
Replace survivor selection with a survival Replace survivor selection with a survival chancechance
SRSRii = ( = (FFii – – FFminmin)) / ( / (FFmaxmax – – FFminmin))
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Experimental SetupExperimental Setup
Compare with a traditional EACompare with a traditional EA Two main test problems: Griewank Function Two main test problems: Griewank Function
and D-TRAP Problemand D-TRAP Problem Survival Method:Survival Method:
Survival Chance Survival Chance or or
N-TournamentN-Tournament Other operators and parameter held constant Other operators and parameter held constant
for both EAsfor both EAs
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Griewank FunctionGriewank Function
NN dimensional minimization problem dimensional minimization problem Many local optimaMany local optima Optimal solution: Optimal solution: xxii = 0 = 0
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D-TRAPD-TRAP
250 4-bit pieces250 4-bit pieces Each piece is worth:Each piece is worth:
3 – 3 – uu if if uu ≤ 3 ≤ 3 44 otherwiseotherwise
Optimal solution: Optimal solution: xxii = 0 = 0
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ResultsResults
Progression of Fitness values of the Griewank Function
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Fitness Evaluations
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EA-OPT Auto-PS-EA
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Results (Continued):Results (Continued):
Changes in Population Size in the Griewank Function
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50 1100 2150 3200 4250 5300 6350 7400 8450 9500
Fitness Evaluations
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Results (Continued):Results (Continued):
Progression of Fitness Values for the D-TRAP problem
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510 1560 2610 3660 4710 5760 6810 7860 8910 9960
Fitness Evaluations
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Fixed Population Size
Dynamic Population Size
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Results (Continued):Results (Continued):
Changes in Population Size during the D-TRAP problem
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510 1560 2610 3660 4710 5760 6810 7860 8910 9960
Fitness Evaluations
Po
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Siz
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AnalysisAnalysis
Performs as well or better than a Performs as well or better than a traditional EAtraditional EA
Still affected by the initial population sizeStill affected by the initial population size
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Future WorkFuture Work
More test problemsMore test problems Use a more competitive EA to test Use a more competitive EA to test
againstagainst
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Questions?Questions?