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On May 20, 2008, at 11:55 AM, Peter Drake wrote:

> Nope, same story -- squelches the error, but doesn't set the  
> subpopulation sizes.

Here's a version of the SUM problem which evolves with two  
simultaneous subpopulations.  Both use the default (ec.subpop.size)  
of 100.  Works cleanly on the CVS version of the software.

Sean


verbosity =                             0
evalthreads =                           1
breedthreads =                          1
seed.0 =                                4357
checkpoint =                            false
checkpoint-modulo =                     1
prefix =                                ec
state =                                 ec.simple.SimpleEvolutionState
init =                                  ec.simple.SimpleInitializer
finish =                                ec.simple.SimpleFinisher
exch =                                  ec.simple.SimpleExchanger
breed =                                 ec.simple.SimpleBreeder
eval =                                  ec.simple.SimpleEvaluator
stat =                                  ec.simple.SimpleStatistics
generations =                           51
quit-on-run-complete =                  true
pop =                                   ec.Population
pop.subpops =                           2
pop.subpop.0 =                          ec.Subpopulation
pop.subpop.1 =                          ec.Subpopulation
pop.subpop.0.duplicate-retries =        0
stat.file                               $out.stat
generations = 5
ec.subpop.size =                        100

ec.subpop.duplicate-retries =           0
ec.subpop.species =                     ec.vector.IntegerVectorSpecies
vector.species.fitness =                ec.simple.SimpleFitness
vector.species.ind =                     
ec.vector.IntegerVectorIndividual
vector.species.min-gene =               0
vector.species.max-gene =               100
vector.species.genome-size =            10
vector.species.crossover-type =         one
vector.species.mutation-prob =          0.1
vector.species.pipe =                    
ec.vector.breed.VectorMutationPipeline
vector.mutate.source.0 =                 
ec.vector.breed.VectorCrossoverPipeline
vector.xover.source.0 =                 ec.select.TournamentSelection
vector.xover.source.1 =                 same

select.tournament.size =                2
eval.problem = ec.app.sum.Sum


### Here's the version if you did separate subpopulations

#pop.subpop.0.size = 			100
#pop.subpop.0.duplicate-retries = 0
#pop.subpop.0.species =                          
ec.vector.IntegerVectorSpecies
#pop.subpop.0.species.fitness =         ec.simple.SimpleFitness
#pop.subpop.0.species.ind =              
ec.vector.IntegerVectorIndividual
#pop.subpop.0.species.min-gene = 0
#pop.subpop.0.species.max-gene = 100
#pop.subpop.0.species.genome-size = 10
#pop.subpop.0.species.crossover-type = one
#pop.subpop.0.species.mutation-prob = 0.1
#pop.subpop.0.species.pipe = ec.vector.breed.VectorMutationPipeline
#pop.subpop.0.species.pipe.source.0 =  
ec.vector.breed.VectorCrossoverPipeline
#pop.subpop.0.species.pipe.source.0.source.0 =  
ec.select.TournamentSelection
#pop.subpop.0.species.pipe.source.0.source.1 = same

#pop.subpop.1.size = 			100
#pop.subpop.1.duplicate-retries = 0
#pop.subpop.1.species =                  ec.vector.IntegerVectorSpecies
#pop.subpop.1.species.fitness =          ec.simple.SimpleFitness
#pop.subpop.1.species.ind =               
ec.vector.IntegerVectorIndividual
#pop.subpop.1.species.min-gene = 0
#pop.subpop.1.species.max-gene = 100
#pop.subpop.1.species.genome-size = 10
#pop.subpop.1.species.crossover-type = one
#pop.subpop.1.species.mutation-prob = 0.1
#pop.subpop.1.species.pipe = ec.vector.breed.VectorMutationPipeline
#pop.subpop.1.species.pipe.source.0 =  
ec.vector.breed.VectorCrossoverPipeline
#pop.subpop.1.species.pipe.source.0.source.0 =  
ec.select.TournamentSelection
#pop.subpop.1.species.pipe.source.0.source.1 = same