Examples of Population

aufnahme.fmg.edu.kit.aifb.AufnahmeTyp.Population
com.heatonresearch.aifh.evolutionary.population.Population
Defines a population of genomes.

A Population is the repository for all the Individuals being bred or evaluated in the evolutionary run at a given time. A Population is basically an array of Subpopulations, each of which are arrays of Individuals coupled with a single Species per Subpoulation.

The first Population is created using the initializePopulation method of the Initializer object, which typically calls the Population's populate() method in turn. On generational systems, subsequent populations are created on a generation-by-generation basis by the Breeder object, replacing the previous Population.

In a multithreaded area of a run, Populations should be considered immutable. That is, once they are created, they should not be modified, nor anything they contain. This protocol helps ensure read-safety under multithreading race conditions.

Parameters

base.`subpops` int >= 1	(the number of subpopulations)
base.`subpop`.n classname, inherits or = ec.Subpopulation	(the class for subpopulation #n)
base.`default-subpop` int >= 0	(the default subpopulation index. The parameter base of this subpopulation will be used as the default base for all subpopulations which do not define one themselves./tr>

Parameter bases

base.subpop.n Subpopulation #n.

@author Sean Luke @version 1.0

jcgp.backend.population.Population
This class primarily holds a collection of chromosomes. In addition, it provides a few utility methods for manipulating and copying chromosomes, useful for evolutionary strategies.

{@code copyChromosome()} is used to create copies of chromosomes, though it is also possible to create a new instance of population directly from a seed chromosome using the right constructor.

For convenience, a random chromosome can be retrieved using {@code getRandomChromosome()}, which is guaranteed to use the experiment's specified seed. If an entirely random population is needed, {@code reinitialise()} should be used to randomiseall chromosomes without creating a new instance of {@code Population}. @author Eduardo Pedroni
org.apache.commons.math3.genetics.Population
A collection of chromosomes that facilitates generational evolution. @since 2.0
org.encog.ml.ea.population.Population
Defines a population of genomes.
org.encog.ml.genetic.population.Population
Defines a population of genomes.
ru.mail.teodorgig.mididermi.base.Population
Differential evolution population class. Implementation of genetic algorithm based optimization approach. All melodies are presented as chromosomes (vectors). During evolution period recombination of chromosomes is applied and human evaluation of the melody quality. @author Todor Balabanov @email teodorgig@mail.ru @date 22 May 2008
wolf.city.map.Population

Examples of ru.mail.teodorgig.mididermi.base.Population

        take[index] = true;
        num--;
      }
    }


    Population population = new Population();


    for (int i = 0; i < pool.size(); i++)
      if (take[i] == true)
        population.add((Melody) pool.elementAt(i).clone());


    return (population);
  }

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Examples of wolf.city.map.Population

    random = new Random(seed);
    for(int i=0; i<10; i++){ //warm up the random number generator
      random.nextDouble();
    }
    //water = new Water(this);
    pop = new Population(this);
    ter = new Terrain(this);


    rm = new Roadmap(this);
    bm = new Blockmap(this);
    fb = new FakeBuildings(this);

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