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package jcgp.backend.modules.es;
import jcgp.backend.modules.Module;
import jcgp.backend.modules.mutator.Mutator;
import jcgp.backend.population.Population;
import jcgp.backend.resources.Resources;
/**
* This interface specifies the required behaviour of an evolutionary strategy. The evolutionary
* strategy's job is to generate the next population of solutions. In JCGP this is done by modifying
* the provided population object rather than creating a new one.
* <br><br>
* A typical implementation of EvolutionaryStratey iterates through the chromosomes
* in the population and selects the individual(s) to be promoted. It then uses
* {@code mutator.mutate()} to generically mutate the promoted individual(s). Parameter-dependent
* strategies can be implemented by accessing the parameters via the resources
* argument.
* <br><br>
* Parameters may be specified to control the implemented strategy. Any parameters
* returned by {@code getLocalParameters()} should be displayed by the user interface,
* if it is being used. See {@link Parameter} for more information.
* <br><br>
* It is advisable to use {@code Resources.reportln()} and {@code Resources.report()}
* to print any relevant information. Note that reportln() and report() are affected
* by the report interval base parameter. Use {@code Resources.println()} and
* {@code Resources.print()} to print information regardless of the current generation.
* See {@link Resources} for more information.
*
* @see Module
*
* @author Eduardo Pedroni
*
*/
public interface EvolutionaryStrategy extends Module {
/**
* Performs the selection algorithm and uses the mutator to create
* the next generation of solutions.
*
* @param population the population to evolve.
* @param mutator the mutator with which to mutate the promoted individuals.
* @param resources parameters and utilities for optional reference.
*/
public abstract void evolve(Population population, Mutator mutator, Resources resources);
}
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