Package ec.coevolve

Class MultiPopCoevolutionaryEvaluator

java.lang.Object
ec.Evaluator
ec.coevolve.MultiPopCoevolutionaryEvaluator
All Implemented Interfaces:
Setup, Singleton, Serializable
Direct Known Subclasses:
SpatialMultiPopCoevolutionaryEvaluator
public class MultiPopCoevolutionaryEvaluator extends Evaluator
MultiPopCoevolutionaryEvaluator.java

MultiPopCoevolutionaryEvaluator is an Evaluator which performs competitive or cooperative multi-population coevolution. Competitive coevolution is where individuals' fitness is determined by testing them against individuals from other subpopulation. Cooperative coevolution is where individuals form teams together with members of other subpopulations, and the individuals' fitness is computed based on the performance of such teams. This evaluator assumes that the problem can only evaluate groups of individuals containing one individual from each subpopulation. Individuals are evaluated regardless of whether or not they've been evaluated in the past.

Your Problem is responsible for updating up the fitness appropriately with values usually obtained from teaming up the individual with different partners from the other subpopulations. MultiPopCoevolutionaryEvaluator expects to use Problems which adhere to the GroupedProblemForm interface, which defines a new evaluate(...) function, plus a preprocess(...) and postprocess(...) function.

This coevolutionary evaluator is single-threaded -- maybe we'll hack in multithreading later. It allows any number of subpopulations (implicitly, any number of individuals being evaluated together). The order of individuals in the subpopulation may be changed during the evaluation process.

Ordinarily MultiPopCoevolutionaryEvaluator does "parallel" coevolution: all subpopulations are evaluated simultaneously, then bred simultaneously. But if you set the "sequential" parameter in the class ec.simple.SimpleBreeder, then MultiPopCoevolutionary behaves in a sequential fashion common in the "classic" version of cooperative coevolution: only one subpopulation is evaluated and bred per generation. The subpopulation index to breed is determined by taking the generation number, modulo the total number of subpopulations.

Parameters

breed.sequential
boolean (default = false)		 (should we evaluate and breed a single subpopulation each generation? Note that this is a SimpleBreeder parameter. )
base.subpop.num-current
int >= 0		 (the number of random individuals from any given subpopulation fropm the current population to be selected as collaborators)
base.subpop.num-gurus
int >= 0		 (the number of guru individuals from any given subpopulation from the previous population to be selected as collaborators. For generation 0, random individuals from the current population will be used. )
base.subpop.num-prev
int >= 0		 (the number of random individuals from any given subpopulation from the previous population to be selected as collaborators. For generation 0, random individuals from the current population will be used)
base.subpop.X.select-prev
instance of ec.SelectionMethod		 (the SelectionMethod used to select partners from the individuals in subpopulation X at the previous generation)
base.subpop.X.select-current
instance of ec.SelectionMethod		 (the SelectionMethod used to select partners from the individuals in subpopulation X at the current generation. WARNING. This SelectionMethod must not select based on fitness, since fitness hasn't been set yet. RandomSelection is a good choice. )
base.shuffling
boolean (default = false)		 (instead of selecting individuals from )
See Also:

  • Field Details

  • Constructor Details

    • MultiPopCoevolutionaryEvaluator

      public MultiPopCoevolutionaryEvaluator()

  • Method Details

    • setup

      public void setup(EvolutionState state, Parameter base)
      Description copied from interface: Setup
      Sets up the object by reading it from the parameters stored in state, built off of the parameter base base. If an ancestor implements this method, be sure to call super.setup(state,base); before you do anything else.
      Specified by:
      setup in interface Setup
      Overrides:
      setup in class Evaluator

    • runComplete

      public String runComplete(EvolutionState state)
      Description copied from class: Evaluator
      Returns non-NULL if the Evaluator believes that the run is finished: perhaps an ideal individual has been found or some other run result has shortcircuited the run so that it should end prematurely right now. Typically a message is stored in the String for the user to know why the system shut down.
      Specified by:
      runComplete in class Evaluator

    • shouldEvaluateSubpop

      public boolean shouldEvaluateSubpop(EvolutionState state, int subpop, int threadnum)
      Returns true if the subpopulation should be evaluated. This will happen if the Breeder believes that the subpopulation should be breed afterwards.

    • evaluatePopulation

      public void evaluatePopulation(EvolutionState state)
      Description copied from class: Evaluator
      Evaluates the fitness of an entire population. You will have to determine how to handle multiple threads on your own, as this is a very domain-specific thing.
      Specified by:
      evaluatePopulation in class Evaluator

    • beforeCoevolutionaryEvaluation

      protected void beforeCoevolutionaryEvaluation(EvolutionState state, Population population, GroupedProblemForm prob)

    • shuffle

      protected void shuffle(EvolutionState state, int[] a)

    • performCoevolutionaryEvaluation

      public void performCoevolutionaryEvaluation(EvolutionState state, Population population, GroupedProblemForm prob)

    • producePrevious

      protected Individual producePrevious(int subpopulation, EvolutionState state, int thread)
      Selects one individual from the previous subpopulation. If there is no previous population, because we're at generation 0, then an individual from the current population is selected at random.

    • produceCurrent

      protected Individual produceCurrent(int subpopulation, EvolutionState state, int thread)
      Selects one individual from the given subpopulation.

    • afterCoevolutionaryEvaluation

      protected void afterCoevolutionaryEvaluation(EvolutionState state, GroupedProblemForm prob)