ec.coevolve

Class MultiPopCoevolutionaryEvaluator

java.lang.Object

ec.Evaluator

ec.coevolve.MultiPopCoevolutionaryEvaluator

All Implemented Interfaces:

Setup, Singleton, java.io.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-elites int >= 0	(the number of elite 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 )

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Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static java.lang.String	P_NUM_ELITE
static java.lang.String	P_NUM_IND
static java.lang.String	P_NUM_RAND_IND
static java.lang.String	P_NUM_SHUFFLED
static java.lang.String	P_SELECTION_METHOD_CURRENT
static java.lang.String	P_SELECTION_METHOD_PREV
static java.lang.String	P_SUBPOP

Fields inherited from class ec.Evaluator

masterproblem, P_IAMSLAVE, P_MASTERPROBLEM, p_problem, P_PROBLEM

Constructor Summary

Constructors

Constructor and Description
MultiPopCoevolutionaryEvaluator()

Method Summary

Modifier and Type	Method and Description
void	evaluatePopulation(EvolutionState state) Evaluates the fitness of an entire population.
void	performCoevolutionaryEvaluation(EvolutionState state, Population population, GroupedProblemForm prob)
boolean	runComplete(EvolutionState state) Returns true if an ideal individual has been found or some other run result has shortcircuited the run so that it should end prematurely right now.
void	setup(EvolutionState state, Parameter base) Sets up the object by reading it from the parameters stored in state, built off of the parameter base base.
boolean	shouldEvaluateSubpop(EvolutionState state, int subpop, int threadnum) Returns true if the subpopulation should be evaluated.

Methods inherited from class ec.Evaluator

closeContacts, initializeContacts, reinitializeContacts

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

P_SUBPOP

public static final java.lang.String P_SUBPOP

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Constant Field Values

P_NUM_RAND_IND

public static final java.lang.String P_NUM_RAND_IND

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Constant Field Values

P_NUM_SHUFFLED

public static final java.lang.String P_NUM_SHUFFLED

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Constant Field Values

P_NUM_ELITE

public static final java.lang.String P_NUM_ELITE

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Constant Field Values

P_NUM_IND

public static final java.lang.String P_NUM_IND

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Constant Field Values

P_SELECTION_METHOD_PREV

public static final java.lang.String P_SELECTION_METHOD_PREV

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Constant Field Values

P_SELECTION_METHOD_CURRENT

public static final java.lang.String P_SELECTION_METHOD_CURRENT

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Constant Field Values

Constructor Detail

MultiPopCoevolutionaryEvaluator

public MultiPopCoevolutionaryEvaluator()

Method Detail

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 boolean runComplete(EvolutionState state)

Description copied from class: Evaluator

Returns true if an ideal individual has been found or some other run result has shortcircuited the run so that it should end prematurely right now.

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

performCoevolutionaryEvaluation

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