public class RuleCrossoverPipeline extends BreedingPipeline
Typical Number of Individuals Produced Per produce(...) call
1 or 2
Number of Sources
2
Parameters
| base.toss bool = true or false (default)/td> | (after crossing over with the first new individual, should its second sibling individual be thrown away instead of adding it to the population?) |
| base.prob 0.0 <= double < 1.0, or 0.5 (default)/td> | (probability that a rule will cross over from one individual to the other) |
Default Base
rule.xover
| Modifier and Type | Field and Description |
|---|---|
static int |
INDS_PRODUCED |
static int |
NUM_SOURCES |
static String |
P_CROSSOVER |
static String |
P_CROSSOVERPROB |
static String |
P_TOSS |
(package private) RuleIndividual[] |
parents
Temporary holding place for parents
|
double |
ruleCrossProbability
What is the probability of a rule migrating?
|
boolean |
tossSecondParent
Should the pipeline discard the second parent after crossing over?
|
DYNAMIC_SOURCES, likelihood, mybase, P_LIKELIHOOD, P_NUMSOURCES, P_SOURCE, sources, V_SAMENO_PROBABILITY, P_PROB, probability| Constructor and Description |
|---|
RuleCrossoverPipeline() |
| Modifier and Type | Method and Description |
|---|---|
Object |
clone()
Creates a new individual cloned from a prototype,
and suitable to begin use in its own evolutionary
context.
|
Parameter |
defaultBase()
Returns the default base for this prototype.
|
int |
numSources()
Returns 2
|
int |
produce(int min,
int max,
int start,
int subpopulation,
Individual[] inds,
EvolutionState state,
int thread)
Produces n individuals from the given subpopulation
and puts them into inds[start...start+n-1],
where n = Min(Max(q,min),max), where q is the "typical" number of
individuals the BreedingSource produces in one shot, and returns
n.
|
void |
setup(EvolutionState state,
Parameter base)
Sets up the BreedingPipeline.
|
int |
typicalIndsProduced()
Returns 2 (unless tossing the second sibling, in which case it returns 1)
|
finishProducing, individualReplaced, maxChildProduction, minChildProduction, preparePipeline, prepareToProduce, produces, reproduce, sourcesAreProperFormgetProbability, pickRandom, setProbability, setupProbabilitiespublic static final String P_TOSS
public static final String P_CROSSOVER
public static final String P_CROSSOVERPROB
public static final int INDS_PRODUCED
public static final int NUM_SOURCES
public boolean tossSecondParent
public double ruleCrossProbability
RuleIndividual[] parents
public Parameter defaultBase()
Prototypepublic int numSources()
numSources in class BreedingPipelinepublic Object clone()
PrototypeTypically this should be a full "deep" clone. However, you may share certain elements with other objects rather than clone hem, depending on the situation:
Implementations.
public Object clone()
{
try
{
return super.clone();
}
catch ((CloneNotSupportedException e)
{ throw new InternalError(); } // never happens
}
public Object clone()
{
try
{
MyObject myobj = (MyObject) (super.clone());
// put your deep-cloning code here...
}
catch ((CloneNotSupportedException e)
{ throw new InternalError(); } // never happens
return myobj;
}
public Object clone()
{
MyObject myobj = (MyObject) (super.clone());
// put your deep-cloning code here...
return myobj;
}
clone in interface Prototypeclone in class BreedingPipelinepublic void setup(EvolutionState state, Parameter base)
BreedingSourceThe most common modification is to normalize it with some other set of probabilities, then set all of them up in increasing summation; this allows the use of the fast static BreedingSource-picking utility method, BreedingSource.pickRandom(...). In order to use this method, for example, if four breeding source probabilities are {0.3, 0.2, 0.1, 0.4}, then they should get normalized and summed by the outside owners as: {0.3, 0.5, 0.6, 1.0}.
setup in interface Prototypesetup in interface Setupsetup in class BreedingPipelinePrototype.setup(EvolutionState,Parameter)public int typicalIndsProduced()
typicalIndsProduced in class BreedingPipelinepublic int produce(int min,
int max,
int start,
int subpopulation,
Individual[] inds,
EvolutionState state,
int thread)
BreedingSourceproduce in class BreedingSourceCopyright © 2014 Evolutionary Computation Laboratory at George Mason University. All rights reserved.