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SUMMARY: INNER | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object | +--ec.BreedingSource | +--ec.BreedingPipeline | +--ec.gp.GPBreedingPipeline | +--ec.gp.breed.InternalCrossoverPipeline
InternalCrossoverPipeline picks two subtrees from somewhere within an individual, and crosses them over. Before doing so, it checks to make sure that the subtrees come from trees with the same tree constraints, that the subtrees are swap-compatible with each other, that the new individual does not violate depth constraints, and that one subtree does not contain the other. It tries tries times to find a valid subtree pair to cross over. Failing this, it just copies the individual.
Typical Number of Individuals Produced Per produce(...) call
1
Number of Sources
1
Parameters
base.tries int >= 1 |
(number of times to try finding valid pairs of nodes) |
base.maxdepth int >= 1 |
(maximum valid depth of the crossed-over individual's trees) |
base.ns.0 classname, inherits and != GPNodeSelector |
(GPNodeSelector for subtree 0. |
base.ns.1 classname, inherits and != GPNodeSelector, or String same |
(GPNodeSelector for subtree 1. If value is same, then ns.1 a copy of whatever ns.0 is) |
base.tree.0 0 < int < (num trees in individuals), if exists |
(first tree for the crossover; if parameter doesn't exist, tree is picked at random) |
base.tree.1 0 < int < (num trees in individuals), if exists |
(second tree for the crossover; if parameter doesn't exist, tree is picked at random. This tree must have the same GPTreeConstraints as tree.0, if tree.0 is defined.) |
Default Base
gp.breed.internal-xover
Parameter bases
base.ns.n | nodeselectn (n is 0 or 1) |
Field Summary | |
static int |
INDS_PRODUCED
|
int |
maxDepth
The deepest tree the pipeline is allowed to form. |
GPNodeSelector |
nodeselect0
How the pipeline chooses the first subtree |
GPNodeSelector |
nodeselect1
How the pipeline chooses the second subtree |
static int |
NUM_SOURCES
|
int |
numTries
How many times the pipeline attempts to pick nodes until it gives up. |
static java.lang.String |
P_INTERNALCROSSOVER
|
static java.lang.String |
P_MAXDEPTH
|
static java.lang.String |
P_NUM_TRIES
|
int |
tree1
Is the first tree fixed? If not, this is -1 |
int |
tree2
Is the second tree fixed? If not, this is -1 |
Fields inherited from class ec.gp.GPBreedingPipeline |
P_NODESELECTOR,
P_TREE,
TREE_UNFIXED |
Fields inherited from class ec.BreedingPipeline |
DYNAMIC_SOURCES,
P_NUMSOURCES,
P_SOURCE,
sources,
V_SAME |
Fields inherited from class ec.BreedingSource |
CHECKBOUNDARY,
DEFAULT_PRODUCED,
NO_PROBABILITY,
P_PROB,
probability,
UNUSED |
Constructor Summary | |
InternalCrossoverPipeline()
|
Method Summary | |
Parameter |
defaultBase()
Returns the default base for this prototype. |
int |
numSources()
Returns the number of sources to this pipeline. |
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. |
java.lang.Object |
protoClone()
Creates a new individual cloned from a prototype, and suitable to begin use in its own evolutionary context. |
void |
setup(EvolutionState state,
Parameter base)
Sets up the BreedingPipeline. |
int |
typicalIndsProduced()
Returns the "typical" number of individuals generated with one call of produce(...) -- by default this is set to 1; you should override this if 1 is not appropriate. |
Methods inherited from class ec.gp.GPBreedingPipeline |
produces |
Methods inherited from class ec.BreedingPipeline |
preparePipeline,
prepareToProduce |
Methods inherited from class ec.BreedingSource |
getProbability,
pickRandom,
protoCloneSimple,
setProbability,
setupProbabilities |
Methods inherited from class java.lang.Object |
clone,
equals,
finalize,
getClass,
hashCode,
notify,
notifyAll,
toString,
wait,
wait,
wait |
Field Detail |
public static final java.lang.String P_INTERNALCROSSOVER
public static final java.lang.String P_NUM_TRIES
public static final java.lang.String P_MAXDEPTH
public static final int NUM_SOURCES
public static final int INDS_PRODUCED
public GPNodeSelector nodeselect0
public GPNodeSelector nodeselect1
public int numTries
public int maxDepth
public int tree1
public int tree2
Constructor Detail |
public InternalCrossoverPipeline()
Method Detail |
public Parameter defaultBase()
public int numSources()
public int typicalIndsProduced()
public java.lang.Object protoClone() throws java.lang.CloneNotSupportedException
The question here is whether or not this means to perform a "deep" or "light" ("shallow") clone, or something in-between. You may need to deep-clone parts of your object rather than simply copying their references, depending on the situation:
Implementations.
public Object protoClone() throws CloneNotSupportedException
{
return super.clone();
}
public Object protoClone() throws CloneNotSupportedException
{
myobj = (MyObject) (super.clone());
// put your deep-cloning code here...
// ...you should use protoClone and not
// protoCloneSimple to clone subordinate objects...
return myobj;
}
public Object protoClone() throws CloneNotSupportedException
{
MyObject myobj = (MyObject)(super.protoClone());
// put your deep-cloning code here...
// ...you should use protoClone and not
// protoCloneSimple to clone subordinate objects...
return myobj;
}
If you know that your superclasses will never change their protoClone() implementations, you might try inlining them in your overridden protoClone() method. But this is dangerous (though it yields a small net increase).
In general, you want to keep your deep cloning to an absolute minimum, so that you don't have to call protoClone() but one time.
The approach taken here is the fastest that I am aware of while still permitting objects to be specified at runtime from a parameter file. It would be faster to use the "new" operator; but that would require hard-coding that we can't do. Although using java.lang.Object.clone() entails an extra layer that deals with stripping away the "protected" keyword and also wrapping the exception handling (which is a BIG hit, about three times as slow as using "new"), it's still MUCH faster than using java.lang.Class.newInstance(), and also much faster than rolling our own Clone() method.
public void setup(EvolutionState state, Parameter base)
The 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}.
Prototype.setup(EvolutionState,Parameter)
public int produce(int min, int max, int start, int subpopulation, Individual[] inds, EvolutionState state, int thread) throws java.lang.CloneNotSupportedException
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