ec.gp.breed

Class InternalCrossoverPipeline

java.lang.Object

ec.BreedingSource

ec.BreedingPipeline

ec.gp.GPBreedingPipeline

ec.gp.breed.InternalCrossoverPipeline

All Implemented Interfaces:

Prototype, Setup, SteadyStateBSourceForm, RandomChoiceChooserD, Serializable, Cloneable

public class InternalCrossoverPipeline
extends GPBreedingPipeline

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
...as many as the source produces

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)

Version:

1.0

Author:

Sean Luke

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
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 String	P_INTERNALCROSSOVER
static String	P_MAXDEPTH
static String	P_NUM_TRIES
private static long	serialVersionUID
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, likelihood, mybase, P_LIKELIHOOD, P_NUMSOURCES, P_SOURCE, sources, V_SAME

Fields inherited from class ec.BreedingSource

NO_PROBABILITY, P_PROB, probability

Constructor Summary

Constructors

Constructor and Description
InternalCrossoverPipeline()

Method Summary

Methods

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.
private boolean	noContainment(GPNode inner1, GPNode inner2) Returns true if inner1 and inner2 do not contain one another
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.
void	setup(EvolutionState state, Parameter base) Sets up the BreedingPipeline.
(package private) boolean	verifyPoints(GPInitializer initializer, GPNode inner1, GPNode inner2) Returns true if inner1 can feasibly be swapped into inner2's position.

Methods inherited from class ec.gp.GPBreedingPipeline

produces

Methods inherited from class ec.BreedingPipeline

finishProducing, individualReplaced, maxChildProduction, minChildProduction, preparePipeline, prepareToProduce, reproduce, sourcesAreProperForm, typicalIndsProduced

Methods inherited from class ec.BreedingSource

getProbability, pickRandom, setProbability, setupProbabilities

Methods inherited from class java.lang.Object

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

Field Detail

serialVersionUID

private static final long serialVersionUID

See Also:

Constant Field Values

P_INTERNALCROSSOVER

public static final String P_INTERNALCROSSOVER

See Also:

Constant Field Values

P_NUM_TRIES

public static final String P_NUM_TRIES

See Also:

Constant Field Values

P_MAXDEPTH

public static final String P_MAXDEPTH

See Also:

Constant Field Values

NUM_SOURCES

public static final int NUM_SOURCES

See Also:

Constant Field Values

nodeselect0

public GPNodeSelector nodeselect0

How the pipeline chooses the first subtree

nodeselect1

public GPNodeSelector nodeselect1

How the pipeline chooses the second subtree

numTries

public int numTries

How many times the pipeline attempts to pick nodes until it gives up.

maxDepth

public int maxDepth

The deepest tree the pipeline is allowed to form. Single terminal trees are depth 1.

tree1

public int tree1

Is the first tree fixed? If not, this is -1

tree2

public int tree2

Is the second tree fixed? If not, this is -1

Constructor Detail

InternalCrossoverPipeline

public InternalCrossoverPipeline()

Method Detail

defaultBase

public Parameter defaultBase()

Description copied from interface: Prototype

Returns the default base for this prototype. This should generally be implemented by building off of the static base() method on the DefaultsForm object for the prototype's package. This should be callable during setup(...).

numSources

public int numSources()

Description copied from class: BreedingPipeline

Returns the number of sources to this pipeline. Called during BreedingPipeline's setup. Be sure to return a value > 0, or DYNAMIC_SOURCES which indicates that setup should check the parameter file for the parameter "num-sources" to make its determination.

Specified by:

numSources in class BreedingPipeline

clone

public Object clone()

Description copied from interface: Prototype

Creates a new individual cloned from a prototype, and suitable to begin use in its own evolutionary context.

Typically this should be a full "deep" clone. However, you may share certain elements with other objects rather than clone hem, depending on the situation:

• If you hold objects which are shared with other instances, don't clone them.
• If you hold objects which must be unique, clone them.
• If you hold objects which were given to you as a gesture of kindness, and aren't owned by you, you probably shouldn't clone them.
• DON'T attempt to clone: Singletons, Cliques, or Groups.
• Arrays are not cloned automatically; you may need to clone an array if you're not sharing it with other instances. Arrays have the nice feature of being copyable by calling clone() on them.

Implementations.

• If no ancestor of yours implements clone(), and you have no need to do clone deeply, and you are abstract, then you should not declare clone().
• If no ancestor of yours implements clone(), and you have no need to do clone deeply, and you are not abstract, then you should implement it as follows:

   public Object clone() 
       {
       try
           { 
           return super.clone();
           }
       catch ((CloneNotSupportedException e)
           { throw new InternalError(); } // never happens
       }
          

• If no ancestor of yours implements clone(), but you need to deep-clone some things, then you should implement it as follows:

   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;
       } 
          

• If an ancestor has implemented clone(), and you also need to deep clone some things, then you should implement it as follows:

   public Object clone() 
       { 
       MyObject myobj = (MyObject) (super.clone());
  
       // put your deep-cloning code here...
  
       return myobj;
       } 
          

Specified by:

clone in interface Prototype

Overrides:

clone in class BreedingPipeline

setup

public void setup(EvolutionState state,
         Parameter base)

Description copied from class: BreedingSource

Sets up the BreedingPipeline. You can use state.output.error here because the top-level caller promises to call exitIfErrors() after calling setup. Note that probability might get modified again by an external source if it doesn't normalize right.

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}.

Specified by:

setup in interface Prototype

Specified by:

setup in interface Setup

Overrides:

setup in class BreedingPipeline

See Also:

Prototype.setup(EvolutionState,Parameter)

noContainment

private boolean noContainment(GPNode inner1,
                    GPNode inner2)

Returns true if inner1 and inner2 do not contain one another

verifyPoints

boolean verifyPoints(GPInitializer initializer,
                   GPNode inner1,
                   GPNode inner2)

Returns true if inner1 can feasibly be swapped into inner2's position.

produce

public int produce(int min,
          int max,
          int start,
          int subpopulation,
          Individual[] inds,
          EvolutionState state,
          int thread)

Description copied from class: BreedingSource

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. max must be >= min, and min must be >= 1. For example, crossover might typically produce two individuals, tournament selection might typically produce a single individual, etc.

Specified by:

produce in class BreedingSource