ec.gp.koza

Class CrossoverPipeline

java.lang.Object

ec.BreedingSource

ec.BreedingPipeline

ec.gp.GPBreedingPipeline

ec.gp.koza.CrossoverPipeline

All Implemented Interfaces:

Prototype, Setup, SteadyStateBSourceForm, RandomChoiceChooserD, Serializable, Cloneable

public class CrossoverPipeline
extends GPBreedingPipeline

CrossoverPipeline is a GPBreedingPipeline which performs a strongly-typed version of Koza-style "Subtree Crossover". Two individuals are selected, then a single tree is chosen in each such that the two trees have the same GPTreeConstraints. Then a random node is chosen in each tree such that each node's return type is type-compatible with the argument type of the slot in the parent which contains the other node. If by swapping subtrees at these nodes the two trees will not violate maximum depth constraints, then the trees perform the swap, otherwise, they repeat the hunt for random nodes.

The pipeline tries at most tries times to a pair of random nodes BOTH with valid swap constraints. If it cannot find any such pairs after tries times, it uses the pair of its last attempt. If either of the nodes in the pair is valid, that node gets substituted with the other node. Otherwise an individual invalid node isn't changed at all (it's "reproduced").

Compatibility with constraints. Since Koza-I/II only tries 1 time, and then follows this policy, this is compatible with Koza. lil-gp either tries 1 time, or tries forever. Either way, this is compatible with lil-gp. My hacked lil-gp kernel either tries 1 time, n times, or forever. This is compatible as well.

This pipeline typically produces up to 2 new individuals (the two newly- swapped individuals) per produce(...) call. If the system only needs a single individual, the pipeline will throw one of the new individuals away. The user can also have the pipeline always throw away the second new individual instead of adding it to the population. In this case, the pipeline will only typically produce 1 new individual per produce(...) call.

Typical Number of Individuals Produced Per produce(...) call
2 * minimum typical number of individuals produced by each source, unless tossSecondParent is set, in which case it's simply the minimum typical number.

Number of Sources
2

Parameters

base.tries int >= 1	(number of times to try finding valid pairs of nodes)
base.maxdepth int >= 1	(maximum valid depth of a crossed-over subtree)
base.maxsize int >= 1	(maximum valid size, in nodes, of a crossed-over subtree)
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.)
base.ns.n classname, inherits and != GPNodeSelector, or String same	(GPNodeSelector for parent n (n is 0 or 1) If, for ns.1 the value is same, then ns.1 a copy of whatever ns.0 is. Note that the default version has no n)
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?)

Default Base
gp.koza.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
static int	INDS_PRODUCED
int	maxDepth The deepest tree the pipeline is allowed to form.
int	maxSize The largest tree (measured as a nodecount) the pipeline is allowed to form.
static int	NO_SIZE_LIMIT
GPNodeSelector	nodeselect1 How the pipeline selects a node from individual 1
GPNodeSelector	nodeselect2 How the pipeline selects a node from individual 2
static int	NUM_SOURCES
int	numTries How many times the pipeline attempts to pick nodes until it gives up.
static String	P_CROSSOVER
static String	P_MAXDEPTH
static String	P_MAXSIZE
static String	P_NUM_TRIES
static String	P_TOSS
GPIndividual[]	parents Temporary holding place for parents
private static long	serialVersionUID
boolean	tossSecondParent Should the pipeline discard the second parent after crossing over?
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
CrossoverPipeline()

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.
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.
int	typicalIndsProduced() Returns 2 * minimum number of typical individuals produced by any sources, else 1* minimum number if tossSecondParent is true.
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

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_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

P_MAXSIZE

public static final String P_MAXSIZE

See Also:

Constant Field Values

P_CROSSOVER

public static final String P_CROSSOVER

See Also:

Constant Field Values

P_TOSS

public static final String P_TOSS

See Also:

Constant Field Values

INDS_PRODUCED

public static final int INDS_PRODUCED

See Also:

Constant Field Values

NUM_SOURCES

public static final int NUM_SOURCES

See Also:

Constant Field Values

NO_SIZE_LIMIT

public static final int NO_SIZE_LIMIT

See Also:

Constant Field Values

nodeselect1

public GPNodeSelector nodeselect1

How the pipeline selects a node from individual 1

nodeselect2

public GPNodeSelector nodeselect2

How the pipeline selects a node from individual 2

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

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.

maxSize

public int maxSize

The largest tree (measured as a nodecount) the pipeline is allowed to form.

tossSecondParent

public boolean tossSecondParent

Should the pipeline discard the second parent after crossing over?

parents

public GPIndividual[] parents

Temporary holding place for parents

Constructor Detail

CrossoverPipeline

public CrossoverPipeline()

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)

typicalIndsProduced

public int typicalIndsProduced()

Returns 2 * minimum number of typical individuals produced by any sources, else 1* minimum number if tossSecondParent is true.

Overrides:

typicalIndsProduced in class BreedingPipeline

verifyPoints

public 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