ec.gp.breed

Class MutateSwapPipeline

java.lang.Object

ec.BreedingSource

ec.BreedingPipeline

ec.gp.GPBreedingPipeline

ec.gp.breed.MutateSwapPipeline

All Implemented Interfaces:

Prototype, Setup, SteadyStateBSourceForm, RandomChoiceChooserD, Serializable, Cloneable

public class MutateSwapPipeline
extends GPBreedingPipeline

MutateSwapPipeline works very similarly to the Swap algorithm described in Kumar Chellapilla, "A Preliminary Investigation into Evolving Modular Programs without Subtree Crossover", GP98.

MutateSwapPipeline picks a random tree, then picks randomly from all the swappable nodes in the tree, and swaps two of its subtrees. If its chosen tree has no swappable nodes, it repeats the choose-tree process. If after tries times it has failed to find a tree with swappable nodes, it gives up and simply copies the individual.

"Swapping" means to take a node n, and choose two children nodes of n, x and y, such that x's return type is swap-compatible with y's slot, and y's return type is swap-compatible with x's slot. The subtrees rooted at x and y are swapped.

A "Swappable" node means a node which is capable of swapping given the existing function set. In general to swap a node foo, it must have at least two children whose return types are type-compatible with each other's slots in foo.

This method is very expensive in searching nodes for "swappability". However, if the number of types is 1 (the GP run is typeless) then the type-constraint-checking code is bypassed and the method runs a little faster.

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.tree.0 0 < int < (num trees in individuals), if exists	(tree chosen for mutation; if parameter doesn't exist, tree is picked at random)

Default Base
gp.breed.mutate-swap

Version:

1.0

Author:

Sean Luke

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static int	NUM_SOURCES
(package private) int	numTries The number of times the pipeline tries to build a valid mutated tree before it gives up and just passes on the original
static String	P_MUTATESWAP
static String	P_NUM_TRIES
private GPNode	swappableNode
(package private) int	tree Is our 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
MutateSwapPipeline()

Method Summary

Methods

Modifier and Type	Method and Description
private void	_swapSomething(GPNode node, EvolutionState state, int thread)
private void	_swapSomethingTypeless(GPNode node, EvolutionState state, int thread)
Parameter	defaultBase() Returns the default base for this prototype.
int	numSources() Returns the number of sources to this pipeline.
private int	numSwappableNodes(GPInitializer initializer, GPNode root, int soFar)
private int	pickSwappableNode(GPInitializer initializer, GPNode root, int num)
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.
private boolean	swappable(GPInitializer initializer, GPNode node) This very expensive method (for types) might be improved in various ways I guess.
private void	swapSomething(GPNode node, EvolutionState state, int thread)

Methods inherited from class ec.gp.GPBreedingPipeline

produces

Methods inherited from class ec.BreedingPipeline

clone, 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

P_MUTATESWAP

public static final String P_MUTATESWAP

See Also:

Constant Field Values

P_NUM_TRIES

public static final String P_NUM_TRIES

See Also:

Constant Field Values

NUM_SOURCES

public static final int NUM_SOURCES

See Also:

Constant Field Values

numTries

int numTries

The number of times the pipeline tries to build a valid mutated tree before it gives up and just passes on the original

tree

int tree

Is our tree fixed? If not, this is -1

swappableNode

private GPNode swappableNode

Constructor Detail

MutateSwapPipeline

public MutateSwapPipeline()

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

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)

swappable

private boolean swappable(GPInitializer initializer,
                GPNode node)

This very expensive method (for types) might be improved in various ways I guess.

swapSomething

private void swapSomething(GPNode node,
                 EvolutionState state,
                 int thread)

_swapSomethingTypeless

private void _swapSomethingTypeless(GPNode node,
                          EvolutionState state,
                          int thread)

_swapSomething

private void _swapSomething(GPNode node,
                  EvolutionState state,
                  int thread)

numSwappableNodes

private int numSwappableNodes(GPInitializer initializer,
                    GPNode root,
                    int soFar)

pickSwappableNode

private int pickSwappableNode(GPInitializer initializer,
                    GPNode root,
                    int num)

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