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java.lang.Object | +--ec.BreedingSource | +--ec.BreedingPipeline | +--ec.gp.GPBreedingPipeline | +--ec.gp.breed.MutateSwapPipeline
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
1
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
Field Summary | |
static int |
INDS_PRODUCED
|
static int |
NUM_SOURCES
|
static java.lang.String |
P_MUTATESWAP
|
static java.lang.String |
P_NUM_TRIES
|
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 | |
MutateSwapPipeline()
|
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. |
void |
setup(EvolutionState state,
Parameter base)
Sets up the BreedingPipeline. |
int |
typicalIndsProduced()
Returns 1 |
Methods inherited from class ec.gp.GPBreedingPipeline |
produces |
Methods inherited from class ec.BreedingPipeline |
preparePipeline,
prepareToProduce,
protoClone |
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_MUTATESWAP
public static final java.lang.String P_NUM_TRIES
public static final int INDS_PRODUCED
public static final int NUM_SOURCES
Constructor Detail |
public MutateSwapPipeline()
Method Detail |
public Parameter defaultBase()
public int numSources()
public int typicalIndsProduced()
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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