public class Uniform extends GPNodeBuilder
Bohm, Walter and Andreas Geyer-Schulz. 1996. "Exact Uniform Initialization for Genetic Programming". In Foundations of Genetic Algorithms IV, Richard Belew and Michael Vose, eds. Morgan Kaufmann. 379-407. (ISBN 1-55860-460-X)
The user-provided requested tree size is either provided directly to the Uniform algorithm, or if the size is NOSIZEGIVEN, then Uniform will pick one at random from the GPNodeBuilder probability distribution system (using either max-depth and min-depth, or using num-sizes).
Further, if the user sets the true-dist parameter, the Uniform will ignore the user's specified probability distribution and instead pick from a distribution between the minimum size and the maximum size the user specified, where the sizes are distributed according to the actual number of trees that can be created with that size. Since many more trees of size 10 than size 3 can be created, for example, size 10 will be picked that much more often.
Uniform also prints out the actual number of trees that exist for a given size, return type, and function set. As if this were useful to you. :-)
The algorithm, which is quite complex, is described in pseudocode below. Basically what the algorithm does is this:
Dealing with Zero Distributions
Some domains have NO tree of a certain size. For example, Artificial Ant's function set can make NO trees of size 2. What happens when we're asked to make a tree of (invalid) size 2 in Artificial Ant then? Uniform presently handles it as follows:
Func NumTreesOfType(type,size)
If NUMTREESOFTYPE[type,size] not defined, // memoize
N[type] = all nodes compatible with type
NUMTREESOFTYPE[type,size] = Sum(n in N[type], NumTreesRootedByNode(n,size))
return NUMTREESOFTYPE[type,size]
Func NumTreesRootedByNode(node,size)
If NUMTREESROOTEDBYNODE[node,size] not defined, // memoize
count = 0
left = size - 1
If node.children.length = 0 and left = 0 // a valid terminal
count = 1
Else if node.children.length <= left // a valid nonterminal
For s is 1 to left inclusive // yeah, that allows some illegal stuff, it gets set to 0
count += NumChildPermutations(node,s,left,0)
NUMTREESROOTEDBYNODE[node,size] = count
return NUMTREESROOTEBYNODE[node,size]
Func NumChildPermutations(parent,size,outof,pickchild)
// parent is our parent node
// size is the size of pickchild's tree that we're considering
// pickchild is the child we're considering
// outof is the total number of remaining nodes (including size) yet to fill
If NUMCHILDPERMUTATIONS[parent,size,outof,pickchild] is not defined, // memoize
count = 0
if pickchild = parent.children.length - 1 and outof==size // our last child, outof must be size
count = NumTreesOfType(parent.children[pickchild].type,size)
else if pickchild < parent.children.length - 1 and
outof-size >= (parent.children.length - pickchild-1) // maybe we can fill with terminals
cval = NumTreesOfType(parent.children[pickchild].type,size)
tot = 0
For s is 1 to outof-size // some illegal stuff, it gets set to 0
tot += NumChildPermutations(parent,s,outof-size,pickchild+1)
count = cval * tot
NUMCHILDPERMUTATIONS [parent,size,outof,pickchild] = count
return NUMCHILDPERMUTATIONS[parent,size,outof,pickchild]
For each type type, size size
ROOT_D[type,size] = probability distribution of nodes of type and size, derived from
NUMTREESOFTYPE[type,size], our node list, and NUMTREESROOTEDBYNODE[node,size]
For each parent,outof,pickchild
CHILD_D[parent,outof,pickchild] = probability distribution of tree sizes, derived from
NUMCHILDPERMUTATIONS[parent,size,outof,pickchild]
Func FillNodeWithChildren(parent,pickchild,outof)
If pickchild = parent.children.length - 1 // last child
Fill parent.children[pickchild] with CreateTreeOfType(parent.children[pickchild].type,outof)
Else choose size from CHILD_D[parent,outof,pickchild]
Fill parent.pickchildren[pickchild] with CreateTreeOfType(parent.children[pickchild].type,size)
FillNodeWithChildren(parent,pickchild+1,outof-size)
return
Func CreateTreeOfType(type,size)
Choose node from ROOT_D[type,size]
If size > 1
FillNodeWithChildren(node,0,size-1)
return node
Parameters
| base.true-dist bool= true or false (default) |
(should we use the true numbers of trees for each size as the distribution for picking trees, as opposed to the user-specified distribution?) |
Default Base
gp.build.uniform
| Modifier and Type | Field and Description |
|---|---|
Hashtable |
_functionsets |
BigInteger[][][] |
_truesizes |
double[][][][][] |
CHILD_D |
Hashtable |
funcnodes |
GPFunctionSet[] |
functionsets |
int |
maxarity |
int |
maxtreesize |
BigInteger[][][][][] |
NUMCHILDPERMUTATIONS |
int |
numfuncnodes |
BigInteger[][][] |
NUMTREESOFTYPE |
BigInteger[][][] |
NUMTREESROOTEDBYNODE |
static String |
P_TRUEDISTRIBUTION |
static String |
P_UNIFORM |
UniformGPNodeStorage[][][][] |
ROOT_D |
boolean[][][] |
ROOT_D_ZERO |
double[][][] |
truesizes |
boolean |
useTrueDistribution |
CHECK_BOUNDARY, maxSize, minSize, NOSIZEGIVEN, P_MAXSIZE, P_MINSIZE, P_NUMSIZES, P_SIZE, sizeDistribution| Constructor and Description |
|---|
Uniform() |
| Modifier and Type | Method and Description |
|---|---|
void |
computePercentages() |
(package private) GPNode |
createTreeOfType(EvolutionState state,
int thread,
GPInitializer initializer,
int functionset,
int type,
int size,
MersenneTwisterFast mt) |
Parameter |
defaultBase()
Returns the default base for this prototype.
|
(package private) void |
fillNodeWithChildren(EvolutionState state,
int thread,
GPInitializer initializer,
int functionset,
GPNode parent,
GPNode parentc,
int pickchild,
int outof,
MersenneTwisterFast mt) |
private double |
getProb(BigInteger i) |
int |
intForNode(GPNode node) |
GPNode |
newRootedTree(EvolutionState state,
GPType type,
int thread,
GPNodeParent parent,
GPFunctionSet set,
int argposition,
int requestedSize) |
BigInteger |
numChildPermutations(GPInitializer initializer,
int functionset,
GPNode parent,
int size,
int outof,
int pickchild) |
BigInteger |
numTreesOfType(GPInitializer initializer,
int functionset,
int type,
int size) |
BigInteger |
numTreesRootedByNode(GPInitializer initializer,
int functionset,
GPNode node,
int size) |
int |
pickSize(EvolutionState state,
int thread,
int functionset,
int type) |
void |
preprocess(EvolutionState state,
int _maxtreesize) |
void |
setup(EvolutionState state,
Parameter base)
Sets up the object by reading it from the parameters stored
in state, built off of the parameter base base.
|
canPick, clone, errorAboutNoNodeWithType, pickSize, warnAboutNonterminal, warnAboutNonTerminalWithType, warnAboutNoTerminalWithTypepublic static final String P_UNIFORM
public static final String P_TRUEDISTRIBUTION
public GPFunctionSet[] functionsets
public Hashtable _functionsets
public Hashtable funcnodes
public int numfuncnodes
public int maxarity
public int maxtreesize
public BigInteger[][][] _truesizes
public double[][][] truesizes
public boolean useTrueDistribution
public BigInteger[][][] NUMTREESOFTYPE
public BigInteger[][][] NUMTREESROOTEDBYNODE
public BigInteger[][][][][] NUMCHILDPERMUTATIONS
public UniformGPNodeStorage[][][][] ROOT_D
public boolean[][][] ROOT_D_ZERO
public double[][][][][] CHILD_D
public Parameter defaultBase()
Prototypepublic void setup(EvolutionState state, Parameter base)
PrototypeFor prototypes, setup(...) is typically called once for the prototype instance; cloned instances do not receive the setup(...) call. setup(...) may be called more than once; the only guarantee is that it will get called at least once on an instance or some "parent" object from which it was ultimately cloned.
public int pickSize(EvolutionState state, int thread, int functionset, int type)
public void preprocess(EvolutionState state, int _maxtreesize)
public final int intForNode(GPNode node)
public BigInteger numTreesOfType(GPInitializer initializer, int functionset, int type, int size)
public BigInteger numTreesRootedByNode(GPInitializer initializer, int functionset, GPNode node, int size)
public BigInteger numChildPermutations(GPInitializer initializer, int functionset, GPNode parent, int size, int outof, int pickchild)
private final double getProb(BigInteger i)
public void computePercentages()
GPNode createTreeOfType(EvolutionState state, int thread, GPInitializer initializer, int functionset, int type, int size, MersenneTwisterFast mt)
void fillNodeWithChildren(EvolutionState state, int thread, GPInitializer initializer, int functionset, GPNode parent, GPNode parentc, int pickchild, int outof, MersenneTwisterFast mt)
public GPNode newRootedTree(EvolutionState state, GPType type, int thread, GPNodeParent parent, GPFunctionSet set, int argposition, int requestedSize)
newRootedTree in class GPNodeBuilderCopyright © 2014 Evolutionary Computation Laboratory at George Mason University. All rights reserved.