xcseco
Class XCSConstants

java.lang.Object
  |
  +--xcseco.XCSConstants

All Implemented Interfaces:

java.io.Serializable

public class XCSConstants

extends java.lang.Object

implements java.io.Serializable

This class provides all relevant learning parameters for the XCS as well as other experimental settings and flags. Most parameter-names are chosen similar to the 'An Algorithmic Description of XCS' ( Butz&Wilson, IlliGAL report 2000017).

Since:

JDK1.1

Version:

XCSJava 1.0

Author:

Martin V. Butz

See Also:

Serialized Form

Field Summary

static double	alpha The fall of rate in the fitness evaluation.
static double	beta The learning rate for updating fitness, prediction, prediction error, and action set size estimate in XCS's classifiers.
static double	delta The fraction of the mean fitness of the population below which the fitness of a classifier may be considered in its vote for deletion.
static boolean	doActionSetSubsumption Specifies if action set subsumption should be executed.
static boolean	doGASubsumption Specifies if GA subsumption should be executed.
static char	dontCare The don't care symbol (normally '#')
static double	epsilon_0 The error threshold under which the accuracy of a classifier is set to one.
static double	fitnessIni The initial prediction value when generating a new classifier (e.g in covering).
static double	fitnessReduction The reduction of the fitness when generating an offspring classifier.
static double	gamma The discount rate in multi-step problems.
static int	maxPopSize Specifies the maximal number of micro-classifiers in the population.
static double	nu Specifies the exponent in the power function for the fitness evaluation.
static double	P_dontcare The probability of using a don't care symbol in an allele when covering.
static double	pM The probability of mutating one allele and the action in an offspring classifier.
static double	predictionErrorIni The initial prediction error value when generating a new classifier (e.g in covering).
static double	predictionErrorReduction The reduction of the prediction error when generating an offspring classifier.
static double	predictionIni The initial prediction value when generating a new classifier (e.g in covering).
static double	pX The probability of applying crossover in an offspring classifier.
static boolean	setupDone Checks if the setup of the constants has already been done.
static int	teletransportation The maximal number of steps executed in one trial in a multi-step problem.
static int	theta_del Specified the threshold over which the fitness of a classifier may be considered in its deletion probability.
static double	theta_GA The threshold for the GA application in an action set.
static double	theta_sub The experience of a classifier required to be a subsumer.

Constructor Summary

XCSConstants()
The default constructor.

Method Summary

static double	drand() Returns a random number in between zero and one.
static void	setSeed(long s) Sets a random seed in order to randomize the pseudo random generator.

Methods inherited from class java.lang.Object

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

Field Detail

setupDone

public static boolean setupDone

Checks if the setup of the constants has already been done.

maxPopSize

public static int maxPopSize

Specifies the maximal number of micro-classifiers in the population. In the multiplexer problem this value is set to 400, 800, 2000 in the 6, 11, 20 multiplexer resp.. In the Woods1 and Woods2 environment the parameter was set to 800.

alpha

public static double alpha

The fall of rate in the fitness evaluation.

beta

public static double beta

The learning rate for updating fitness, prediction, prediction error, and action set size estimate in XCS's classifiers.

gamma

public static double gamma

The discount rate in multi-step problems.

delta

public static double delta

The fraction of the mean fitness of the population below which the fitness of a classifier may be considered in its vote for deletion.

nu

public static final double nu

Specifies the exponent in the power function for the fitness evaluation.

theta_GA

public static double theta_GA

The threshold for the GA application in an action set.

epsilon_0

public static final double epsilon_0

The error threshold under which the accuracy of a classifier is set to one.

theta_del

public static int theta_del

Specified the threshold over which the fitness of a classifier may be considered in its deletion probability.

pX

public static double pX

The probability of applying crossover in an offspring classifier.

pM

public static double pM

The probability of mutating one allele and the action in an offspring classifier.

P_dontcare

public static double P_dontcare

The probability of using a don't care symbol in an allele when covering.

predictionErrorReduction

public static final double predictionErrorReduction

The reduction of the prediction error when generating an offspring classifier.

fitnessReduction

public static final double fitnessReduction

The reduction of the fitness when generating an offspring classifier.

theta_sub

public static double theta_sub

The experience of a classifier required to be a subsumer.

teletransportation

public static final int teletransportation

The maximal number of steps executed in one trial in a multi-step problem.

doGASubsumption

public static final boolean doGASubsumption

Specifies if GA subsumption should be executed.

doActionSetSubsumption

public static final boolean doActionSetSubsumption

Specifies if action set subsumption should be executed.

predictionIni

public static double predictionIni

The initial prediction value when generating a new classifier (e.g in covering).

predictionErrorIni

public static double predictionErrorIni

The initial prediction error value when generating a new classifier (e.g in covering).

fitnessIni

public static double fitnessIni

The initial prediction value when generating a new classifier (e.g in covering).

dontCare

public static final char dontCare

The don't care symbol (normally '#')

Constructor Detail

XCSConstants

public XCSConstants()

The default constructor.

Method Detail

setSeed

public static void setSeed(long s)

Sets a random seed in order to randomize the pseudo random generator.

drand

public static double drand()

Returns a random number in between zero and one.