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A B C D E F G I L M N O P R S T U W X _

A

action - Variable in class XClassifier
The action of this classifier.
actionSetSize - Variable in class XClassifier
The action set size estimate of the classifier.
actualizeCounter() - Method in class Slot
Actualize the indicator of inputs.
actualizeTime() - Method in class Slot
Counts the time spent in the address book by an agent
addBestAnswerToPopulation(XClassifier, XClassifierSet) - Method in class XClassifierSet
Once a classifier has been selected after communication, it is added to the population of classifiers of the asking agent.
addClassifier(XClassifier) - Method in class XClassifierSet
Adds a classifier to the set and increases the numerositySum value accordingly.
addNumerosity(int) - Method in class XClassifier
Adds to the numerosity of the classifier.
address - Variable in class Slot
the address of an agent in the address book
addressBook - Variable in class Agent
The address book of the agent
addressSet - Variable in class Book
the array of addresses, each slot containing the name of an agent and its exchange activity record.
addressSetSize - Variable in class Book
the size of the address book
addToAddressBook(Agent) - Method in class Book
Add an agent to the address book if it participates in the communication
addValues(XClassifier) - Method in class XClassifierSet
Increases the numerositySum value with the numerosity of the classifier.
addXClassifierToPopulation(XClassifier) - Method in class XClassifierSet
Adds the classifier to the population and checks if an identical classifier exists.
affiche(int[][], PrintWriter) - Method in class AgentsPopulations
Prints the matrix of relationships into the outfile
agent - Variable in class Slot
an agent
Agent - class Agent.
This class is an agent, containing the main loop of the XCS and handling communications.
Agent() - Constructor for class Agent
Constructs the XCS system of the agent.
agentSet - Variable in class AgentsPopulations
The list of agents
AgentsPopulations - class AgentsPopulations.
Title : communities of practice Description : Model emergence of communities of practice from heterogeneous interacting agents Copyright : Copyright (c) Olivier Dupouet, Murat Yildizoglu
AgentsPopulations(int, Environment, String, String) - Constructor for class AgentsPopulations
Constructor for the initial population of agents
agSet - Variable in class AgentsPopulations
The created agents list for purpose of communication
alpha - Static variable in class XCSConstants
The fall of rate in the fitness evaluation.
answer(String, XClassifierSet, int) - Method in class Agent
The method used by agents to answer the question.
applyMutation(String, int) - Method in class XClassifier
Applies a niche mutation to the classifier.
askAgentsAtRandom(AgentsPopulations, String, Environment, XClassifierSet, int) - Method in class Agent
This method asks agents randomly chosen in the population to answer the question. 10% of the whole population is selected.
askAgentsInAddressBook(AgentsPopulations, Environment, String, XClassifierSet, int) - Method in class Agent
This method asks to each agent in the address book to try to answer the question.
averErr - Variable in class Agent
initialization of the average performance fitness and prediction error of the agent's population of classifiers
averExp - Variable in class Agent
initialization of the average performance fitness and prediction error of the agent's population of classifiers
averFit - Variable in class Agent
initialization of the average performance fitness and prediction error of the agent's population of classifiers
averPerf - Variable in class Agent
initialization of the average performance fitness and prediction error of the agent's population of classifiers

B

bestActionWinner() - Method in class PredictionArray
Selects the action in the prediction array with the best value.
bestClassifier - Variable in class Agent
The classifier selected for communication
beta - Static variable in class XCSConstants
The learning rate for updating fitness, prediction, prediction error, and action set size estimate in XCS's classifiers.
bits - Variable in class Square
the number of bits used to code the variables in binaries
Book - class Book.
This class is the address book an agent maintains in order to communicate and build its "community.
Book(AgentsPopulations) - Constructor for class Book
construct an address book
buildRelationships(int[][]) - Method in class AgentsPopulations
Constructs the matrix of the relationships between agents stored in the out file at the end of each experiment

C

car - Variable in class Square
The different variables are stored in an array of integers.
checkAgent(int) - Method in class Agent
Checks that 1) the agent does not choose itself 2) the agents does not choose an agent already in its address book
checkRand(int[], int) - Method in class Agent
Checks that a random number is not drawn twice in one single process
chooseAgents(int, AgentsPopulations) - Method in class Agent
Build an array of randomly chosen agents.
classifierSetVariables(double, int) - Method in class XClassifier
Sets the initial variables of a new classifier.
cllSize - Variable in class XClassifierSet
The actual number of macro-classifiers in the list (which is in fact equal to the number of entries in the array).
clSet - Variable in class XClassifierSet
The classifier list (in form of an array)
computeCliquishness(int[][]) - Method in class AgentsPopulations
Computes the average cliquishness of the graph derived from the matrix of relationships
computeDispersion() - Method in class XClassifierSet
Computes the dispersion of classifiers in the population, that is the sum of variances along the X axis and variance along Y axis
computeDistance(String, String) - Method in interface Environment
Compute the distance between the signal and the most remote classifier from the signal.
computeDistance(String, String) - Method in class Square
Computes the distance between two points in the problem space.
computeMinDistance(Environment, String, double) - Method in class XClassifierSet
Computes the minimum distance between a classifier and the centre of the competence of an agent
computePerformance(double[]) - Method in class AgentsPopulations
Computes the average performance of the population of agents based on the performance of the responding agents at each signal.
computeSize(int[]) - Method in class AgentsPopulations
Computes the size of the neignborhood of an agent
computeVariance(int[]) - Method in class XClassifierSet
Computes variance along one dimension (X or Y)
condition - Variable in class XClassifier
The condition of this classifier.
confirmClassifiersInSet() - Method in class XClassifierSet
Updates the numerositySum of the set and deletes all classifiers with numerosity 0.
conLength - Static variable in class Square
Specifies the length of each presented problem.
cons - Static variable in class XClassifier
An instance of the learning parameters in XCSJava.
cons - Static variable in class XClassifierSet
The cons parameter is necessary for all kinds of calculations in the set.
cons - Static variable in class AgentsPopulations
Stores the relevant constants for XCS.
cons - Static variable in class Agent
Stores the relevant constants for XCS.
cons - Static variable in class Square
Stores the relevant constants for XCS.
containsClassifier(XClassifier) - Method in class XClassifierSet
Returns the position of the classifier in the set if it is present and -1 otherwise.
correct - Variable in class Square
Stores if the last classification was correct.
countEdges(int[][], int[], int) - Method in class AgentsPopulations
Count the number of links existing between the agents belonging to the same neignborhood
createMatchingCondition(String) - Method in class XClassifier
Creates a matching condition considering the constant P_dontcare<\code>.
createRandomAction(int) - Method in class XClassifier
Creates a random action.
createRandomCondition(int) - Method in class XClassifier
Creates a condition randomly considering the constant P_dontcare<\code>.
currentState - Variable in class Square
Stores the current problem.

D

decode(char[], int) - Method in class XClassifierSet
Turns a binary string into an integer
deleteAddress(Slot) - Method in class Book
delete an agent from the address book if it has not exchanged 5 times in a raw.
deleteFromPopulation() - Method in class XClassifierSet
Deletes one classifier in the population.
delta - Static variable in class XCSConstants
The fraction of the mean fitness of the population below which the fitness of a classifier may be considered in its vote for deletion.
distLevelOne - Variable in class Agent
threshold distance from the central competence of agents for signals and GA
distLevelTwo - Variable in class Agent
threshold distance from the core competence to accept communication
doActionSetSubsumption - Static variable in class XCSConstants
Specifies if action set subsumption should be executed.
doActionSetSubsumption() - Method in class XClassifierSet
Executes action set subsumption.
doGASubsumption - Static variable in class XCSConstants
Specifies if GA subsumption should be executed.
dontCare - Static variable in class XCSConstants
The don't care symbol (normally '#')
doOneSingleStepExperiment(PrintWriter, PrintWriter) - Method in class AgentsPopulations
Executes one single-step experiment monitoring the performance.
doOneSingleStepProblemExplore(String, int, AgentsPopulations) - Method in class Agent
Executes one main learning loop for a single step problem.
doReset() - Method in interface Environment
Returns if the agent has reached the end of a problem.
doReset() - Method in class Square
Returns true after the current problem was classified
drand() - Static method in class XCSConstants
Returns a random number in between zero and one.

E

edgeSquare - Variable in class Square
Edge of the square problem
elementAt(int) - Method in class XClassifierSet
Returns the classifier at the specified position.
encode(int) - Method in class Square
turn an integer into a binary
env - Variable in class AgentsPopulations
Stores the posed problem.
Environment - interface Environment.
This is the interface that must be implemented by all problems presented to the XCSJava implementation.
epsilon_0 - Static variable in class XCSConstants
The error threshold under which the accuracy of a classifier is set to one.
equals(XClassifier) - Method in class XClassifier
Returns if the two classifiers are identical in condition and action.
exchangeCounter - Variable in class Slot
the counter keeping track of the exchange occuring with one agent
exchangedCl - Variable in class Slot
 
executeAction(int) - Method in interface Environment
Executes an action in the environment.
executeAction(int) - Method in class Square
Executes the action and determines the reward.
experience - Variable in class XClassifier
The experience of the classifier.

F

fitness - Variable in class XClassifier
The fitness of the classifier in terms of the macro-classifier.
fitnessIni - Static variable in class XCSConstants
The initial prediction value when generating a new classifier (e.g in covering).
fitnessReduction - Static variable in class XCSConstants
The reduction of the fitness when generating an offspring classifier.

G

gamma - Static variable in class XCSConstants
The discount rate in multi-step problems.
generateSituation() - Method in class Square
Generates the values of the variables constituting the current state
getAccuracy() - Method in class XClassifier
Returns the accuracy of the classifier.
getAction() - Method in class XClassifier
Returns the action of the classifier.
getActionSetSize() - Method in class XClassifier
Returns the size of the action set
getAddBookSize() - Method in class Book
return the size of the address book
getAddress() - Method in class Slot
Returns the name of an agent stored at a given place in the address book
getAddressBook() - Method in class Agent
return the address book of the agent
getAddressSet() - Method in class Book
return the set of agents in the address book
getAgentSet() - Method in class AgentsPopulations
return the population of agents considered
getAnswer() - Method in class Slot
Returns the classifier passed from one agent to another.
getAnswerSet() - Method in class XClassifierSet
returns the array of answering classifiers
getAverageExperience() - Method in class XClassifierSet
Returns the average experience of the classifier set
getAverageFitness() - Method in class XClassifierSet
Returns the average Fitness of the classifier set
getAveragePerformance() - Method in class XClassifierSet
Returns the average performance of the classifier set
getAveragePredictionError() - Method in class XClassifierSet
Returns the average error of the classifier set
getBestValue() - Method in class PredictionArray
Returns the highest value in the prediction array.
getCollAnsSize() - Method in class XClassifierSet
returns the number of answers in the array used to pass the answers from one agent to another
getCondition() - Method in class XClassifier
Returns the condition part of the classifier
getConditionLength() - Method in interface Environment
Returns the length of the coded situations.
getConditionLength() - Method in class Square
Returns the problem length
getCurrentState() - Method in interface Environment
Returns the current situation.
getCurrentState() - Method in class Square
Returns the current problem
getDelProp(double) - Method in class XClassifier
Returns the vote for deletion of the classifier.
getDelProp(double, double) - Method in class XClassifier
Returns the vote for deletion of the classifier (second method).
getExchangeCounter() - Method in class Slot
Returns the exchange counter
getExperience() - Method in class XClassifier
Returns the age of the classifier
getExperienceSum() - Method in class XClassifierSet
Returns the sum of experiences in the population of classifiers
getFitness() - Method in class XClassifier
Returns the fitness of the classifier.
getFitnessSum() - Method in class XClassifierSet
Returns the sum of the fitnesses of all classifiers in the set.
getIdenticalClassifier(XClassifier) - Method in class XClassifierSet
Looks for an identical classifier in the population.
getMaxPayoff() - Method in interface Environment
Returns the maximal payoff receivable in an environment.
getMaxPayoff() - Method in class Square
Returns the maximal payoff possible in the current multiplexer problem.
getName() - Method in class Agent
Return the name of the agent
getNbVar() - Method in class Square
Returns the number of variables comprised in the problem
getNrActions() - Method in interface Environment
Returns the number of possible actions in the environment
getNrActions() - Method in class Square
Returns the number of possible actions.
getNumerosity() - Method in class XClassifier
Returns the numerosity of the classifier.
getNumerositySum() - Method in class XClassifierSet
Return the numerosity of the population of classifiers of one agent
getPerformance() - Method in class Agent
return the reward received by the agent
getPopulation() - Method in class Agent
Return the population of rules of an agent
getPrediction() - Method in class XClassifier
Returns the prediction of the classifier.
getPredictionError() - Method in class XClassifier
Returns the prediction error of the classifier.
getPredictionErrorSum() - Method in class XClassifierSet
Returns the sum of errors in the population of classifiers
getPredictionSum() - Method in class XClassifierSet
Returns the sum of the prediction values of all classifiers in the set.
getProblemSurface() - Method in interface Environment
Returns the size of the problem space
getProblemSurface() - Method in class Square
Returns the edge of the surface of the square problem space
getSet() - Method in class AgentsPopulations
return the population of agents considered during a communication process
getSize() - Method in class XClassifierSet
Returns the number of macro-classifiers in the set.
getTime() - Method in class Slot
Returns the time spent by an agent in an address book.
getTimeStamp() - Method in class XClassifier
Returns the time stamp of the classifier.
getTimeStampAverage() - Method in class XClassifierSet
Returns the average of the time stamps in the set.
getTimeStampSum() - Method in class XClassifierSet
Returns the sum of the time stamps of all classifiers in the set.
getValue(int) - Method in class PredictionArray
Returns the value of the specified entry in the prediction array.
gpop - Variable in class Agent
Stores the current population of XCS.

I

increaseExperience() - Method in class XClassifier
Increases the Experience of the classifier by one.
increaseNumerositySum(int) - Method in class XClassifierSet
Increases recursively all numerositySum values in the set and all parent sets.
increaseSize() - Method in class XClassifierSet
update the size of the array of answers collected
initExVal - Variable in class Slot
The number of runs without answer allowed to an agent in the address book before to delete it
insertDiscoveredXClassifiers(XClassifier, XClassifier, XClassifier) - Method in class XClassifierSet
Inserts both discovered classifiers keeping the maximal size of the population and possibly doing GA subsumption.
isActionCovered(int) - Method in class XClassifierSet
Returns if the specified action is covered in this set.
isMoreGeneral(XClassifier) - Method in class XClassifier
Returns if the classifier is more general than cl.
isMultiStepProblem() - Method in interface Environment
Returns true if the problem is a multi-step problem.
isMultiStepProblem() - Method in class Square
Returns false since the square problem is a single step problem
isSubsumer() - Method in class XClassifier
Returns if the classifier is a possible subsumer.

L

listNeighbors(int[][], int[], int) - Method in class AgentsPopulations
Builds the list of first neighbors of an agent.

M

main(String[]) - Static method in class AgentsPopulations
The Main loop
match(String) - Method in class XClassifier
Returns if the classifier matches in the current situation.
maxPayoff - Variable in class Square
Specifies the maximal payoff possible in this environment.
maxPopSize - Static variable in class XCSConstants
Specifies the maximal number of micro-classifiers in the population.
maxProblems - Variable in class AgentsPopulations
Specifies the number of exploration problems/trials to solve in one experiment by one agent.
mutateAction(int) - Method in class XClassifier
Mutates the action of the classifier.
mutateCondition(String) - Method in class XClassifier
Mutates the condition of the classifier.

N

name - Variable in class Agent
The name of the agent
nbAnswers - Variable in class XClassifierSet
number of answers collected during the communication process
nbVar - Variable in class Square
The number of variables taken into account in the process of evaluation, i.e. in calculating the right action.
nr - Variable in class PredictionArray
The sum of the fitnesses of classifiers that represent each entry in the prediction array.
nrActions - Variable in class Square
In the square problem there are 6 possible classifications
nrExps - Variable in class AgentsPopulations
Specifies the number of investigated experiments for each agent.
nu - Static variable in class XCSConstants
Specifies the exponent in the power function for the fitness evaluation.
numerosity - Variable in class XClassifier
The numerosity of the classifier.
numerositySum - Variable in class XClassifierSet
The Sum of the numerosity in one set is always kept up to date!

O

ordering() - Method in class Book
Classes the address Book by decreasing time of presence in the address book.
outFile1 - Variable in class AgentsPopulations
Stores the specified output File, where the performance will be written.
outFile2 - Variable in class AgentsPopulations
Stores the specified output File, where the performance will be written.

P

P_dontcare - Static variable in class XCSConstants
The probability of using a don't care symbol in an allele when covering.
pa - Variable in class PredictionArray
The prediction array.
parentSet - Variable in class XClassifierSet
Each set keeps a reference to the parent set out of which it was generated.
payoffLandscape - Static variable in class Square
Defines if either a payoff landscape or a 1000/0 payoff is provided after the execution of a classification.
perC - Variable in class Agent
The percentage of agents asked at random in the whole population of agents
pM - Static variable in class XCSConstants
The probability of mutating one allele and the action in an offspring classifier.
prediction - Variable in class XClassifier
The reward prediction value of this classifier.
PredictionArray - class PredictionArray.
This class generates a prediction array of the provided set.
PredictionArray(XClassifierSet, int) - Constructor for class PredictionArray
Constructs the prediction array according to the current set and the possible number of actions.
predictionError - Variable in class XClassifier
The reward prediction error of this classifier.
predictionErrorIni - Static variable in class XCSConstants
The initial prediction error value when generating a new classifier (e.g in covering).
predictionErrorReduction - Static variable in class XCSConstants
The reduction of the prediction error when generating an offspring classifier.
predictionIni - Static variable in class XCSConstants
The initial prediction value when generating a new classifier (e.g in covering).
printCharacteristics(PrintWriter) - Method in class XClassifierSet
print characteristics into a file
printSet() - Method in class XClassifierSet
Prints the classifier set to the control panel.
printSet(PrintWriter) - Method in class XClassifierSet
Prints the classifier set to the specified print writer (which usually refers to a file).
printXClassifier() - Method in class XClassifier
Prints the classifier to the control panel.
printXClassifier(PrintWriter) - Method in class XClassifier
Prints the classifier to the print writer (normally referencing a file).
pX - Static variable in class XCSConstants
The probability of applying crossover in an offspring classifier.

R

random - Variable in class Square
Used to generate new situations randomly
randomActionWinner() - Method in class PredictionArray
Selects an action randomly.
randomArray - Variable in class Agent
A vector used to store agents picked up at random from the total population of agents
randomPopulation(AgentsPopulations) - Method in class Agent
Construct a random population of agents picked up from the global population.
removeClassifier(int) - Method in class XClassifierSet
Removes the (possible macro-) classifier at the specified array position from the population.
removeClassifier(XClassifier) - Method in class XClassifierSet
Removes the specified (possible macro-) classifier from the population.
reset - Variable in class Square
Is set to true after a classification was executed
resetState() - Method in interface Environment
Resets the current state to a random instance of a problem.
resetState() - Method in class Square
Generates a new random problem instance.
reward - Variable in class Agent
The reward the agent receives from the environment for a given answer
rouletteActionWinner() - Method in class PredictionArray
Selects an action in the prediction array by roulette wheel selection.
runExperiment(Environment) - Method in class AgentsPopulations
Runs the posed problem with XCS.
runGA(int, Environment, String, int, double, double) - Method in class XClassifierSet
The Genetic Discovery in XCS takes place here.

S

scale - Variable in class Square
In the square problem, variables'values can rank from 0 to 3
seed - Static variable in class XCSConstants
The initialization of the pseudo random generator.
selectBestAnswer(XClassifierSet, int) - Method in class Agent
THis method is used by the agent who asks a question to select the best answer from the ones it recieved
selectXClassifierRW(double) - Method in class XClassifierSet
Selects one classifier using roulette wheel selection according to the fitnesses of the classifiers.
setActionSetSize(int) - Method in class XClassifier
Sets the size of the action set
setAddress(int) - Method in class Slot
Sets the name of an agent in a slot when it is introduced in the address book.
setAddressBook(Book) - Method in class Agent
Set an address book for the agent
setExperience(int) - Method in class XClassifier
Sets the experience of the classifier
setFitness(double) - Method in class XClassifier
Sets the fitness of the classifier.
setName(int) - Method in class Agent
Set the name of the agent
setNumberOfExperiments(int) - Method in class AgentsPopulations
Resets the number of experiments for each agent.
setNumberOfTrials(int) - Method in class AgentsPopulations
Resets the maximal number of trials in one experiment for an agent.
setNumerosity(int) - Method in class XClassifier
Sets the numerosity of the classifier
setPrediction(double) - Method in class XClassifier
Sets the prediction of the classifier.
setPredictionError(double) - Method in class XClassifier
Sets the prediction error of the classifier.
setSeed(long) - Static method in class XCSConstants
Sets a random seed in order to randomize the pseudo random generator.
setTimeStamp(int) - Method in class XClassifier
Sets the time stamp of the classifier.
setTimeStamps(int) - Method in class XClassifierSet
Sets the time stamp of all classifiers in the set to the current time.
setXClassifierSet(XClassifierSet) - Method in class Agent
Set the initial population of classifiers within an agent
slot - Variable in class Book
a slot of the address book
Slot - class Slot.
This class is the address book an agent maintains in order to communicate and build its "community.
Slot() - Constructor for class Slot
The constructor for a slot that will be inserted in an address book.
Square - class Square.
This class implements the problem to be solved by agents.
Square(int) - Constructor for class Square
Constructs the square problem according to the specified problem length and chosen payoff type.
startCommunication(String, Environment, XClassifierSet, AgentsPopulations, int) - Method in class Agent
This method is the communication itself.
startExperiments(PrintWriter, PrintWriter) - Method in class AgentsPopulations
This function runs the number of experiments specified.
subsumes(XClassifier) - Method in class XClassifier
Returns if the classifier subsumes cl.
subsumeXClassifier(XClassifier) - Method in class XClassifierSet
Tries to subsume a classifier in the current set.
subsumeXClassifier(XClassifier, XClassifier, XClassifier) - Method in class XClassifierSet
Tries to subsume a classifier in the parents.

T

teletransportation - Static variable in class XCSConstants
The maximal number of steps executed in one trial in a multi-step problem.
test(String) - Method in class XClassifier
test if a given classifier can match as an answer to the question posed.
testFitness(double) - Method in class XClassifierSet
Tests if the fitness of a classifier is above the average performance of the population of classifiers
testPerformance(double) - Method in class XClassifierSet
Tests if the performance of a classifier is above the average performance of the population of classifiers
theta_del - Static variable in class XCSConstants
Specified the threshold over which the fitness of a classifier may be considered in its deletion probability.
theta_GA - Static variable in class XCSConstants
The threshold for the GA application in an action set.
theta_sub - Static variable in class XCSConstants
The experience of a classifier required to be a subsumer.
timeAB - Variable in class Slot
Counts the time an agent stays in an address book. reflects the stability of the relationship
timeStamp - Variable in class XClassifier
The time the last GA application took place in this classifier.
totalNumberOfAgents - Static variable in class AgentsPopulations
the number of agents constituting the population
totalNumberOfAgents - Static variable in class Agent
The total number of agents involved in the experiment
trackExchange(XClassifier) - Method in class Slot
Returns the classifier passed from one agent to another.
transferAddressBook(Agent) - Method in class Book
If an agent receives an answer from another agent, then in turn it transfers to this agent the highest part of its address book, i.e.
twoPointCrossover(XClassifier) - Method in class XClassifier
Applies two point crossover and returns if the classifiers changed.

U

updateActionSetSize(double) - Method in class XClassifier
Updates the action set size.
updateFitness(double, double) - Method in class XClassifier
Updates the fitness of the classifier according to the relative accuracy.
updateFitnessSet() - Method in class XClassifierSet
Special function for updating the fitnesses of the classifiers in the set.
updatePrediction(double) - Method in class XClassifier
Updates the prediction of the classifier according to P.
updatePreError(double) - Method in class XClassifier
Updates the prediction error of the classifier according to P.
updateSet(double, double) - Method in class XClassifierSet
Updates all parameters in the current set (should be the action set).

W

wasCorrect() - Method in interface Environment
Returns if this action was a good/correct action.
wasCorrect() - Method in class Square
Returns true if the last executed action was a correct classification
wholePopulation - Static variable in class AgentsPopulations
The total population of agents

X

XClassifier - class XClassifier.
Each instance of this class represents one classifier.
XClassifier(double, int, int, int) - Constructor for class XClassifier
Construct a classifier with random condition and random action.
XClassifier(double, int, int, String) - Constructor for class XClassifier
Construct matching classifier with random action.
XClassifier(double, int, String, int) - Constructor for class XClassifier
Constructs a classifier with matching condition and specified action.
XClassifier(XClassifier) - Constructor for class XClassifier
Constructs an identical XClassifier.
XClassifierSet - class XClassifierSet.
This class handles the different sets of classifiers.
XClassifierSet(int) - Constructor for class XClassifierSet
Creates a new, empty population initializing the population array to the maximal population size plus the number of possible actions.
XClassifierSet(int, int) - Constructor for class XClassifierSet
A new random population
XClassifierSet(String, XClassifierSet, int, int) - Constructor for class XClassifierSet
Constructs a match set out of the population.
XClassifierSet(XClassifierSet, int) - Constructor for class XClassifierSet
Constructs an action set out of the given match set.
XClassifierSet(XCSConstants) - Constructor for class XClassifierSet
Construct the list of classifier candidate for answering a question
XCSConstants - class XCSConstants.
This class provides all relevant learning parameters for the XCS as well as other experimental settings and flags.
XCSConstants() - Constructor for class XCSConstants
The default constructor.

_

_A - Static variable in class XCSConstants
Constant for the random number generator (default = 16807).
_M - Static variable in class XCSConstants
Constant for the random number generator (modulus of PMMLCG = 2^31 -1).
_Q - Static variable in class XCSConstants
Constant for the random number generator (=_M/_A).
_R - Static variable in class XCSConstants
Constant for the random number generator (=_M mod _A).
A B C D E F G I L M N O P R S T U W X _
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