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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 reference 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 the routines handling communications.
Agent(double, double) - Constructor for class Agent
Constructs the XCS system of the agent.
agentSet - Variable in class AgentsPopulations
The list of agents
AgentsPopulations - class AgentsPopulations.
This is the class where the population of agents are initialized.
AgentsPopulations(int, double, double, int, int, int, String, int, double, PrintWriter, int) - Constructor for class AgentsPopulations
Constructor for the initial organisation
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.
averClique - Variable in class AgentsPopulations
Average cliquishness in the Agents population, for each problem
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

BatchSimulator - class BatchSimulator.
This class implements the main loop.
BatchSimulator() - Constructor for class BatchSimulator
Constructor
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 and then computes whether or not a signal is in the core competence of the agent.
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)
communication - Variable in class AgentsPopulations
Communication between agents is allowed (=1) or not (=0)
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 XClassifierSet
The cons parameter is necessary for all kinds of calculations in the set.
cons - Static variable in class BatchSimulator
Stores the relevant constants for XCS.
cons - Static variable in class AgentsPopulations
Stores the relevant constants for XCS.
cons - Static variable in class XClassifier
An instance of the learning parameters in XCSJava.
cons - Static variable in class Square
Stores the relevant constants for XCS.
cons - Static variable in class Agent
Stores the relevant constants for XCS.
cons - Static variable in class Slot
Stores the relevant constants for XCS.
consultRatio - Variable in class AgentsPopulations
Percentage of the population to be consulted by the agents
containsClassifier(XClassifier) - Method in class XClassifierSet
Returns the position of the classifier in the set if it is present and -1 otherwise.
coreCompetence - Variable in class AgentsPopulations
Competence range of the agents (determines their core specialisations)
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 initExVal 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 between the central competencies of agents and both signals from the environment and offsprings generated by 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() - Method in class AgentsPopulations
Executes one single-step experiment.
doOneSingleStepProblemExplore(String, int, AgentsPopulations, int) - 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.
getCloseState(String, AgentsPopulations) - Method in class Agent
The agent computes whether or not the signal from the environment is in its realm of specialisation or not before to tell it to the manager.
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 (first method).
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
getNbCommunications() - Method in class Agent
Returns the number of communications made by 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 - Static variable in class XCSConstants
The number of runs without answer allowed to an agent in the address book before to delete it.
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 one discovered classifier 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 BatchSimulator
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.
MAXPROBLEMS - Static variable in class BatchSimulator
The number of problems
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
nbCommunications - Variable in class Agent
Number of Communications done by each agent for each problem
nbRuns - Static variable in class BatchSimulator
Number of simulations in the batch
nbVar - Variable in class Square
The number of variables taken into account in the process of evaluation, i.e. in calculating the right action.
noAnswer - Variable in class Agent
reward to the system in case there is no solution found by the agent
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

orderAgentsTable - Variable in class AgentsPopulations
The order in which agents receive the problem
ordering() - Method in class Book
Classes the address Book by decreasing time of presence in the address book.
orgaType - Variable in class AgentsPopulations
Type of the organization studied m= manager c= community
outFile1 - Static variable in class BatchSimulator
File to store results

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 (when =1) or a 1000/0 payoff (when =0) is provided after the execution of a classification.
payoffType - Variable in class AgentsPopulations
Structure of the reward function in the environment
perC - Variable in class Agent
The percentage of agents asked at random in the whole population of agents
performance - Variable in class AgentsPopulations
Performance one agent gains in answering a signal from the problem space
performanceCP - Variable in class AgentsPopulations
the cumulated performance of the system
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).
problemType - Variable in class AgentsPopulations
The type of the environment, i.e. the problem space
pwCP - Variable in class AgentsPopulations
The output file
pX - Static variable in class XCSConstants
The probability of applying crossover in an offspring classifier.

R

R - Static variable in class BatchSimulator
Random generator
R - Variable in class AgentsPopulations
Random generator
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.
run - Variable in class AgentsPopulations
Number of runs of the total simulation
run() - Method in class AgentsPopulations
The loop where the population of agents is generated and the experiment is launched
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

saveProb - Variable in class AgentsPopulations
Probabilities for data to be saved for statistical treatment
SAVEPROB - Static variable in class BatchSimulator
The probability of saving the results of each problem
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, String, 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
selectorAgent - Variable in class AgentsPopulations
Selection in the PredictionArray for each Agent: 1: bestActionWinner 0: rouletteActionWinner
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
shakeAgentsOrder(int) - Method in class AgentsPopulations
Method used to build at each experiment a random list.
slot - Variable in class Book
A slot of the address book
Slot - class Slot.
This class is the entries of 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.
solution - Variable in class Agent
Has the agent found a solution?
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() - 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.
totalCommunications - Variable in class AgentsPopulations
The total number of communications in the population for each problem.
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
Creates a new random population, initializing the population array to the maximal population size plus the number of possible actions.
XClassifierSet(String, XClassifierSet, int) - Constructor for class XClassifierSet
Constructs a match set out of the population, without covering.
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).
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