Serialized Form

Class Agent implements Serializable

Serialized Fields

gpop

XClassifierSet gpop

Stores the current population of XCS.

bestClassifier

XClassifier bestClassifier

The classifier selected for communication

name

int name

The name of the agent

solution

boolean solution

Has the agent found a solution?

distLevelOne

double distLevelOne

threshold distance between the central competencies of agents and both signals from the environment and offsprings generated by GA

distLevelTwo

double distLevelTwo

threshold distance from the core competence to accept communication

noAnswer

double noAnswer

reward to the system in case there is no solution found by the agent

addressBook

Book addressBook

The address book of the agent

randomArray

java.util.Vector randomArray

A vector used to store agents picked up at random from the total population of agents

perC

double perC

The percentage of agents asked at random in the whole population of agents

averPerf

double averPerf

initialization of the average performance fitness and prediction error of the agent's population of classifiers

averFit

double averFit

initialization of the average performance fitness and prediction error of the agent's population of classifiers

averExp

double averExp

initialization of the average performance fitness and prediction error of the agent's population of classifiers

averErr

double averErr

initialization of the average performance fitness and prediction error of the agent's population of classifiers

reward

double reward

The reward the agent receives from the environment for a given answer

nbCommunications

int nbCommunications

Number of Communications done by each agent for each problem

Class AgentsPopulations implements Serializable

Serialized Fields

maxProblems

int maxProblems

Specifies the number of exploration problems/trials to solve in one experiment by one agent.

nrExps

int nrExps

Specifies the number of investigated experiments for each agent.

performanceCP

double performanceCP

the cumulated performance of the system

agentSet

Agent[] agentSet

The list of agents

agSet

java.util.Vector agSet

The created agents list for purpose of communication

env

Environment env

Stores the posed problem.

communication

int communication

Communication between agents is allowed (=1) or not (=0)

coreCompetence

double coreCompetence

Competence range of the agents (determines their core specialisations)

consultRatio

double consultRatio

Percentage of the population to be consulted by the agents

selectorAgent

int selectorAgent

Selection in the PredictionArray for each Agent: 1: bestActionWinner 0: rouletteActionWinner

payoffType

int payoffType

Structure of the reward function in the environment

problemType

java.lang.String problemType

The type of the environment, i.e. the problem space

totalCommunications

int totalCommunications

The total number of communications in the population for each problem.

averClique

double averClique

Average cliquishness in the Agents population, for each problem

performance

double performance

Performance one agent gains in answering a signal from the problem space

run

int run

Number of runs of the total simulation

orgaType

java.lang.String orgaType

Type of the organization studied m= manager c= community

pwCP

java.io.PrintWriter pwCP

The output file

orderAgentsTable

int[] orderAgentsTable

The order in which agents receive the problem

saveProb

double saveProb

Probabilities for data to be saved for statistical treatment

R

java.util.Random R

Random generator

Class Book implements Serializable

Serialized Fields

slot

Slot slot

A slot of the address book

addressSet

Slot[] addressSet

The array of addresses, each slot containing the name of an agent and its exchange activity record.

addressSetSize

int addressSetSize

The size of the address book

Class PredictionArray implements Serializable

Serialized Fields

pa

double[] pa

The prediction array.

nr

double[] nr

The sum of the fitnesses of classifiers that represent each entry in the prediction array.

Class Slot implements Serializable

Serialized Fields

address

int address

the reference of an agent in the address book

exchangedCl

XClassifier exchangedCl

exchangeCounter

int exchangeCounter

the counter keeping track of the exchange occuring with one agent. This counter is set at initExval when an agent is introduced in the address book and decreased by 1 each time the agent does not answer. When it equals 0, the agent is removed from the address book.

timeAB

int timeAB

Counts the time an agent stays in an address book. reflects the stability of the relationship

initExVal

int initExVal

The number of runs without answer allowed to an agent in the address book before to delete it.

agent

Agent agent

an agent

Class Square implements Serializable

Serialized Fields

maxPayoff

int maxPayoff

Specifies the maximal payoff possible in this environment.

edgeSquare

int edgeSquare

Edge of the square problem

random

java.util.Random random

Used to generate new situations randomly

currentState

java.lang.String currentState

Stores the current problem.

correct

boolean correct

Stores if the last classification was correct.

reset

boolean reset

Is set to true after a classification was executed

nrActions

int nrActions

In the square problem there are 6 possible classifications

See Also:

Constant Field Values

scale

int scale

In the square problem, variables'values can rank from 0 to 3

See Also:

Constant Field Values

bits

int bits

the number of bits used to code the variables in binaries

nbVar

int nbVar

The number of variables taken into account in the process of evaluation, i.e. in calculating the right action.

See Also:

Constant Field Values

car

int[] car

The different variables are stored in an array of integers. This array is used to generate the string passed to the agents and the value of the correct action

Class XClassifier implements Serializable

Serialized Fields

condition

java.lang.String condition

The condition of this classifier.

action

int action

The action of this classifier.

prediction

double prediction

The reward prediction value of this classifier.

predictionError

double predictionError

The reward prediction error of this classifier.

fitness

double fitness

The fitness of the classifier in terms of the macro-classifier.

numerosity

int numerosity

The numerosity of the classifier. This is the number of micro-classifier this macro-classifier represents.

experience

int experience

The experience of the classifier. This is the number of problems the classifier learned from so far.

actionSetSize

double actionSetSize

The action set size estimate of the classifier.

timeStamp

int timeStamp

The time the last GA application took place in this classifier.

Class XClassifierSet implements Serializable

Serialized Fields

numerositySum

int numerositySum

The Sum of the numerosity in one set is always kept up to date!

parentSet

XClassifierSet parentSet

Each set keeps a reference to the parent set out of which it was generated. In the population itself this pointer is set to zero.

clSet

XClassifier[] clSet

The classifier list (in form of an array)

cllSize

int cllSize

The actual number of macro-classifiers in the list (which is in fact equal to the number of entries in the array).

nbAnswers

int nbAnswers

number of answers collected during the communication process

Class XCSConstants implements Serializable