Serialized Form
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Class Agent implements Serializable |
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
distLevelOne
double distLevelOne
- threshold distance from the central competence of agents for signals and
GA
distLevelTwo
double distLevelTwo
- threshold distance from the core competence to accept communication
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
outFile1
java.io.File outFile1
- Stores the specified output File, where the performance will be written.
outFile2
java.io.File outFile2
- Stores the specified output File, where the performance will be written.
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.
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.
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Class Book implements Serializable |
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
pa
double[] pa
- The prediction array.
nr
double[] nr
- The sum of the fitnesses of classifiers that represent each entry in the prediction array.
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Class Slot implements Serializable |
address
int address
- the address of an agent in the address book
exchangedCl
XClassifier exchangedCl
exchangeCounter
int exchangeCounter
- the counter keeping track of the exchange occuring with one agent
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
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Class Square implements Serializable |
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
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.
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