/***********************************************************************
This file is part of KEEL-software, the Data Mining tool for regression,
classification, clustering, pattern mining and so on.
Copyright (C) 2004-2010
F. Herrera (herrera@decsai.ugr.es)
L. S�nchez (luciano@uniovi.es)
J. Alcal�-Fdez (jalcala@decsai.ugr.es)
S. Garc�a (sglopez@ujaen.es)
A. Fern�ndez (alberto.fernandez@ujaen.es)
J. Luengo (julianlm@decsai.ugr.es)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see http://www.gnu.org/licenses/
**********************************************************************/
/**
* <p>
* @author Written by Albert Orriols (La Salle, Ram�n Llull University - Barcelona) 28/03/2004
* @author Modified by Xavi Sol� (La Salle, Ram�n Llull University - Barcelona) 03/12/2008
* @version 1.1
* @since JDK1.2
* </p>
*/
package keel.Algorithms.Genetic_Rule_Learning.XCS;
import keel.Algorithms.Genetic_Rule_Learning.XCS.KeelParser.Config;
import java.lang.*;
import java.io.*;
import java.util.*;
abstract class SSEnvironment implements Environment{
/**
* <p>
* This is the base class for all the single step problems environments
* that can specify their behaviour by code (that don't need to read the
* correct action for each condition from a file).
* </p>
*/
///////////////////////////////////////
// attributes
/**
* <p>
* Represents the number of actions that can take the condition.
* </p>
*
*/
private int numActions;
/**
* <p>
* Represents the length of the condition.
* </p>
*
*/
private int condLength;
/**
* <p>
* Indicates if the classification has been correct.
* </p>
*
*/
private boolean isCorrect;
/**
* <p>
* Represents the maximum payoff that a classifier can get.
* </p>
*
*/
private double maxPayOff;
/**
* <p>
* Represents the minimum payoff that a classifier can get.
* </p>
*
*/
private double minPayOff;
/**
* <p>
* Represents the current state of the environment.
* </p>
*
*/
private double[] currentState;
/**
* <p>
* It indicates if the classification has been performed.
*
*/
private boolean classExecuted;
///////////////////////////////////////
// operations
/**
* <p>
* It's the constructor of the class. It initializes the environment.
* </p>
* <p>
*
* @param nActions is the number of possible actions in the current
* environment.
* </p>
* <p>
* @param cLength is the condition length of the classifier
* </p>
*/
// public SSEnvironment(int nActions, int cLength) {
// your code here
// } // end SSEnvironment
/**
* <p>
* Determines if the classification was good
* </p>
* <p>
*
* @return a boolean that indicates if the last classification was good.
* </p>
*/
public boolean wasCorrect() {
// your code here
return false;
} // end wasCorrect
/**
* <p>
* This function returns the reward given when applying the action to the
* environment.
* </p>
* <p>
*
* @return a double with the reward
* </p>
* <p>
* @param action is the action chosen to do.
* </p>
*/
public double makeAction(int action) {
// your code here
return 0.0;
} // end makeAction
/**
* <p>
* The function returns the current state.
* </p>
* <p>
*
* @return a double[] with the current state.
* </p>
*/
public double[] getCurrentSate() {
// your code here
return null;
} // end getCurrentSate
/**
* <p>
* Creates a new state of the problem. XCS has to decide the
* action to do.
* </p>
* <p>
*
* @return a double[] with the new state.
* </p>
*/
public double[] newState() {
// your code here
return null;
} // end newState
/**
* <p>
* Returns the environment maximum payoff
* </p>
* <p>
* @return a double with the environment maximum payoff.
* </p>
*/
public double getMaxPayoff(){
return 0.;
}
/**
* <p>
* Returns the environment minimum payoff
* </p>
* <p>
* @return a double with the environment minimum payoff.
* </p>
*/
public double getMinPayoff(){
return 0.;
}
/**
* <p>
* Returns if the class has been performed. It is used
* in the multiple step problems.
* </p>
* <p>
* @return a boolean indicating if the problem has finished.
* </p>
*/
public boolean isPerformed(){
return false;
}
/**
* <p>
* Returns the class of the environmental state. It's
* used by UCS (supervised learning).
* </p>
* <p>
* @return a int with the class associated to the current environmental
* state.
* </p>
*/
public int getEnvironmentClass(){
return 0;
} //end getClass
/**
* <p>
* It initializes the first example. It is used in the file
* environment to get the examples sequentially.
* </p>
*/
public void beginSequentialExamples(){}
/**
* <p>
* It returns the new Example of a single step file environment.
* </p>
*/
public double[] getSequentialState(){return null;}
/**
* <p>
* It returns the number of examples of the database. It's only
* used in the file environments.
* </p>
*/
public int getNumberOfExamples(){return 0;}
/**
* <p>
* It deletes the examples of the database that match with the
* classifier passed. It's only used in the file enviornment.
* </p>
*/
public void deleteMatchedExamples(Classifier cl){}
} // end SSEnvironment