/***********************************************************************
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.*;
public class MPEnvironment extends SSEnvironment {
/**
* <p>
* This is the typical example for a single step problem, the multiplexer.
* </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 is the number of bits that indicate the position. In the MUX problem,
* some bits may not be valid. For example, in a MUX of 12
* bits, 3 bits are for adressing, and 8 bits represent the condition (position bits)
* So, 1 bit is not valid (it does not influence the output).
* </p>
*
*/
private int positionBits;
/**
* <p>
* It indicates if the classification has been performed. In mux problem it's true
* in every step.
*
*/
private boolean classExecuted;
///////////////////////////////////////
// operations
/**
* <p>
* It is the constructor of the class. It initializes the environment.
* </p>
*/
public MPEnvironment() {
//super();
condLength = Config.clLength;
double i = 0;
for(i=1.0; (int) i+Math.pow(2.,i)<=condLength; i++);//calculates the position bits in this problem
positionBits=(int)(i-1);
classExecuted = false;
isCorrect = false;
currentState = new double[Config.clLength];
maxPayOff = 1000;
minPayOff = 0;
System.out.println ("Number of bits position: "+positionBits);
initRepresentationParameters();
} // end MPEnvironment
/**
* <p>
* Determines if the classification was good
* </p>
* <p>
*
* @return a boolean that indicates if the last classification was good.
* </p>
*/
public boolean wasCorrect() {
return isCorrect;
} // end wasCorrect
/**
* <p>
* This function returns the reward given when applying the action in 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) {
int position = 0;
for (int i=0; i<positionBits; i++){
if (currentState[i] == (double)'1')
position += (int)Math.pow(2.0, positionBits -i -1);
}
if ( (int)(currentState[position+positionBits] - (double)'0') == action){
isCorrect = true;
classExecuted = true;
return maxPayOff;
}
isCorrect = false;
classExecuted = true;
return minPayOff;
} // end makeAction
/**
* <p>
* The function returns the current state.
* </p>
* <p>
*
* @return a float[] with the current state.
* </p>
*/
public double[] getCurrentState() {
return currentState;
} // end getCurrentSate
/**
* <p>
* Creates a new state of the problem. XCS has to decide the action to do.
* </p>
* <p>
*
* @return a float[] with the new state.
* </p>
*/
public double[] newState() {
for (int i=0; i<condLength; i++){
if (Config.rand() < 0.5)
currentState[i] = (double) '0';
else
currentState[i] = (double) '1';
}
classExecuted = false;
return currentState;
} // end newState
/**
* <p>
* Returns the environment maximum payoff
* </p>
* <p>
* @return a double with the environment maximum payoff.
* </p>
*/
public double getMaxPayoff(){
return maxPayOff;
}
/**
* <p>
* Returns the environment minimum payoff
* </p>
* <p>
* @return a double with the environment minimum payoff.
* </p>
*/
public double getMinPayoff(){
return minPayOff;
}
/**
* <p>
* Returns if the action 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 classExecuted;
}
/**
* <p>
* Return the class of the environmental state. It's used by UCS
* (in supervised learning).
* </p>
* <p>
* @return a int with the class associated with the current environmental
* state.
* </p>
*/
public int getEnvironmentClass(){
int position = 0;
for (int i=0; i<positionBits; i++){
if (currentState[i] == (double)'1')
position += (int)Math.pow(2.0, positionBits -i -1);
}
return ((int)currentState[position + positionBits] - (int)'0');
} //end getEnvironmentClass
/**
* <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 de
* classifier given as a parameter. It's only used in the file environment.
* </p>
*/
public void deleteMatchedExamples(Classifier cl){}
/**
* <p>
* Initializes the representation parameters of the enviornment
* </p>
*/
private void initRepresentationParameters(){
// When reading the descriptor it will be modified if there is a real or integer attribute
Config.ternaryRep = true;
// The number of actions will be updated while reading the file.
Config.numberOfActions = 2;
Config.charVector = new char[3];
Config.charVector[0] = '0';
Config.charVector[1] = '1';
Config.charVector[2] = '#';
Config.numberOfCharacters = 3;
}
} // end MPEnvironment