nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/sco/SCAgent.java

   1 package net.adaptivebox.sco;
   2
   3 /**
   4  * Description: The description of social cognitive agent.
   5  *
   6  * @Information source: a) external library (L); b) the own memory: a point that
   7  * generated in the last learning cycle
   8  *
   9  * @Coefficients: TaoB and TaoW
  10  *
  11  * @ Author        Create/Modi     Note
  12  * Xiaofeng Xie    Mar 11, 2003
  13  * Xiaofeng Xie    May 11, 2004
  14  * Xiaofeng Xie    May 20, 2004
  15  *
  16  * This library is free software; you can redistribute it and/or
  17  * modify it under the terms of the GNU Lesser General Public
  18  * License as published by the Free Software Foundation; either
  19  * version 2.1 of the License, or (at your option) any later version.
  20  *
  21  * This library is distributed in the hope that it will be useful,
  22  * but WITHOUT ANY WARRANTY; without even the implied warranty of
  23  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
  24  * Lesser General Public License for more details.
  25  *
  26  * Please acknowledge the author(s) if you use this code in any way.
  27  *
  28  * @version 1.0
  29  * @Since MAOS1.0
  30  *
  31  * @References:
  32  * [1] Xie X F, Zhang W J. Solving engineering design problems by social cognitive
  33  * optimization. Genetic and Evolutionary Computation Conference, 2004: 261-262
  34  */
  35
  36
  37 import net.adaptivebox.global.*;
  38 import net.adaptivebox.space.*;
  39 import net.adaptivebox.goodness.*;
  40 import net.adaptivebox.problem.*;
  41 import net.adaptivebox.knowledge.*;
  42
  43 public class SCAgent {
  44
  45   //Describes the problem to be solved (encode the point into intermediate information)
  46   private ProblemEncoder problemEncoder;
  47   //Forms the goodness landscape
  48   private IGoodnessCompareEngine specComparator;
  49
  50   //the coefficients of SCAgent
  51   protected int TaoB = 2;
  52   //The early version set TaoW as the size of external library (NL), but 4 is often enough
  53   protected int TaoW = 4;
  54
  55   //The referred external library
  56   protected Library externalLib;
  57   //store the point that generated in current learning cycle
  58   protected SearchPoint trailPoint;
  59   //the own memory: store the point that generated in last learning cycle
  60   protected SearchPoint pcurrent_t;
  61
  62   public void setExternalLib(Library lib) {
  63     externalLib = lib;
  64   }
  65
  66   public void setProblemEncoder(ProblemEncoder encoder) {
  67     problemEncoder = encoder;
  68     trailPoint = problemEncoder.getFreshSearchPoint();
  69     pcurrent_t = problemEncoder.getEncodedSearchPoint();
  70   }
  71
  72   public void setSpecComparator(IGoodnessCompareEngine comparer) {
  73     specComparator = comparer;
  74   }
  75
  76   public SearchPoint generatePoint() {
  77     //generate a new point
  78     generatePoint(trailPoint);
  79     //evalute the generated point
  80     problemEncoder.evaluate(trailPoint);
  81     return trailPoint;
  82   }
  83
  84   protected void generatePoint(ILocationEngine tempPoint) {
  85     SearchPoint Xmodel, Xrefer, libBPoint;
  86
  87     // choose Selects a better point (libBPoint) from externalLib (L) based
  88     // on tournament selection
  89     int xb = externalLib.tournamentSelection(specComparator, TaoB, true);
  90     libBPoint = externalLib.getSelectedPoint(xb);
  91     // Compares pcurrent_t with libBPoint
  92     // The better one becomes model point (Xmodel)
  93     // The worse one becomes refer point (Xrefer)
  94     if(specComparator.compare(pcurrent_t.getEncodeInfo(), libBPoint.getEncodeInfo())==IGoodnessCompareEngine.LARGER_THAN) {
  95       Xmodel = libBPoint;
  96       Xrefer = pcurrent_t;
  97     } else {
  98       Xmodel = pcurrent_t;
  99       Xrefer = libBPoint;
 100     }
 101     // observational learning: generates a new point near the model point, which
 102     // the variation range is decided by the difference of Xmodel and Xrefer
 103     inferPoint(tempPoint, Xmodel, Xrefer, problemEncoder.getDesignSpace());
 104   }
 105
 106   //1. Update the current point into the external library
 107   //2. Replace the current point by the generated point
 108   public void updateInfo() {
 109     //Selects a bad point kw from TaoW points in Library
 110     int xw = externalLib.tournamentSelection(specComparator, TaoW, false);
 111     //Repaces kw with pcurrent_t
 112     externalLib.getSelectedPoint(xw).importPoint(pcurrent_t);
 113     //Repaces pcurrent_t (x(t)) with trailPoint (x(t+1))
 114     pcurrent_t.importPoint(trailPoint);
 115    }
 116
 117   //  1---model point, 2---refer point
 118    public boolean inferPoint(ILocationEngine newPoint, ILocationEngine point1,ILocationEngine point2, DesignSpace space){
 119      double[] newLoc = newPoint.getLocation();
 120      double[] real1 = point1.getLocation();
 121      double[] real2 = point2.getLocation();
 122
 123      for (int i=0; i<newLoc.length; i++) {
 124        newLoc[i] = real1[i]*2-real2[i];
 125        //boundary handling
 126        newLoc[i] = space.boundAdjustAt(newLoc[i], i);
 127        newLoc[i] = RandomGenerator.doubleRangeRandom(newLoc[i], real2[i]);
 128      }
 129      return true;
 130    }
 131 }
 132