package asm;import java.awt.Frame;/** * Title:        Artificial Stock Market * Description:  人工模擬股市（來源：SFI的Swarm版本）的Java版本 * Copyright:    Copyright (c) 2003 * Company:      http://agents.yeah.net * @author jake * @version 1.0 */public class AgentParam extends Frame {  public int numfcasts; /*"number of forecasts maintained by this agent"*/  //public int condwords; /*"number of words of memory required to hold bits"*/  public int condbits; /*"number of conditions bits are monitored"*/  public int mincount; /*"minimum number of times forecast must be used to become active"*/  public int gafrequency; /*"how often is genetic algorithm done?"*/  public int firstgatime; /*"after how many time steps is the genetic algorithm done"*/  public int longtime;	/*" unused time before Generalize() in genetic algorithm"*/  public int individual;  public double tauv;  public double lambda;  public double maxbid;  public double bitprob;  public double subrange;	/*" fraction of min-max range for initial random values"*/  public double a_min,a_max;	/*" min and max for p+d coef"*/  public double b_min,b_max;	/*" min and max for div coef"*/  public double c_min,c_max;	/*" min and max for constant term"*/  public double a_range,b_range,c_range;	/*" derived: max - min" */  public double newfcastvar;	/*" variance assigned to a new forecaster"*/  public double newfcastspec;  public double addvar;  public double initvar;	/*" variance of overall forecast for t<200"*/  public double bitcost;	/*" penalty parameter for specificity"*/  public double maxdev;	/*" max deviation of a forecast in variance estimation"*/  public double poolfrac;	/*" fraction of rules in replacement pool"*/  public double newfrac;	/*" fraction of rules replaced"*/  public double pcrossover;	/*" probability of running Crossover()."*/  public double plinear;	/*" linear combination "crossover" prob."*/  public double prandom;	/*" random from each parent crossover prob."*/  public double pmutation;	/*" per bit mutation prob."*/  public double plong;	        /*" long jump prob."*/  public double pshort;	/*" short (neighborhood) jump prob."*/  public double nhood;	        /*" size of neighborhood."*/  public double genfrac;	/*" fraction of 0/1 bits to generalize"*/  public double gaprob;	/*" derived: 1/gafrequency"*/  public int npool;		/*" derived: replacement pool size"*/  public int nnew;		/*" derived: number of new rules"*/  public int nnulls;            /*" unnused bits"*/  //int *bitlist;		/*" dynamic array, length condbits"*/  //double *problist;	/*" dynamic array, length condbits"*/  public int npoolmax ;		/* size of reject array */  public int nnewmax ;		/* size of newfcast array */  public int ncondmax;		/* size of newc*/  public AgentParam() {    numfcasts=100;//規則數目    initvar=1.0; //初始化方差    a_min=0;    b_min=-10;    c_min=-1;    a_max=4;    b_max=10;    c_max=5;    subrange=1;//系數的一個變化范圍，sub只能取[0,1]的數值    condbits=60;//規則if部分的二進制位數    nnulls=0;//無用空位的個數    bitcost=0.02;//位部分的適應度對總是硬度的貢獻權重    newfcastvar=0.6;//新規則的方差    newfcastspec=0.4;//新規則條件部分出現2的概率[0,1]取值    firstgatime=2;//第一次執行遺傳算法的允許時間    gafrequency=1000;//執行遺傳算法的頻率    mincount=1;//被激活喚醒的最小次數    individual=0;//是否僅僅采用最好規則進行方差計算？布爾值    tauv=50;//更新規則表現時候的權重系數global_mean = b*global_mean + a*ftarget;    lambda=0.9;//需求函數x=(E(p+d)-(1+r)p)/lambda*variance的系數    addvar=10;//改造的需求函數x=(E(p+d)-(1+r)p)/(lambda*variance+addvar)為了防止variance對結果英想過大    maxbid=10;//最大持股量    initvar=50;//初始方差    maxdev=100;//最大的離差    pcrossover=0.3;//交叉概率    pmutation=0.01;//變異概率    plong=0.6;//大變異的概率    pshort=0.3;//小變異的概率    plinear=0.4;//線性交叉的概率    prandom=0.3;//隨機交叉的概率    longtime=200;//長時間沒有被激活    genfrac=0.1;//位2的平均長度    nhood=3;//鄰域的長度    poolfrac=0.3;//淘汰規則池的比例    newfrac=0.2;//新規則的比例    npoolmax=10;    nnewmax=10;    ncondmax=10;    reinit();  }  public void reinit(){    //重新初始化一些參數    a_range = a_max - a_min;    b_range = b_max - b_min;    c_range = c_max - c_min;    gaprob = 1.0/(double)gafrequency;    if (1.0+bitcost*(condbits-nnulls) <= 0.0){      //system.Out("wrong with the bitcost,condbits,nnulls");      return;    }    npool = (int)(numfcasts*poolfrac + 0.5);    nnew = (int)(numfcasts*newfrac + 0.5);  // Record maxima needed for GA working space  if (npool > npoolmax) npoolmax = npool;  if (nnew > nnewmax) nnewmax = nnew;  }}