コード例 #1
0
ファイル: GENALG2.C プロジェクト: chrisdurtschi/ai
void Cross()
{
  int i, j, l, loc, temp;
  int NCross = 0;

  for (i=0; i<MaxPop; i++)  /* for each individual in the population */
  {
    if (FRandom(1.0) > ProbCross) continue;  /* skip unless within prob'y */

    NCross++;
    do
      j = IRandom(MaxPop);
    while (j == i);  /* select random mate (not with itself) */

    loc = IRandom(CodeSize - 2) + 1; /* cross-over location 1 to size-1 */
    for (l=loc; l<CodeSize; l++)  /* for loci at loc and beyond, exchange */
    {
      temp = Pop[i].Code[l];
      Pop[i].Code[l] = Pop[j].Code[l];
      Pop[j].Code[l] = temp;
    }
  }
  
  if (NTop)   /* print unless NTop is 0 */
    printf( "\n There were %d crossovers. \n",NCross);
}
コード例 #2
0
ファイル: GENALG2.C プロジェクト: chrisdurtschi/ai
/* reproduce the next generation based on survivablility */
void Repro()
{
  int i, j;
  float Cut;  /* the point in total goodness where individual is selected */
  float Tot;  /* cumulative goodness */

  for (i=0; i<MaxPop; i++)  /* for each individual in the new population */
  {
    Cut = FRandom(TotGood);

    for (j=0, Tot=0; j<MaxPop; j++) /* search old ones to locate cut */
    {
      Tot += Pop[j].Good;
      
      if (Cut < Tot)
      {
        NewPop[i] = Pop[j];      /* select individual for new group */
        break;
      }
      
      NewPop[i] = Pop[MaxPop];  /* only if cut bigger than total ??? */
    }
  }
  
  for (i=0; i<MaxPop; i++)  /* copy each individual in the population */
    Pop[i] = NewPop[i];
}/* function to handle cross-overs in the current generation */
コード例 #3
0
ファイル: GENALG2.C プロジェクト: chrisdurtschi/ai
/* ------------------------------------------------------------
    a sample fitness function for the 2-armed bandit problem
   ------------------------------------------------------------ */
float fitness(int arm)
{
  float prob[2] = {0.25,0.75};

  if (FRandom(1.0) < prob[arm])
    return 1.0;
  else
    return 0.0;
}
コード例 #4
0
ファイル: s_chicken.cpp プロジェクト: smcbeth/Example
void
S_Chicken::Think( )
{
	S_BaseMobile::Think();

	SetMovingForward( true );

	// do chicken stuff
	SetNextThink( FRandom( 0.5f, 1.0f ) );
}
コード例 #5
0
ファイル: mapgen.cpp プロジェクト: trezker/Mapgen
//Creates a heightmap from your seed.
void MAPGEN::create(float fractalfactor, int seed){
	srand(seed);
	int w=msize,h=msize;
	int i, j, k;
	float amount = 256;//, l;

	// Do the corners
	map[0][0] = 0; //FRandom(amount);
	map[w-1][0] = 0; //FRandom(amount);
	map[w-1][h-1] = 0; //FRandom(amount);
	map[0][h-1] = 0; //FRandom(amount);
	amount /= fractalfactor;

	for (i = 128; i > 0; i /= 2){
		// This is the square phase
		for (j = i; j < w; j += 2 * i)
			for (k = i; k < h; k += 2 * i){
				map[j][k] = (map[Minus(j, i)][Minus(k, i)] +
					map[Minus(j, i)][Plus(k, i)] +
					map[Plus(j, i)][Plus(k, i)] +
					map[Plus(j, i)][Minus(k, i)]) / 4. +
					FRandom(amount);
			}
		amount /= fractalfactor;

		// This is the diamond phase
		for (j = 0; j < w; j += i)
			for (k = 0; k < h; k += i)
				if ((((j + k) / i) % 2) == 1){
					//  In this phase we might fall off the edge
					//  when we count the average of neighbours
					//  Minus and Plus take care of that
					map[j][k] = (map[Minus(j, i)][k] +
						map[j][Minus(k, i)] +
						map[Plus(j, i)][k] +
						map[j][Plus(k, i)]) / 4 +
						FRandom(amount);
				}
		amount /= fractalfactor;
	}
}
コード例 #6
0
ファイル: GENALG2.C プロジェクト: chrisdurtschi/ai
/* perform mutations for this generation */
void Mutate()
{
  int i, l;
  int NMut = 0;

  for (i=0; i<MaxPop; i++)  /* for each individual in the population */
  {
    if (FRandom(1.0) > ProbMut) continue;  /* skip unless within prob'y */
      NMut++;

    l = IRandom(CodeSize);  /* select locus to mutate */
    Pop[i].Code[l] = (Pop[i].Code[l]
    +IRandom(CodeSchema[l]-2)+1)%CodeSchema[l]; /* different value */
  }
  if (NTop)   /* print unless NTop is 0 */
    printf( "\n There were %d mutations. \n", NMut);
}