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);
}
/* 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 */
/* ------------------------------------------------------------
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;
}
void
S_Chicken::Think( )
{
S_BaseMobile::Think();
SetMovingForward( true );
// do chicken stuff
SetNextThink( FRandom( 0.5f, 1.0f ) );
}
//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;
}
}
/* 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);
}
