GAULFUNC boolean ga_sa_boltzmann_acceptance( population *pop,
entity *original,
entity *putative )
{
return ( original->fitness < putative->fitness ||
random_boolean_prob(exp((putative->fitness-original->fitness)
/(GA_BOLTZMANN_FACTOR*pop->sa_params->temperature))) );
}
void pingpong_mutate(population *pop, entity *mother, entity *son)
{
/* Checks. */
if (!mother || !son) die("Null pointer to entity structure passed");
if (random_boolean_prob(0.5))
pingpong_mutate_swap(pop, mother, son);
else
pingpong_mutate_shift(pop, mother, son);
return;
}
boolean wildfire_seed(population *pop, entity *adam)
{
int i, j, k; /* Map square. */
if (random_boolean())
{
for(i=0; i<WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION; i++)
{
((int *)adam->chromosome[0])[i] = random_boolean_prob((double)WILDFIRE_CISTERNS/
((double)WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION));
}
}
else
{
for(i=0; i<WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION; i++)
{
((int *)adam->chromosome[0])[i] = 0;
}
/* Deliberately places slightly fewer cisterns than allowed. */
i = random_int(WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION);
j = random_int(WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION);
k = WILDFIRE_CISTERNS;
while (k>0)
{
i = (i+j)%(WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION);
if (((int *)adam->chromosome[0])[i] == 1)
{
j = random_int(WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION);
}
else
{
((int *)adam->chromosome[0])[i] = 1;
}
k--;
}
}
return TRUE;
}
int ga_deterministiccrowding( population *pop,
const int max_generations )
{
int generation=0; /* Current generation number. */
int *permutation, *ordered; /* Arrays of entities. */
entity *mother, *father; /* Current entities. */
entity *son, *daughter, *entity; /* Current entities. */
int i; /* Loop variable over entities. */
double dist1, dist2; /* Genetic or phenomic distances. */
int rank; /* Rank of entity in population. */
/* Checks. */
if (!pop)
die("NULL pointer to population structure passed.");
if (!pop->dc_params)
die("ga_population_set_deterministiccrowding_params(), or similar, must be used prior to ga_deterministiccrowding().");
if (!pop->evaluate) die("Population's evaluation callback is undefined.");
if (!pop->mutate) die("Population's mutation callback is undefined.");
if (!pop->crossover) die("Population's crossover callback is undefined.");
if (!pop->dc_params->compare) die("Population's comparison callback is undefined.");
plog(LOG_VERBOSE, "The evolution by deterministic crowding has begun!");
pop->generation = 0;
/*
* Score the initial population members.
*/
if (pop->size < pop->stable_size)
gaul_population_fill(pop, pop->stable_size - pop->size);
for (i=0; i<pop->size; i++)
{
if (pop->entity_iarray[i]->fitness == GA_MIN_FITNESS)
pop->evaluate(pop, pop->entity_iarray[i]);
}
sort_population(pop);
ga_genocide_by_fitness(pop, GA_MIN_FITNESS);
/*
* Prepare arrays to store permutations.
*/
permutation = s_malloc(sizeof(int)*pop->size);
ordered = s_malloc(sizeof(int)*pop->size);
for (i=0; i<pop->size;i++)
ordered[i]=i;
plog( LOG_VERBOSE,
"Prior to the first generation, population has fitness scores between %f and %f",
pop->entity_iarray[0]->fitness,
pop->entity_iarray[pop->size-1]->fitness );
/*
* Do all the generations:
*
* Stop when (a) max_generations reached, or
* (b) "pop->generation_hook" returns FALSE.
*/
while ( (pop->generation_hook?pop->generation_hook(generation, pop):TRUE) &&
generation<max_generations )
{
generation++;
pop->generation = generation;
pop->orig_size = pop->size;
plog(LOG_DEBUG,
"Population size is %d at start of generation %d",
pop->orig_size, generation );
sort_population(pop);
random_int_permutation(pop->orig_size, ordered, permutation);
for ( i=0; i<pop->orig_size; i++ )
{
mother = pop->entity_iarray[i];
father = pop->entity_iarray[permutation[i]];
/*
* Crossover step.
*/
plog(LOG_VERBOSE, "Crossover between %d (rank %d fitness %f) and %d (rank %d fitness %f)",
ga_get_entity_id(pop, mother),
ga_get_entity_rank(pop, mother), mother->fitness,
ga_get_entity_id(pop, father),
ga_get_entity_rank(pop, father), father->fitness);
son = ga_get_free_entity(pop);
daughter = ga_get_free_entity(pop);
pop->crossover(pop, mother, father, daughter, son);
/*
* Mutation step.
*/
if (random_boolean_prob(pop->mutation_ratio))
{
plog(LOG_VERBOSE, "Mutation of %d (rank %d)",
ga_get_entity_id(pop, daughter),
ga_get_entity_rank(pop, daughter) );
entity = ga_get_free_entity(pop);
pop->mutate(pop, daughter, entity);
ga_entity_dereference(pop, daughter);
daughter = entity;
}
if (random_boolean_prob(pop->mutation_ratio))
{
plog(LOG_VERBOSE, "Mutation of %d (rank %d)",
ga_get_entity_id(pop, son),
ga_get_entity_rank(pop, son) );
entity = ga_get_free_entity(pop);
pop->mutate(pop, son, entity);
ga_entity_dereference(pop, son);
son = entity;
}
/*
* Apply environmental adaptations, score entities, sort entities, etc.
* FIXME: Currently no adaptation.
*/
pop->evaluate(pop, daughter);
pop->evaluate(pop, son);
/*
* Evaluate similarities.
*/
dist1 = pop->dc_params->compare(pop, mother, daughter) + pop->dc_params->compare(pop, father, son);
dist2 = pop->dc_params->compare(pop, mother, son) + pop->dc_params->compare(pop, father, daughter);
/*
* Determine which entities will survive, and kill the others.
*/
if (dist1 < dist2)
{
rank = ga_get_entity_rank(pop, daughter);
if (daughter->fitness < mother->fitness)
{
entity = pop->entity_iarray[i];
pop->entity_iarray[i] = pop->entity_iarray[rank];
pop->entity_iarray[rank] = entity;
}
ga_entity_dereference_by_rank(pop, rank);
rank = ga_get_entity_rank(pop, son);
if (son->fitness < father->fitness)
{
entity = pop->entity_iarray[permutation[i]];
pop->entity_iarray[permutation[i]] = pop->entity_iarray[rank];
pop->entity_iarray[rank] = entity;
}
ga_entity_dereference_by_rank(pop, rank);
}
else
{
rank = ga_get_entity_rank(pop, son);
if (son->fitness < mother->fitness)
{
entity = pop->entity_iarray[i];
pop->entity_iarray[i] = pop->entity_iarray[rank];
pop->entity_iarray[rank] = entity;
}
ga_entity_dereference_by_rank(pop, rank);
rank = ga_get_entity_rank(pop, daughter);
if (daughter->fitness < father->fitness)
{
entity = pop->entity_iarray[permutation[i]];
pop->entity_iarray[permutation[i]] = pop->entity_iarray[rank];
pop->entity_iarray[rank] = entity;
}
ga_entity_dereference_by_rank(pop, rank);
}
}
/*
* Use callback.
*/
plog(LOG_VERBOSE,
"After generation %d, population has fitness scores between %f and %f",
generation,
pop->entity_iarray[0]->fitness,
pop->entity_iarray[pop->size-1]->fitness );
} /* Generation loop. */
/*
* Ensure final ordering of population is correct.
*/
sort_population(pop);
return generation;
}
boolean random_boolean_prob_wrapper(double *prob)
{
return random_boolean_prob(*prob);
}
double wildfire_simulation(int map[WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION], boolean show)
{
int time; /* Simulation time. */
int burning[WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION]; /* Map. */
int crews[WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION]; /* Map. */
int num_burnt=0; /* Number of burnt squares. */
int i, j, k; /* Loop variables. */
int p; /* Selected map square. */
int dir; /* Wind direction. */
/* Start with no burnt squares. */
for(p=0; p<WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION; p++)
burning[p] = 0;
/* Random initial wind direction. */
dir = random_int(4);
/* Perform simulation. */
for(time=0; time<WILDFIRE_TIME; time++)
{
/* Set fire to random squares. */
for(i=0; i<WILDFIRE_FLASHPOINTS; i++)
{
p = random_int(WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION);
if (map[p] == 0 && burning[p] == 0) burning[p]=1;
}
/* Apply the wind direction changing. */
if (WILDFIRE_PREDICTABLE_WIND == TRUE)
{
if (dir==3)
dir=0;
else
dir++;
}
else if ( random_boolean_prob(WILDFIRE_WIND_CHANGE_PROB) )
{
dir = random_int(4);
}
/* Fire crews try their best. */
/* Look for fires that can spread most easily, and extinguish them. */
/* FIXME: Implement firecrews to take account of predictable winds. */
/* Currently very simple: Extinguish fires that will spread the most
during this day. */
/* Firstly, assess the fires. */
switch (dir)
{
case 0:
/* North */
for(p=0; p<WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION; p++)
{
if (burning[p] > 0 && burning[p] < 2)
{
crews[p]=1;
while( crews[p]<WILDFIRE_WIND_SPEED &&
(j=p-crews[p]*WILDFIRE_X_DIMENSION)>0 &&
map[j] == 0 &&
burning[j] == 0 )
{
crews[p]++;
}
}
else
{
crews[p]=0;
}
}
break;
case 1:
/* East */
for(p=WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION-1; p>=0; p--)
{
if (burning[p] > 0 && burning[p] < 2)
{
crews[p]=1;
while( crews[p]<WILDFIRE_WIND_SPEED &&
(j=p+crews[p])%WILDFIRE_X_DIMENSION<(WILDFIRE_X_DIMENSION-1) &&
map[j] == 0 &&
burning[j] == 0 )
{
crews[p]++;
}
}
else
{
crews[p]=0;
}
}
break;
case 2:
/* South */
for(p=WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION-1; p>=0; p--)
{
if (burning[p] > 0 && burning[p] < 2)
{
crews[p]=1;
while( crews[p]<WILDFIRE_WIND_SPEED &&
(j=p+crews[p]*WILDFIRE_X_DIMENSION)<(WILDFIRE_Y_DIMENSION-1) &&
map[j] == 0 &&
burning[j] == 0 )
{
crews[p]++;
}
}
else
{
crews[p]=0;
}
}
break;
case 3:
/* West */
for(p=0; p<WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION; p++)
{
if (burning[p] > 0 && burning[p] < 2)
{
crews[p]=1;
while( crews[p]<WILDFIRE_WIND_SPEED &&
(j=p-crews[p])%WILDFIRE_X_DIMENSION>0 &&
map[j] == 0 &&
burning[j] == 0 )
{
crews[p]++;
}
}
else
{
crews[p]=0;
}
}
break;
}
/* Assign the firecrews. */
k = WILDFIRE_CREWS;
j = WILDFIRE_WIND_SPEED;
while (j>0 && k>0)
{
for(p=0; p<WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION && k>0; p++)
{
if (crews[p]==j)
{
crews[p]=-1;
burning[p]=0;
k--;
}
}
j--;
}
/* Age fires. */
for(p=0; p<WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION; p++)
{
if (burning[p] > 0 ) burning[p]++;
}
for (k=0; k<WILDFIRE_WIND_SPEED; k++)
{
/* Spread fires. */
switch (dir)
{
case 0:
/* North */
for(p=0; p<WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION; p++)
{
if (burning[p] > 0 && burning[p] < 3)
{
if (p>WILDFIRE_X_DIMENSION)
if ( map[p-WILDFIRE_X_DIMENSION] == 0 &&
burning[p-WILDFIRE_X_DIMENSION] == 0 &&
crews[p-WILDFIRE_X_DIMENSION] != -1 )
burning[p-WILDFIRE_X_DIMENSION]=1;
}
}
break;
case 1:
/* East */
for(p=WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION-1; p>=0; p--)
{
if (burning[p] > 0 && burning[p] < 3)
{
if (p%WILDFIRE_X_DIMENSION<(WILDFIRE_X_DIMENSION-1))
if ( map[p+1] == 0 &&
burning[p+1] == 0 &&
crews[p+1] != -1 )
burning[p+1]=1;
}
}
break;
case 2:
/* South */
for(p=WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION-1; p>=0; p--)
{
if (burning[p] > 0 && burning[p] < 3)
{
if (p<WILDFIRE_X_DIMENSION*(WILDFIRE_Y_DIMENSION-1))
if ( map[p+WILDFIRE_X_DIMENSION] == 0 &&
burning[p+WILDFIRE_X_DIMENSION] == 0 &&
crews[p+WILDFIRE_X_DIMENSION] != -1 )
burning[p+WILDFIRE_X_DIMENSION]=1;
}
}
break;
case 3:
/* West */
for(p=0; p<WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION; p++)
{
if (burning[p] > 0 && burning[p] < 3)
{
if (p%WILDFIRE_X_DIMENSION>0)
if ( map[p-1] == 0 &&
burning[p-1] == 0 &&
crews[p-1] != -1 )
burning[p-1]=1;
}
}
break;
}
}
}
/* Count number of burnt squares. */
for(i=0; i<WILDFIRE_X_DIMENSION*WILDFIRE_Y_DIMENSION; i++)
if (burning[i]!=0) num_burnt++;
if (show)
{
printf("Map after simulation is:\n");
for (i=0; i<WILDFIRE_Y_DIMENSION; i++)
{
for (k=0; k<WILDFIRE_X_DIMENSION; k++)
{
printf( "%s ", map[i*WILDFIRE_X_DIMENSION+k]?"o":
((burning[i*WILDFIRE_X_DIMENSION+k]==0)?
((crews[i*WILDFIRE_X_DIMENSION+k]==-1)?"*":"."):"x") );
}
printf("\n");
}
}
return num_burnt;
}