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Conscious_Openmp.c
360 lines (294 loc) · 8.79 KB
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Conscious_Openmp.c
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#include <stdio.h>
#include <stdarg.h>
#include <stdlib.h>
#include <windows.h>
#include <omp.h>
#ifndef GLOBAL
#define GLOBAL "Global.h"
#include GLOBAL
#endif
#include "EvalueFunc.c"
#include "GameBoard.c"
#define GROUP_SIZE 50
#define CROSSOVER_RATE 50
#define MUTATION_RATE 10
FILE *fout, *record;
void NextStep(Board ,Board , int*, int,...);
int PlayGame();
double Evalue(int *);
void GeneticAlgorithm();
void InitGroup(int [][COUNT_FUNC]);
void Eliminate(int [][COUNT_FUNC]);
void Crossover(int [][COUNT_FUNC]);
void Mutation (int [][COUNT_FUNC]);
void PrintGene(int [][COUNT_FUNC]);
void Record(int [][COUNT_FUNC]);
int main(int argc, char *argv[]){
int test[] = {1217,-183,1357,-1250,-345,193,-2,-1066,1285,-1127};
srand(time(NULL));
if (PLAY_MODE == 1)
PlayGame(test);
else
GeneticAlgorithm();
return 0;
}
int PlayGame(int *Parameter){
Board gameBoard,nextBoard;
int i;
int maxLevel;
InitGame(gameBoard);
PrintBoard(gameBoard);
while (1){
NextStep(nextBoard,gameBoard, Parameter, COUNT_STEP, MoveLeft, MoveRight, MoveUp, MoveDown);
UpdateBoard(gameBoard,nextBoard);
maxLevel = FinishGame(gameBoard);
if ( maxLevel != 0){
break;
}
if (PLAY_MODE == 1)
if ( TotalScore > 1000)
Sleep(1000);
else
Sleep(100);
}
return maxLevel;
}
void GeneticAlgorithm(){
int maxIter = 100;
int i,j,k;
int group[GROUP_SIZE][COUNT_FUNC];
int oldParameter[COUNT_FUNC];
int maxIndex;
double sum,max,min,tmp;
int count_record = 0;
char output[300];
/*初始族群*/
InitGroup(group);
for ( i = 0 ; i < maxIter ; i++){
Eliminate(group);
Crossover(group);
Mutation(group);
sum = 0;
max = -1;
min = 20;
maxIndex = 0;
#pragma omp parallel for
for ( j = 0 ; j < GROUP_SIZE ; j++){
tmp= Evalue( group[j]);
if ( tmp > 10){
fout = fopen("parameter.txt", "a");
sprintf(output,"Parameter = ");
for ( k = 0 ; k < COUNT_FUNC ; k++){
sprintf(output,"%s %5d",output, group[j][k]);
}
sprintf(output,"%s, Score = %lf\n",output,tmp);
fprintf(fout,"%s",output);
fclose(fout);
}
sum += tmp;
if ( tmp > max ){
max= tmp;
maxIndex = j;
}
if ( tmp < min )
min = tmp;
}
if ( i % 10 == 0)
Record(group);
printf("Level(%d) = %.2lf, %.2lf, %.2lf\n", i,max,sum/GROUP_SIZE,min);
if ( max >= 10.5 && PlayGame(group[maxIndex]) >= 10.9)
break;
}
printf("==Result==\n");
for ( i = 0 ; i < COUNT_FUNC ; i++){
printf(", %d", group[maxIndex][i]);
}
putchar('\n');
}
void Record(int group[][COUNT_FUNC]){
int i,j;
char output[10000];
memset(output,0,10000);
record = fopen("record.txt","w");
for ( i = 0 ; i < GROUP_SIZE ; i++){
sprintf(output,"%sParameter %d :",output, i);
for ( j = 0 ; j < COUNT_FUNC ; j++){
sprintf(output,"%s %5d",output, group[i][j]);
}
sprintf(output,"%s , score = %d\n",output, PlayGame(group[i]) );
}
fprintf(record,"%s",output);
fclose(record);
}
void PrintGene(int group[][COUNT_FUNC]){
int i,j;
for ( i = 0 ; i < GROUP_SIZE ; i++){
printf("Parameter %d :",i);
for (j = 0 ; j < COUNT_FUNC ; j++){
printf(" %3d", group[i][j]);
}
putchar('\n');
}
}
void InitGroup(int group[][COUNT_FUNC]){
int i,j;
FILE *fin;
if ( INPUT_MODE != 0)
fin = fopen("record.txt","r");
for ( i = 0 ; i < GROUP_SIZE ; i++){
for ( j = 0 ; j < COUNT_FUNC ; j++){
if (INPUT_MODE == 0){
if (EVALE_MODE == 0)
group[i][j] = rand()%21 -10;
else
group[i][j] = rand()%11;
}
else
fscanf(fin,"%d",&group[i][j]);
}
}
if (INPUT_MODE != 0)
fclose(fin);
printf("Init...\n");
PrintGene(group);
}
/*基因有一定的機率突變，突變範圍是 -50% ~ 50%*/
void Mutation(int group[][COUNT_FUNC]){
int i,j;
int tmp;
#pragma omp parallel for
for ( i = 0 ; i < GROUP_SIZE ; i++){
if ( (rand()%100 + 1) <= MUTATION_RATE ){
for ( j = 0 ; j < COUNT_FUNC ; j++){
if ( EVALE_MODE == 0)
group[i][j] = rand()%3100 - 1500 ;
else
group[i][j] = rand()%1500 ;
}
}
}
if (GA_DEBUG_MODE == 1){
printf("==Mutation==\n");
PrintGene(group);
}
}
void Crossover(int group[][COUNT_FUNC]){
int i,j;
int copy[GROUP_SIZE][COUNT_FUNC];
int index[2][GROUP_SIZE/2];
int countA,countB;
int crossoverPoint;
for (i = 0 ; i < GROUP_SIZE ; i++){
for ( j = 0 ; j < COUNT_FUNC ; j++){
copy[i][j] = group[i][j];
}
}
countA = 0;
countB = 0;
for ( i = 0 ; i < GROUP_SIZE ; i++){
if ( (rand()%2 == 0 && countA < GROUP_SIZE/2) || countB >= GROUP_SIZE/2 )
index[0][countA++] = i;
else
index[1][countB++] = i;
}
if ( countA != countB)
printf("Partition Error\n");
#pragma omp parallel for
for ( i = 0 ; i < GROUP_SIZE/2 ; i++){
if ( (rand()%100 + 1) <= CROSSOVER_RATE ){
crossoverPoint = rand()%(COUNT_FUNC-2) + 1;
/**printf(" %d <-> %d at (%d)\n", index[0][i], index[1][i], crossoverPoint);*/
for ( j = 0 ; j < COUNT_FUNC ; j++){
if ( j < crossoverPoint){
group[ index[0][i] ][j] = copy[ index[0][i] ][j];
group[ index[1][i] ][j] = copy[ index[1][i] ][j];
}
else{
group[ index[0][i] ][j] = copy[ index[1][i] ][j];
group[ index[1][i] ][j] = copy[ index[0][i] ][j];
}
}
}
}
if (GA_DEBUG_MODE == 1){
printf("==Crossover==\n");
PrintGene(group);
}
}
/*依照每組基因的分數來篩選基因，分數越高越有機會被選上*/
void Eliminate( int group[][COUNT_FUNC]){
int probability[GROUP_SIZE];
int copy[GROUP_SIZE][COUNT_FUNC];
int i,j;
int sum, tmp;
int index;
int random;
//int offset[] = {1,2,4,8,16,32,64,128,256,512,1024,2048};
int offset[] = {1,4,9,16,25,36,49,64,81,100,121};
sum = 0;
for (i = 0; i < GROUP_SIZE ; i++){
tmp = (int)(Evalue(group[i]));
tmp = offset[tmp];
sum += tmp;
if ( i == 0 )
probability[i] = tmp;
else
probability[i] = probability[i-1] + tmp;
}
for (i = 0 ; i < GROUP_SIZE ; i++){
for ( j = 0 ; j < COUNT_FUNC ; j++){
copy[i][j] = group[i][j];
}
}
for ( i = 0 ; i < GROUP_SIZE ; i++){
random = rand()%sum + 1;
for ( j = 0 ; j < GROUP_SIZE ; j++){
if ( probability[j] >= random){
index = j;
break;
}
}
for ( j = 0 ; j < COUNT_FUNC ;j++)
group[i][j] = copy[index][j];
}
if ( i != GROUP_SIZE){
printf("Eliminate Error\n");
}
if (GA_DEBUG_MODE == 1){
printf("==Eliminate==\n");
PrintGene(group);
}
}
/*計算每組基因的分數*/
double Evalue(int *Parameter){
double round = ROUND;
double score = 0;
int i;
#pragma omp parallel for
for (i = 0 ; i < ROUND ; i++){
score += PlayGame(Parameter);
}
score /= round;
return score;
}
void NextStep(Board nextBoard,Board gameBoard,int *weightParameter, int count_step,...){
int i;
int maxScore, tmp_score;
int modified;
Movement maxChoice, tmp_choice;
va_list moveStep;
va_start(moveStep, count_step);
maxScore = -2147483647;
for ( i = 0 ; i< count_step ; i ++){
tmp_choice= va_arg(moveStep, Movement);
modified =tmp_choice(nextBoard, gameBoard);
if (modified == 1){
tmp_score = Frame_CalculateScore(nextBoard, weightParameter);
if ( tmp_score > maxScore){
maxScore = tmp_score;
maxChoice = tmp_choice;
}
}
}
maxChoice(nextBoard,gameBoard);
}