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heuristic-arena-abminmax #17

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Riad KARA-MOSTEFA wants to merge 9 commits from heuristic-arena-abminmax into master
pull from: heuristic-arena-abminmax
merge into: kara-mosr:master
Conversation 2 Commits 9 Files Changed 30 +97 -96
4 changed files with 97 additions and 96 deletions
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Showing only changes of commit 98c6b4678e - Show all commits

3
javaAPI/fr/iut_fbleau/HexGame/HeuristicBot.java
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@@ -35,10 +35,11 @@ public class HeuristicBot extends AbstractGamePlayer {
int size = board.getSize();
int center = size / 2;
float score = 0;
//HexBoard simBoard = (HexBoard) board.safeCopy();
for (int i = 0; i < size; i++) {
for (int j = 0; j < size; j++) {
if (board.getPlayerAt(i, j) == Player.PLAYER1) {
if (board.getCellPlayer(i, j) == Player.PLAYER1) {
score += Math.abs(i - center) + Math.abs(j - center); // Distance from center
}
}

2
javaAPI/fr/iut_fbleau/HexGame/MiniMaxBot.java
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@@ -79,7 +79,7 @@ public class MiniMaxBot extends AbstractGamePlayer {
int score = 0;
for (int i = 0; i < size; i++) {
for (int j = 0; j < size; j++) {
if (board.getPlayerAt(i, j) == Player.PLAYER1) {
if (board.getCellPlayer(i, j) == Player.PLAYER1) {
score += Math.abs(i - center) + Math.abs(j - center); // Distance from center
}
}

4
javaAPI/fr/iut_fbleau/HexGame/MonteCarloBot.java
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@@ -37,7 +37,7 @@ public class MonteCarloBot extends AbstractGamePlayer {
private float monteCarloSimulation(HexBoard board) {
RandomBot simBot = new RandomBot(Player.PLAYER1, new Random().nextLong());
HexBoard simBoard = board.safeCopy();
HexBoard simBoard = (HexBoard) board.safeCopy();
int wins = 0;
int simulations = 0;
@@ -51,7 +51,7 @@ public class MonteCarloBot extends AbstractGamePlayer {
wins++;
}
simulations++;
simBoard = board.safeCopy(); // Reset the board for the next simulation
simBoard = (HexBoard) board.safeCopy(); // Reset the board for the next simulation
}
return (float) wins / simulations;

38
javaAPI/fr/iut_fbleau/HexGame/Simulation.java
View File

@@ -3,6 +3,7 @@ package fr.iut_fbleau.HexGame;
import fr.iut_fbleau.GameAPI.*;
import java.util.EnumMap;
import java.util.LinkedList;
import java.util.Random;
public class Simulation extends AbstractGame {
@@ -27,18 +28,19 @@ public class Simulation extends AbstractGame {
//METHODES
/*Le jeu de Hex ne peut jamais finir avec le résultat null. En utilisant cette propriété, on peut avoir cet algorithme simplifié du monte-carlo*/
private float MonteCarlo(HexBoard position){
RandomBot simplay = new RandomBot();
HexBoard simpos = position.safeCopy();
private float MonteCarlo(HexBoard position, Player current){
RandomBot simplay = new RandomBot(current, new Random().nextLong());
HexBoard simpos = position;
LinkedList<Integer[]> ctaken = taken;
HexPly testmove;
float wins = 0;
float losses = 0;
int count = 0;
for(int i=0; i<EVALDEPTH; i++){
while(!simpos.isGameOver()){
count++;
testmove = (HexPly) simplay.giveYourMove(simpos);
if(!ctaken.contains(t) && simpos.isLegal(testmove)){
if(!ctaken.contains(new Integer[]{testmove.getRow(), testmove.getCol()}) && simpos.isLegal(testmove)){
ctaken.add(new Integer[]{testmove.getRow(), testmove.getCol()});
simpos.doPly(testmove);
if(simpos.getResult()==Result.LOSS){
@@ -48,16 +50,16 @@ public class Simulation extends AbstractGame {
}
}
}
simpos = position.safeCopy();
//System.out.println("count:"+count);
for (int j=0; j<count; j++) {
simpos.undoPly();
}
ctaken = taken;
count = 0;
}
if(wins>=losses){
return losses/wins;
} else {
return -(wins/losses);
}
System.out.println(" wins : "+wins+"/losses : "+losses);
System.out.println(" eval : "+(wins-losses)/EVALDEPTH);
return (wins-losses)/EVALDEPTH;
}
private float explMAX(HexBoard position, int depth){
@@ -66,7 +68,7 @@ public class Simulation extends AbstractGame {
} else if (position.getResult()==Result.WIN){
return 1.0f;
} else if (depth==MAXDEPTH) {
return MonteCarlo(position);
return MonteCarlo(position, Player.PLAYER1);
} else {
float bestcase = -1.0f;
HexPly bestcasemove;
@@ -108,7 +110,7 @@ public class Simulation extends AbstractGame {
} else if (position.getResult()==Result.WIN){
return 1.0f;
} else if (depth==MAXDEPTH) {
return MonteCarlo(position);
return MonteCarlo(position, Player.PLAYER2);
} else {
float bestcase = 1.0f;
HexPly bestcasemove;
@@ -150,7 +152,7 @@ public class Simulation extends AbstractGame {
} else if (position.getResult()==Result.WIN){
return 1.0f;
} else if (depth==MAXDEPTH) {
return MonteCarlo(position);
return MonteCarlo(position, Player.PLAYER1);
} else {
float bestcase = A;
HexPly bestcasemove;
@@ -187,15 +189,13 @@ public class Simulation extends AbstractGame {
return bestcase;
}
}
private float explMINAB(HexBoard position, int depth, float A, float B){
if (position.getResult()==Result.LOSS) {
return -1.0f;
} else if (position.getResult()==Result.WIN){
return 1.0f;
} else if (depth==MAXDEPTH) {
return MonteCarlo(position);
return MonteCarlo(position, Player.PLAYER2);
} else {
float bestcase = B;
HexPly bestcasemove;