c'est 'bon'

javaAPI/fr/iut_fbleau/HexGame/HeuristicBot.java

@@ -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
                 }
             }

javaAPI/fr/iut_fbleau/HexGame/HexMain.java

@@ -1,7 +1,6 @@
 package fr.iut_fbleau.HexGame;
 
 import fr.iut_fbleau.GameAPI.*;
-
 import java.util.EnumMap;
 import java.util.Scanner;
 
@@ -11,7 +10,7 @@ import java.util.Scanner;
 public class HexMain {
 
     public static void main(String[] args) {
-        int size = 11;
+        int size = 7;
         if (args.length >= 1) {
             try { size = Integer.parseInt(args[0]); } catch (NumberFormatException ignored) {}
         }
@@ -19,12 +18,19 @@ public class HexMain {
         HexBoard board = new HexBoard(size);
 
         Scanner sc = new Scanner(System.in);
+        Result res;
         EnumMap<Player, AbstractGamePlayer> players = new EnumMap<>(Player.class);
         players.put(Player.PLAYER1, new HumanConsolePlayer(Player.PLAYER1, sc));
         players.put(Player.PLAYER2, new HumanConsolePlayer(Player.PLAYER2, sc));
 
+
+        if (args.length>=2 && args[1].equals("autoplay")) {
+            Simulation sim = new Simulation(board, players);
+            res = sim.run(); 
+        } else {
             AbstractGame game = new AbstractGame(board, players) {};
-        Result res = game.run();
+            res = game.run();
+        }
 
         System.out.println(board);
         System.out.println("Résultat (du point de vue de PLAYER1) : " + res);

javaAPI/fr/iut_fbleau/HexGame/MiniMaxBot.java

@@ -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
                 }
             }

javaAPI/fr/iut_fbleau/HexGame/MonteCarloBot.java

@@ -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;

javaAPI/fr/iut_fbleau/HexGame/Simulation.java

@@ -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;