diff --git a/javaAPI/fr/iut_fbleau/HexGame/Simulation.java b/javaAPI/fr/iut_fbleau/HexGame/Simulation.java
index 61f26c3..24b5388 100644
--- a/javaAPI/fr/iut_fbleau/HexGame/Simulation.java
+++ b/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 {
@@ -27,16 +28,18 @@ 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();
+    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(new Integer[]{testmove.getRow(), testmove.getCol()}) && simpos.isLegal(testmove)){
                     ctaken.add(new Integer[]{testmove.getRow(), testmove.getCol()});
@@ -48,15 +51,18 @@ public class Simulation extends AbstractGame {
                     }
                 }
             }
-            simpos = position;
+            //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;
 
     }
 
@@ -66,7 +72,7 @@ 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 +114,7 @@ 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 +156,7 @@ 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;
@@ -194,7 +200,7 @@ 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 = B;
                 HexPly bestcasemove;