4 Commits

Author SHA1 Message Date
vaisse c278b18872 definable size for arena 2026-02-06 11:25:47 +01:00
vaisse e0a2c2642a c'est 'bon' 2026-02-06 11:13:37 +01:00
vaisse c9e559fe12 cette fois-ci ce sera la bonne 2026-02-06 11:01:27 +01:00
vaisse 98c6b4678e par pitié 2026-02-06 11:00:03 +01:00
18 changed files with 123 additions and 103 deletions
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+7
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@@ -0,0 +1,7 @@
Bot 1, Bot 2, Winner
RandomBot,MiniMaxBot,WIN
RandomBot,HeuristicBot,WIN
RandomBot,MonteCarloBot,WIN
MiniMaxBot,HeuristicBot,WIN
MiniMaxBot,MonteCarloBot,WIN
HeuristicBot,MonteCarloBot,WIN
1 Bot 1 Bot 2 Winner
2 RandomBot MiniMaxBot WIN
3 RandomBot HeuristicBot WIN
4 RandomBot MonteCarloBot WIN
5 MiniMaxBot HeuristicBot WIN
6 MiniMaxBot MonteCarloBot WIN
7 HeuristicBot MonteCarloBot WIN
+4 -2
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@@ -12,11 +12,13 @@ public class Arena {
private List<AbstractGamePlayer> bots = new ArrayList<>();
private FileWriter csvWriter;
private int board_size;
public Arena() {
public Arena(int size) {
try {
csvWriter = new FileWriter("arena_results.csv");
csvWriter.append("Bot 1, Bot 2, Winner\n");
this.board_size = size;
} catch (IOException e) {
e.printStackTrace();
}
@@ -51,7 +53,7 @@ public class Arena {
}
private Result playMatch(AbstractGamePlayer bot1, AbstractGamePlayer bot2) {
IBoard board = new HexBoard(11);
IBoard board = new HexBoard(this.board_size);
EnumMap<Player, AbstractGamePlayer> players = new EnumMap<>(Player.class);
players.put(Player.PLAYER1, bot1);
players.put(Player.PLAYER2, bot2);
+5 -1
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@@ -4,7 +4,11 @@ import fr.iut_fbleau.GameAPI.Player;
public class ArenaMain {
public static void main(String[] args) {
Arena arena = new Arena();
int size = 7;
if (args.length >= 1) {
try { size = Integer.parseInt(args[0]); } catch (NumberFormatException ignored) {}
}
Arena arena = new Arena(size);
arena.addBot(new RandomBot(Player.PLAYER1, 12345L)); // Correct constructor usage
arena.addBot(new MiniMaxBot(Player.PLAYER2));
arena.addBot(new HeuristicBot(Player.PLAYER1));
@@ -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
}
}
+9 -3
View File
@@ -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);
@@ -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
}
}
@@ -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;
+19 -19
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;