Compare commits
5 Commits
| Author | SHA1 | Date | |
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| fe13b946b1 | |||
| c278b18872 | |||
| e0a2c2642a | |||
| c9e559fe12 | |||
| 98c6b4678e |
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@@ -0,0 +1 @@
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,vaisse,salle235-12,06.02.2026 11:29,file:///export/home/an23/vaisse/.config/libreoffice/4;
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@@ -0,0 +1,7 @@
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Bot 1, Bot 2, Winner
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RandomBot,MiniMaxBot,WIN
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RandomBot,HeuristicBot,WIN
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RandomBot,MonteCarloBot,WIN
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MiniMaxBot,HeuristicBot,WIN
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MiniMaxBot,MonteCarloBot,WIN
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HeuristicBot,MonteCarloBot,WIN
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@@ -26,5 +26,6 @@ public abstract class AbstractGamePlayer {
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* @throws IllegalStateException if the Situation is already in the bookmarks
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*/
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public abstract AbstractPly giveYourMove(IBoard p);
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public abstract Boolean jesuisMinimax();
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}
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@@ -12,11 +12,13 @@ public class Arena {
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private List<AbstractGamePlayer> bots = new ArrayList<>();
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private FileWriter csvWriter;
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private int board_size;
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public Arena() {
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public Arena(int size) {
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try {
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csvWriter = new FileWriter("arena_results.csv");
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csvWriter.append("Bot 1, Bot 2, Winner\n");
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this.board_size = size;
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} catch (IOException e) {
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e.printStackTrace();
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}
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@@ -51,12 +53,12 @@ public class Arena {
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}
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private Result playMatch(AbstractGamePlayer bot1, AbstractGamePlayer bot2) {
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IBoard board = new HexBoard(11);
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IBoard board = new HexBoard(this.board_size);
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EnumMap<Player, AbstractGamePlayer> players = new EnumMap<>(Player.class);
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players.put(Player.PLAYER1, bot1);
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players.put(Player.PLAYER2, bot2);
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Simulation simulation = new Simulation(board, players);
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return simulation.run();
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return simulation.runForArena();
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}
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}
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@@ -4,8 +4,12 @@ import fr.iut_fbleau.GameAPI.Player;
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public class ArenaMain {
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public static void main(String[] args) {
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Arena arena = new Arena();
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arena.addBot(new RandomBot(Player.PLAYER1, 12345L)); // Correct constructor usage
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int size = 7;
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if (args.length >= 1) {
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try { size = Integer.parseInt(args[0]); } catch (NumberFormatException ignored) {}
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}
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Arena arena = new Arena(size);
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arena.addBot(new RandomBot(Player.PLAYER1, 24015L)); // Correct constructor usage
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arena.addBot(new MiniMaxBot(Player.PLAYER2));
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arena.addBot(new HeuristicBot(Player.PLAYER1));
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arena.addBot(new MonteCarloBot(Player.PLAYER2)); // Correct constructor usage
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@@ -8,6 +8,10 @@ public class HeuristicBot extends AbstractGamePlayer {
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super(me); // Correct constructor usage
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}
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public Boolean jesuisMinimax(){
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return false;
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}
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@Override
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public AbstractPly giveYourMove(IBoard board) {
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HexBoard hb = (HexBoard) board;
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@@ -35,10 +39,11 @@ public class HeuristicBot extends AbstractGamePlayer {
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int size = board.getSize();
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int center = size / 2;
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float score = 0;
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//HexBoard simBoard = (HexBoard) board.safeCopy();
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for (int i = 0; i < size; i++) {
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for (int j = 0; j < size; j++) {
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if (board.getPlayerAt(i, j) == Player.PLAYER1) {
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if (board.getCellPlayer(i, j) == Player.PLAYER1) {
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score += Math.abs(i - center) + Math.abs(j - center); // Distance from center
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}
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}
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@@ -1,7 +1,6 @@
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package fr.iut_fbleau.HexGame;
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import fr.iut_fbleau.GameAPI.*;
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import java.util.EnumMap;
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import java.util.Scanner;
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@@ -11,7 +10,7 @@ import java.util.Scanner;
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public class HexMain {
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public static void main(String[] args) {
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int size = 11;
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int size = 7;
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if (args.length >= 1) {
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try { size = Integer.parseInt(args[0]); } catch (NumberFormatException ignored) {}
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}
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@@ -19,12 +18,19 @@ public class HexMain {
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HexBoard board = new HexBoard(size);
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Scanner sc = new Scanner(System.in);
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Result res;
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EnumMap<Player, AbstractGamePlayer> players = new EnumMap<>(Player.class);
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players.put(Player.PLAYER1, new HumanConsolePlayer(Player.PLAYER1, sc));
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players.put(Player.PLAYER2, new HumanConsolePlayer(Player.PLAYER2, sc));
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if (args.length>=2 && args[1].equals("autoplay")) {
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Simulation sim = new Simulation(board, players);
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res = sim.run();
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} else {
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AbstractGame game = new AbstractGame(board, players) {};
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Result res = game.run();
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res = game.run();
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}
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System.out.println(board);
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System.out.println("Résultat (du point de vue de PLAYER1) : " + res);
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@@ -18,6 +18,10 @@ public class HumanConsolePlayer extends AbstractGamePlayer {
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this.in = in;
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}
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public Boolean jesuisMinimax(){
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return false;
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}
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@Override
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public AbstractPly giveYourMove(IBoard board) {
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if (!(board instanceof HexBoard)) {
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@@ -10,6 +10,10 @@ public class MiniMaxBot extends AbstractGamePlayer {
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super(me); // Correct constructor usage
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}
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public Boolean jesuisMinimax(){
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return true;
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}
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@Override
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public AbstractPly giveYourMove(IBoard board) {
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HexBoard hb = (HexBoard) board;
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@@ -79,7 +83,7 @@ public class MiniMaxBot extends AbstractGamePlayer {
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int score = 0;
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for (int i = 0; i < size; i++) {
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for (int j = 0; j < size; j++) {
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if (board.getPlayerAt(i, j) == Player.PLAYER1) {
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if (board.getCellPlayer(i, j) == Player.PLAYER1) {
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score += Math.abs(i - center) + Math.abs(j - center); // Distance from center
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}
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}
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@@ -12,6 +12,10 @@ public class MonteCarloBot extends AbstractGamePlayer {
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super(me); // Correct constructor usage
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}
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public Boolean jesuisMinimax(){
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return false;
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}
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@Override
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public AbstractPly giveYourMove(IBoard board) {
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HexBoard hb = (HexBoard) board;
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@@ -37,7 +41,7 @@ public class MonteCarloBot extends AbstractGamePlayer {
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private float monteCarloSimulation(HexBoard board) {
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RandomBot simBot = new RandomBot(Player.PLAYER1, new Random().nextLong());
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HexBoard simBoard = board.safeCopy();
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HexBoard simBoard = (HexBoard) board.safeCopy();
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int wins = 0;
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int simulations = 0;
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@@ -51,7 +55,7 @@ public class MonteCarloBot extends AbstractGamePlayer {
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wins++;
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}
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simulations++;
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simBoard = board.safeCopy(); // Reset the board for the next simulation
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simBoard = (HexBoard) board.safeCopy(); // Reset the board for the next simulation
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}
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return (float) wins / simulations;
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@@ -19,6 +19,10 @@ public class RandomBot extends AbstractGamePlayer {
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this.rng = rng;
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}
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public Boolean jesuisMinimax(){
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return false;
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}
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public RandomBot(Player me, long seed) {
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this(me, new Random(seed));
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}
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@@ -3,6 +3,7 @@ package fr.iut_fbleau.HexGame;
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import fr.iut_fbleau.GameAPI.*;
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import java.util.EnumMap;
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import java.util.LinkedList;
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import java.util.Random;
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public class Simulation extends AbstractGame {
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@@ -27,18 +28,19 @@ public class Simulation extends AbstractGame {
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//METHODES
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/*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*/
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private float MonteCarlo(HexBoard position){
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RandomBot simplay = new RandomBot();
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HexBoard simpos = position.safeCopy();
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private float MonteCarlo(HexBoard position, Player current){
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RandomBot simplay = new RandomBot(current, new Random().nextLong());
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HexBoard simpos = position;
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LinkedList<Integer[]> ctaken = taken;
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HexPly testmove;
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float wins = 0;
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float losses = 0;
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int count = 0;
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for(int i=0; i<EVALDEPTH; i++){
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while(!simpos.isGameOver()){
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count++;
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testmove = (HexPly) simplay.giveYourMove(simpos);
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if(!ctaken.contains(t) && simpos.isLegal(testmove)){
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if(!ctaken.contains(new Integer[]{testmove.getRow(), testmove.getCol()}) && simpos.isLegal(testmove)){
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ctaken.add(new Integer[]{testmove.getRow(), testmove.getCol()});
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simpos.doPly(testmove);
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if(simpos.getResult()==Result.LOSS){
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@@ -48,16 +50,16 @@ public class Simulation extends AbstractGame {
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}
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}
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}
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simpos = position.safeCopy();
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//System.out.println("count:"+count);
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for (int j=0; j<count; j++) {
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simpos.undoPly();
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}
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ctaken = taken;
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count = 0;
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}
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if(wins>=losses){
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return losses/wins;
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} else {
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return -(wins/losses);
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}
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//System.out.println(" wins : "+wins+"/losses : "+losses);
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//System.out.println(" eval : "+(wins-losses)/EVALDEPTH);
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return (wins-losses)/EVALDEPTH;
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}
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private float explMAX(HexBoard position, int depth){
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@@ -66,7 +68,7 @@ public class Simulation extends AbstractGame {
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} else if (position.getResult()==Result.WIN){
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return 1.0f;
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} else if (depth==MAXDEPTH) {
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return MonteCarlo(position);
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return MonteCarlo(position, Player.PLAYER1);
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} else {
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float bestcase = -1.0f;
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HexPly bestcasemove;
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@@ -108,7 +110,7 @@ public class Simulation extends AbstractGame {
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} else if (position.getResult()==Result.WIN){
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return 1.0f;
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} else if (depth==MAXDEPTH) {
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return MonteCarlo(position);
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return MonteCarlo(position, Player.PLAYER2);
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} else {
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float bestcase = 1.0f;
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HexPly bestcasemove;
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@@ -150,7 +152,7 @@ public class Simulation extends AbstractGame {
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} else if (position.getResult()==Result.WIN){
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return 1.0f;
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} else if (depth==MAXDEPTH) {
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return MonteCarlo(position);
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return MonteCarlo(position, Player.PLAYER1);
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} else {
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float bestcase = A;
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HexPly bestcasemove;
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@@ -187,15 +189,13 @@ public class Simulation extends AbstractGame {
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return bestcase;
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}
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}
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private float explMINAB(HexBoard position, int depth, float A, float B){
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if (position.getResult()==Result.LOSS) {
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return -1.0f;
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} else if (position.getResult()==Result.WIN){
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return 1.0f;
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} else if (depth==MAXDEPTH) {
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return MonteCarlo(position);
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return MonteCarlo(position, Player.PLAYER2);
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} else {
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float bestcase = B;
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HexPly bestcasemove;
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@@ -235,8 +235,6 @@ private float explMINAB(HexBoard position, int depth, float A, float B){
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}
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private AbstractPly GiveBestMove(IBoard board) {
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if (!(board instanceof HexBoard)) {
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throw new IllegalArgumentException("Ce joueur attend un HexBoard.");
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@@ -269,5 +267,27 @@ private float explMINAB(HexBoard position, int depth, float A, float B){
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return simCurrentBoard.getResult();
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}
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public Result runForArena(){
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while(!simCurrentBoard.isGameOver()){
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AbstractGamePlayer player = simmapPlayers.get(simCurrentBoard.getCurrentPlayer());
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IBoard board = simCurrentBoard.safeCopy();
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AbstractPly ply;
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if(player.jesuisMinimax()){
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ply = GiveBestMove(board);
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} else {
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ply = player.giveYourMove(board);
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}
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HexPly concretePly = (HexPly) ply;
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if (simCurrentBoard.isLegal(ply)) {
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simCurrentBoard.doPly(ply);
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taken.add(new Integer[]{concretePly.getRow(), concretePly.getCol()});
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System.out.println("Player "+player+" goes ("+concretePly.getRow()+","+concretePly.getCol()+")");
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}
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else throw new IllegalStateException("Player "+ player + " is a bloody cheat. He tried playing : "+concretePly.getRow()+","+concretePly.getCol()+" I give up.");
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}
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return simCurrentBoard.getResult();
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}
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}
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Reference in New Issue
Block a user