guezoloic/SNAKE
1
0
Fork 0
mirror of https://github.com/Cpt-Adok/SNAKE.git synced 2026-01-25 06:34:06 +00:00
Code Issues Packages Projects Releases Wiki Activity

changement dans la façon qu'il apprend

Browse Source
This commit is contained in:
guezoloic
2024-06-04 12:08:46 +02:00
parent b40750c4ed
commit 99c814c37f
6 changed files with 52 additions and 46 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
Makefile
View File

@@ -27,7 +27,7 @@ $(BIN_DIR)/$(MAIN_FILE).class : $(SRC_DIR)/$(MAIN_FILE).java
$(JAVAC) -d $(BIN_DIR) -sourcepath $(SRC_DIR) -classpath $(JAR) $< $(JAVAC) -d $(BIN_DIR) -sourcepath $(SRC_DIR) -classpath $(JAR) $<
run: run:
java -cp $(BIN_DIR) $(MAIN_FILE) $(channel) $(adversaire) java -Xmx16g -cp $(BIN_DIR) $(MAIN_FILE) $(channel) $(adversaire)
clean: clean:
@rm -rf $(BIN_DIR) @rm -rf $(BIN_DIR)

BIN
res/save/learn.ser
View File

Binary file not shown.

BIN
res/save/learn1.ser Normal file
View File

Binary file not shown.

BIN
res/save/learn2.ser Normal file
View File

Binary file not shown.

44
src/Main.java
View File

@@ -8,46 +8,44 @@ import tests.IATest;
public class Main { public class Main {
public static void main(String[] args) { public static void main(String[] args) {
// Personnage.n = 4; Personnage.n = 4;
// Map map = new Map(12, 22); Map map = new Map(12, 22);
// // lancer en local // // lancer en local
// if (args.length < 2) { if (args.length < 2) {
// Grid[][] grid = map.getGrid(); Grid[][] grid = map.getGrid();
// QTable qTable1 = new QTable(); // QTable qTable1 = new QTable();
// qTable1.getValues("path_to_save_qtable1.ser"); // qTable1.getValues("res" + File.separator + "save" + File.separator + "learn1.ser");
// QTable qTable2 = new QTable(); // QTable qTable2 = new QTable();
// qTable2.getValues("path_to_save_qtable2.ser"); // qTable2.getValues("res" + File.separator + "save" + File.separator + "learn1.ser");
// // Avant de jouer contre l'ia, vous pouvez essayer de l'entrainer avec la fonction tests.IATest.learnIAvsIA() // // Avant de jouer contre l'ia, vous pouvez essayer de l'entrainer avec la fonction tests.IATest.learnIAvsIA()
// // il jouera avec lui meme et mettra les sauvegardes dans le dossier learn.ser, // // il jouera avec lui meme et mettra les sauvegardes dans le dossier learn.ser,
// // Attention lors de l'apprentissage, ne pas couper le processus sinon vous allez perdre toute vos donnees // // Attention lors de l'apprentissage, ne pas couper le processus sinon vous allez perdre toute vos donnees
// Personnage[] personnages = new Personnage[] { Personnage[] personnages = new Personnage[] {
// new IAQLearning(new int[] {2, 2}, qTable1), // new IAQLearning(new int[] {2, 2}, qTable1),
// // new Player(new int[] {2, 2}, "Philippe Etchebest"), new Player(new int[] {2, 2}, "Philippe Etchebest"),
// // new Player(new int[] {grid[0].length - 3, grid.length - 3}, "Luke Skywalker"), new Player(new int[] {grid[0].length - 3, grid.length - 3}, "Luke Skywalker"),
// // new Robot("Robot", new int[] {grid[0].length - 3, grid.length - 3}), // new Robot("Robot", new int[] {grid[0].length - 3, grid.length - 3}),
// new IAQLearning(new int[] {grid[0].length - 3, grid.length - 3}, qTable2), // new IAQLearning(new int[] {grid[0].length - 3, grid.length - 3}, qTable2),
// }; };
// // map.addObjectsRandomize(new Item[] {Item.FRAISE, Item.WALL}, 2); // map.addObjectsRandomize(new Item[] {Item.FRAISE, Item.WALL}, 2);
// // map.addObjects(Item.FRAISE, 2, 2); // map.addObjects(Item.FRAISE, 2, 2);
// new Terminal(map, personnages).run(); new Terminal(map, personnages).run();
// } }
// // lancer en ligne // // lancer en ligne
// else { else {
// Personnage[] personnages = new Personnage[] { Personnage[] personnages = new Personnage[] {
// new Player(new int[] {0, 0}, "Philippe Etchebest"), new Player(new int[] {0, 0}, "Philippe Etchebest"),
// }; };
// new Terminal(map, personnages).run(args[0], args[1]); new Terminal(map, personnages).run(args[0], args[1]);
// } }
IATest.learnIAvsIA();
} }
} }

38
src/tests/IATest.java
View File

@@ -13,9 +13,13 @@ import personnage.Personnage;
import types.Mouvement; import types.Mouvement;
public class IATest { public class IATest {
private final static String path = "res" + File.separator + private final static String path1 = "res" + File.separator +
"save" + File.separator + "save" + File.separator +
"learn.ser"; "learn1.ser";
private final static String path2 = "res" + File.separator +
"save" + File.separator +
"learn2.ser";
public static void learnIA() { public static void learnIA() {
double alpha = 0.1; double alpha = 0.1;
@@ -33,7 +37,7 @@ public class IATest {
IAQLearning iaqLearning = new IAQLearning(new int[] {2, 2}, qTable, alpha, gamma, epsilon); IAQLearning iaqLearning = new IAQLearning(new int[] {2, 2}, qTable, alpha, gamma, epsilon);
Map map = new Map(12, 22); Map map = new Map(12, 22);
qTable.getValues(path); qTable.getValues(path1);
while (true) { while (true) {
Map mapIA = new Map(map.getGrid()[0].length, map.getGrid().length); Map mapIA = new Map(map.getGrid()[0].length, map.getGrid().length);
@@ -64,31 +68,34 @@ public class IATest {
map.clearMap(); map.clearMap();
} }
qTable.save(path); qTable.save(path1);
epsilon = Math.max(minEpsilon, epsilon * decay_rate); epsilon = Math.max(minEpsilon, epsilon * decay_rate);
System.out.println("Episode : " + episode + " | Robot 1 States : " + qTable.getqValues().size()); System.out.println("Episode : " + episode + " | States : " + qTable.getqValues().size());
} }
} }
public static void learnIAvsIA() { public static void learnIAvsIA() {
double alpha = 0.1; double alpha = 0.9;
double gamma = 0.9; double gamma = 0.9;
double epsilon = 0.1; double epsilon = 0.1;
int maxEpisode = 1000; int maxEpisode = 1000000;
Personnage.n = 4; Personnage.n = 4;
for (int episode = 0; episode < maxEpisode; episode++) { QTable qTable1 = new QTable();
QTable qTable = new QTable(); qTable1.getValues(path1);
qTable.getValues(path);
QTable qTable2 = new QTable();
qTable2.getValues(path2);
for (int episode = 0; episode < maxEpisode; episode++) {
Map map = new Map(12, 22); Map map = new Map(12, 22);
IAQLearning[] iaqLearnings = new IAQLearning[] { IAQLearning[] iaqLearnings = new IAQLearning[] {
new IAQLearning(new int[] {2, 2}, qTable, alpha, gamma, epsilon), new IAQLearning(new int[] {2, 2}, qTable1, alpha, gamma, epsilon),
new IAQLearning(new int[] {9, 19}, qTable, alpha, gamma, epsilon), new IAQLearning(new int[] {9, 19}, qTable2, alpha, gamma, epsilon),
}; };
boolean isGameOver = false; boolean isGameOver = false;
@@ -136,13 +143,14 @@ public class IATest {
mapIA.clearMap(); mapIA.clearMap();
map.clearMap(); map.clearMap();
System.out.println("States 1: " + qTable1.getqValues().size() + " States 2: " + qTable2.getqValues().size());
} }
if(isGameOver) break; if(isGameOver) break;
qTable.save(path);
System.out.println("Episode: " + episode + " States: " + qTable.getqValues().size());
} }
System.out.println(" States 1: " + qTable1.getqValues().size() + " States 2: " + qTable2.getqValues().size() + "Episode: " + episode);
} }
qTable1.save(path1);
} }
} }