add new results of needed timestamps in total
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@@ -17,11 +17,12 @@ public class RNG {
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private static Random rng;
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private static Random rngEnv;
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private static int seed = 123;
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private static int envSeed = 13;
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static {
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rng = new Random();
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rng.setSeed(seed);
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rngEnv = new Random();
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rngEnv.setSeed(seed);
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rngEnv.setSeed(13);
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}
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public static Random getRandom() {
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@@ -34,7 +35,6 @@ public class RNG {
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public static void setSeed(int seed){
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RNG.seed = seed;
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rng.setSeed(seed);
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rngEnv = new Random();
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rngEnv.setSeed(seed);
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rngEnv.setSeed(13);
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}
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}
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@@ -32,6 +32,7 @@ public class QLearningOffPolicyTDControl<A extends Enum> extends EpisodicLearnin
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@Override
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protected void nextEpisode() {
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State state = environment.reset();
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try {
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Thread.sleep(delay);
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@@ -72,19 +73,19 @@ public class QLearningOffPolicyTDControl<A extends Enum> extends EpisodicLearnin
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}*/
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if(reward == Reward.FOOD_DROP_DOWN_SUCCESS){
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if(reward == Reward.FOOD_DROP_DOWN_SUCCESS) {
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foodCollected++;
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foodTimestampsTotal += timestampTilFood;
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if(foodCollected % 1000 == 0){
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System.out.println(foodTimestampsTotal / 1000f + " " + timestampCurrentEpisode);
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File file = new File(ContinuousAnt.FILE_NAME);
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//System.out.println(foodCollected + " " + timestampCurrentEpisode);
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File file = new File(ContinuousAnt.FILE_NAME);
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if(foodCollected % 1000 == 0) {
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try {
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Files.writeString(Path.of(file.getPath()), foodTimestampsTotal/1000f +",", StandardOpenOption.APPEND);
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Files.writeString(Path.of(file.getPath()), timestampCurrentEpisode + ",", StandardOpenOption.APPEND);
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} catch (IOException e) {
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e.printStackTrace();
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}
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foodTimestampsTotal = 0;
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}
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foodTimestampsTotal = 0;
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if(foodCollected == 1000){
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((EpsilonGreedyPolicy<A>) this.policy).setEpsilon(0.15f);
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}
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@@ -98,8 +99,7 @@ public class QLearningOffPolicyTDControl<A extends Enum> extends EpisodicLearnin
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System.out.println("final 0 expl");
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((EpsilonGreedyPolicy<A>) this.policy).setEpsilon(0.00f);
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}
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if(foodCollected == 15000){
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File file = new File(ContinuousAnt.FILE_NAME);
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if(foodCollected == 30000) {
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try {
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Files.writeString(Path.of(file.getPath()), "\n", StandardOpenOption.APPEND);
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} catch (IOException e) {
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@@ -8,31 +8,47 @@ import evironment.antGame.AntWorldContinuous;
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import java.io.File;
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import java.io.IOException;
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import java.util.ArrayList;
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import java.util.List;
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public class ContinuousAnt {
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public static final String FILE_NAME = "converge22.txt";
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public static final String FILE_NAME = "optDiscTimestampsNew.txt";
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public static void main(String[] args) {
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int i = 4+4+4+6+6+6+8+10+12+14+14+16+16+16+18+18+18+20+20+20+22+22+22+24+24+24+24+26+26+26+26+26+28+28+28+28+28+30+30+30+30+32+32+32+34+34+34+36+36+38+40+42;
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System.out.println(i/52f);
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int k = 4 + 4 + 4 + 6 + 6 + 6 + 8 + 10 + 12 + 14 + 14 + 16 + 16 + 16 + 18 + 18 + 18 + 20 + 20 + 20 + 22 + 22 + 22 + 24 + 24 + 24 + 24 + 26 + 26 + 26 + 26 + 26 + 28 + 28 + 28 + 28 + 28 + 30 + 30 + 30 + 30 + 32 + 32 + 32 + 34 + 34 + 34 + 36 + 36 + 38 + 40 + 42;
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System.out.println(k / 52f);
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File file = new File(FILE_NAME);
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try {
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file.createNewFile();
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} catch (IOException e) {
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e.printStackTrace();
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}
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RNG.setSeed(56);
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RLController<AntAction> rl = new RLController<>(
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new AntWorldContinuous(8, 8),
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Method.Q_LEARNING_OFF_POLICY_CONTROL,
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AntAction.values());
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rl.setDelay(0);
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rl.setNrOfEpisodes(1);
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//0.99 0.9 0.5
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//0.99 0.95 0.9 0.7 0.5 0.3 0.1
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rl.setDiscountFactor(0.1f);
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// 0.1, 0.3, 0.5, 0.7 0.9
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rl.setLearningRate(0.9f);
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rl.setEpsilon(0.2f);
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rl.start();
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List<Float> discValues = new ArrayList<>() {
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};
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discValues.add(0.05f);
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discValues.add(0.1f);
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discValues.add(0.3f);
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discValues.add(0.5f);
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discValues.add(0.7f);
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discValues.add(0.9f);
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discValues.add(0.95f);
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discValues.add(0.99f);
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for(float disc : discValues) {
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RNG.setSeed(13);
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RLController<AntAction> rl = new RLController<>(
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new AntWorldContinuous(8, 8),
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Method.Q_LEARNING_OFF_POLICY_CONTROL,
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AntAction.values());
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rl.setDelay(0);
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rl.setNrOfEpisodes(1);
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//0.99 0.9 0.5
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//0.99 0.95 0.9 0.7 0.5 0.3 0.1
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rl.setDiscountFactor(disc);
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// 0.1, 0.3, 0.5, 0.7 0.9
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rl.setLearningRate(0.9f);
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rl.setEpsilon(0.2f);
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rl.start();
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}
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}
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}
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