Super IA #5
@@ -28,9 +28,8 @@ public class AlphaBetaAI extends AI {
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public AlphaBetaAI(CommandExecutor commandExecutor, Color color, int searchDepth) {
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super(commandExecutor, color);
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this.searchDepth = searchDepth;
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int threadCount = Runtime.getRuntime().availableProcessors() - 1;
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int threadCount = Runtime.getRuntime().availableProcessors() / 2;
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this.threadPool = Executors.newFixedThreadPool(threadCount, new AlphaBetaThreadCreator(commandExecutor, color, threadCount));
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System.out.println();
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}
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private Move getBestMove() {
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@@ -48,7 +47,9 @@ public class AlphaBetaAI extends AI {
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}
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for (int i = 0; i < moves.size(); i++) {
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System.out.printf("Progress : %.2f %% ", (float) (i) / moves.size() * 100.0f);
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Move move = moves.get(i);
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System.out.print("\r");
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float value = MIN_FLOAT;
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try {
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value = moveEvaluations.get(i).get();
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@@ -61,7 +62,7 @@ public class AlphaBetaAI extends AI {
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}
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}
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System.out.println("Best move : " + bestMoveValue);
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System.out.println("Best move : " + bestMoveValue + " ");
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return bestMove;
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}
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@@ -1,6 +1,10 @@
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package chess.ai.minimax;
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import java.util.ArrayList;
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import java.util.Collections;
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import java.util.List;
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import java.util.Map;
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import java.util.Map.Entry;
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import chess.ai.PieceCost;
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import chess.ai.PiecePosCost;
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@@ -76,7 +80,23 @@ public class AlphaBetaThread extends Thread {
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if (moves.isEmpty())
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return getEndGameEvaluation();
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List<Entry<Move, Float>> movesCost = new ArrayList<>(moves.size());
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for (Move move : moves) {
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this.simulation.tryMove(move);
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movesCost.add(Map.entry(move, getBoardEvaluation()));
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this.simulation.undoMove();
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}
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Collections.sort(movesCost, (first, second) -> {
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return Float.compare(first.getValue(), second.getValue());
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});
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if (depth == 1)
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return -movesCost.getFirst().getValue();
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for (var moveEntry : movesCost) {
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Move move = moveEntry.getKey();
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this.simulation.tryMove(move);
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value = Float.max(value, -negaMax(depth - 1, -beta, -alpha));
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this.simulation.undoMove();
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