Examples of com.barrybecker4.game.twoplayer.common.search.strategy.NegaScoutMemoryStrategy

Package com.barrybecker4.game.twoplayer.common.search.strategy

Examples of com.barrybecker4.game.twoplayer.common.search.strategy.NegaScoutMemoryStrategy

com.barrybecker4.puzzle.tantrix.solver.path.TantrixPath

e.csail.mit.edu/plaat/mtdf.html and http://en.wikipedia.org/wiki/Negascout Transposition table (TT) enhanced Alpha-Beta (from http://www.top-5000.nl/ps/An%20Algorithm%20faster%20than%20negascout%20and%20SSS%20in%20pratice.pdf)

 function AlphaBetaWithMemory(n, a, b) { // Check if position is in table and has been searched to sufficient depth. if (retrieve(n)) { if (n.max <= a or n.max == n.min)  return n.max; if (n.min >= b) return n.min ; } // Reached the maximum search depth if (n = leaf) { n.min = n.max = g = eval(n); } else  { g = -inf; c = firstchild(n); // Search until a cutoff occurs or all children have been considered while g < b and c != null { g = max(g, -AlphaBetaWithMemory(c, -b, -a)); a = max(a, g); c = nextbrother(c); } // Save in transposition table if g <= a then n.max = g; if a < g < b then n.max = n.min = g; if g >= b then n.min = g; } store(n); return g; }

@author Barry Becker

        this.numTiles = numTiles;
    }


    public TantrixBoard initialPosition() {
        //MathUtil.RANDOM.setSeed(1);
        return new TantrixBoard(new HexTiles().createRandomList(numTiles));
    }

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        ParameterArray solution =
            optimizer.doOptimization(strategy, initialGuess, SOLVED_THRESH);


        solution_ =
            new TantrixBoard(((TantrixPath)solution).getTilePlacements(), board.getPrimaryColor());


        TilePlacementList moves;
        if (evaluateFitness(solution) >= SOLVED_THRESH) {
            moves = ((TantrixPath)solution).getTilePlacements();
        } else {

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     * @param params
     */
    public void optimizerChanged(ParameterArray params) {
        // update our current best guess at the solution.
        TantrixPath path = (TantrixPath)params;
        solution_ = new TantrixBoard(path.getTilePlacements(), path.getPrimaryPathColor());
        puzzlePanel_.refresh(solution_, numTries_++);
    }

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        drawGrid(g2, board);


        Location topLeftCorner = board.getBoundingBox().getTopLeftCorner();


        for (Location loc : board.getTantrixLocations()) {
            TilePlacement placement = board.getTilePlacement(loc);
            tileRenderer.render(g2, placement, topLeftCorner, hexRadius);
        }
    }

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            optimizer.doOptimization(strategy, initialGuess, SOLVED_THRESH);


        solution_ =
            new TantrixBoard(((TantrixPath)solution).getTilePlacements(), board.getPrimaryColor());


        TilePlacementList moves;
        if (evaluateFitness(solution) >= SOLVED_THRESH) {
            moves = ((TantrixPath)solution).getTilePlacements();
        } else {
            moves = null;
        }

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        int numTiles = path.size();
        double distance = path.getEndPointDistance();
        boolean isLoop = distance == 0 && path.isLoop();


        ConsistencyChecker checker = new ConsistencyChecker(path.getTilePlacements(), path.getPrimaryPathColor());
        int numFits = checker.numFittingTiles();
        boolean allFit = numFits == numTiles;
        boolean consistentLoop = isLoop && allFit;
        boolean perfectLoop = false;
        double compactness = determineCompactness(path);

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        boolean perfectLoop = false;
        double compactness = determineCompactness(path);


        if (consistentLoop) {
            Tantrix tantrix = new Tantrix(path.getTilePlacements());
            InnerSpaceDetector innerDetector = new InnerSpaceDetector(tantrix);
            perfectLoop = !innerDetector.hasInnerSpaces();
            //System.out.println("perfect loop");
        }


        double fitness =
                LOOP_PROXIMITY_WEIGHT * (numTiles - distance) / (0.1 + numTiles)

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                               boolean useConcurrency) {
        super(board);
        puzzlePanel_ = puzzlePanel;
        strategy = useConcurrency ? OptimizationStrategyType.CONCURRENT_GENETIC_SEARCH :
                                    OptimizationStrategyType.GENETIC_SEARCH;
        evaluator = new PathEvaluator();
    }

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     * @return list of moves to a solution.
     */
    @Override
    public TilePlacementList solve()  {


        ParameterArray initialGuess = new TantrixPath(board);
        assert(initialGuess.size() > 0) : "The random path should have some tiles!";
        long startTime = System.currentTimeMillis();


        Optimizer optimizer = new Optimizer(this);
        optimizer.setListener(this);

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     * We show the current status.
     * @param params
     */
    public void optimizerChanged(ParameterArray params) {
        // update our current best guess at the solution.
        TantrixPath path = (TantrixPath)params;
        solution_ = new TantrixBoard(path.getTilePlacements(), path.getPrimaryPathColor());
        puzzlePanel_.refresh(solution_, numTries_++);
    }

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