Examples of GreedyBestFirstSearch

aima.core.search.informed.GreedyBestFirstSearch
Artificial Intelligence A Modern Approach (3rd Edition): page 92.

Greedy best-first search tries to expand the node that is closest to the goal, on the grounds that this is likely to lead to a solution quickly. Thus, it evaluates nodes by using just the heuristic function; that is, f(n) = h(n) @author Ravi Mohan @author Mike Stampone

Examples of aima.core.search.informed.GreedyBestFirstSearch

      break;
    case UC_SEARCH:
      result = new UniformCostSearch(qs);
      break;
    case GBF_SEARCH:
      result = new GreedyBestFirstSearch(qs, hf);
      break;
    case ASTAR_SEARCH:
      result = new AStarSearch(qs, hf);
      break;
    case RBF_SEARCH:

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Examples of aima.core.search.informed.GreedyBestFirstSearch

    try {
      Problem problem = new Problem(boardWithThreeMoveSolution,
          EightPuzzleFunctionFactory.getActionsFunction(),
          EightPuzzleFunctionFactory.getResultFunction(),
          new EightPuzzleGoalTest());
      Search search = new GreedyBestFirstSearch(new GraphSearch(),
          new MisplacedTilleHeuristicFunction());
      SearchAgent agent = new SearchAgent(problem, search);
      printActions(agent.getActions());
      printInstrumentation(agent.getInstrumentation());
    } catch (Exception e) {

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Examples of aima.core.search.informed.GreedyBestFirstSearch

    try {
      Problem problem = new Problem(boardWithThreeMoveSolution,
          EightPuzzleFunctionFactory.getActionsFunction(),
          EightPuzzleFunctionFactory.getResultFunction(),
          new EightPuzzleGoalTest());
      Search search = new GreedyBestFirstSearch(new GraphSearch(),
          new ManhattanHeuristicFunction());
      SearchAgent agent = new SearchAgent(problem, search);
      printActions(agent.getActions());
      printInstrumentation(agent.getInstrumentation());
    } catch (Exception e) {

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Examples of aima.core.search.informed.GreedyBestFirstSearch


      Problem problem = new Problem(board,
          EightPuzzleFunctionFactory.getActionsFunction(),
          EightPuzzleFunctionFactory.getResultFunction(),
          new EightPuzzleGoalTest());
      Search search = new GreedyBestFirstSearch(new GraphSearch(),
          new ManhattanHeuristicFunction());
      SearchAgent agent = new SearchAgent(problem, search);
      Assert.assertEquals(49, agent.getActions().size());
      Assert.assertEquals("197",
          agent.getInstrumentation().getProperty("nodesExpanded"));

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Examples of aima.core.search.informed.GreedyBestFirstSearch

        MapFunctionFactory.getActionsFunction(romaniaMap),
        MapFunctionFactory.getResultFunction(), new DefaultGoalTest(
            SimplifiedRoadMapOfPartOfRomania.BUCHAREST),
        new MapStepCostFunction(romaniaMap));


    Search search = new GreedyBestFirstSearch(new TreeSearch(),
        new StraightLineDistanceHeuristicFunction(
            SimplifiedRoadMapOfPartOfRomania.BUCHAREST, romaniaMap));
    SearchAgent agent = new SearchAgent(problem, search);
    Assert.assertEquals(
        "[Action[name==moveTo, location==Sibiu], Action[name==moveTo, location==Fagaras], Action[name==moveTo, location==Bucharest]]",

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Examples of aima.core.search.informed.GreedyBestFirstSearch

        MapFunctionFactory.getActionsFunction(romaniaMap),
        MapFunctionFactory.getResultFunction(), new DefaultGoalTest(
            SimplifiedRoadMapOfPartOfRomania.BUCHAREST),
        new MapStepCostFunction(romaniaMap));


    Search search = new GreedyBestFirstSearch(new GraphSearch(),
        new StraightLineDistanceHeuristicFunction(
            SimplifiedRoadMapOfPartOfRomania.BUCHAREST, romaniaMap));
    SearchAgent agent = new SearchAgent(problem, search);
    Assert.assertEquals(
        "[Action[name==moveTo, location==Sibiu], Action[name==moveTo, location==Fagaras], Action[name==moveTo, location==Bucharest]]",

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