Examples of aima.core.search.uninformed.UniformCostSearch

aima.core.search.uninformed.UniformCostSearch
ses the lowest-cost node in frontier if problem.GOAL-TEST(node.STATE) then return SOLUTION(node) add node.STATE to explored for each action in problem.ACTIONS(node.STATE) do child <- CHILD-NODE(problem, node, action) if child.STATE is not in explored or frontier then frontier <- INSERT(child, frontier) else if child.STATE is in frontier with higher PATH-COST then replace that frontier node with child Figure 3.14 Uniform-cost search on a graph. The algorithm is identical to the general graph search algorithm in Figure 3.7, except for the use of a priority queue and the addition of an extra check in case a shorter path to a frontier state is discovered. The data structure for frontier needs to support efficient membership testing, so it should combine the capabilities of a priority queue and a hash table. @author Ciaran O'Reilly @author Ruediger Lunde

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

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  public void testUniformCostSuccesfulSearch() throws Exception {
    Problem problem = new Problem(new NQueensBoard(8),
        NQueensFunctionFactory.getIActionsFunction(),
        NQueensFunctionFactory.getResultFunction(),
        new NQueensGoalTest());
    Search search = new UniformCostSearch();
    SearchAgent agent = new SearchAgent(problem, search);


    List<Action> actions = agent.getActions();


    Assert.assertEquals(8, actions.size());

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  public void testUniformCostUnSuccesfulSearch() throws Exception {
    Problem problem = new Problem(new NQueensBoard(3),
        NQueensFunctionFactory.getIActionsFunction(),
        NQueensFunctionFactory.getResultFunction(),
        new NQueensGoalTest());
    Search search = new UniformCostSearch();
    SearchAgent agent = new SearchAgent(problem, search);


    List<Action> actions = agent.getActions();


    Assert.assertEquals(0, actions.size());

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


    Search search = new UniformCostSearch();
    SearchAgent agent = new SearchAgent(problem, search);


    List<Action> actions = agent.getActions();


    Assert.assertEquals(
        "[Action[name==moveTo, location==RimnicuVilcea], Action[name==moveTo, location==Pitesti], Action[name==moveTo, location==Bucharest]]",
        actions.toString());
    Assert.assertEquals("278.0",
        search.getMetrics().get(QueueSearch.METRIC_PATH_COST));
  }

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    Problem problem = new Problem("start",
        MapFunctionFactory.getActionsFunction(map),
        MapFunctionFactory.getResultFunction(), new DefaultGoalTest(
            "goal"), new MapStepCostFunction(map));


    Search search = new UniformCostSearch();
    SearchAgent agent = new SearchAgent(problem, search);


    List<Action> actions = agent.getActions();


    Assert.assertEquals(
        "[Action[name==moveTo, location==b], Action[name==moveTo, location==d], Action[name==moveTo, location==goal]]",
        actions.toString());
    Assert.assertEquals("5.5",
        search.getMetrics().get(QueueSearch.METRIC_PATH_COST));
  }

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    aMap.addBidirectionalLink("B", "C", 4.0);
    aMap.addBidirectionalLink("C", "D", 7.0);
    aMap.addUnidirectionalLink("B", "E", 14.0);


    me = new MapEnvironment(aMap);
    ma = new MapAgent(me.getMap(), me, new UniformCostSearch(),
        new String[] { "A" });
  }

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    Assert.assertEquals(p.getAttribute(DynAttributeNames.PERCEPT_IN), "D");
  }


  @Test
  public void testTwoAgentsSupported() {
    MapAgent ma1 = new MapAgent(me.getMap(), me, new UniformCostSearch(),
        new String[] { "A" });
    MapAgent ma2 = new MapAgent(me.getMap(), me, new UniformCostSearch(),
        new String[] { "A" });


    me.addAgent(ma1, "A");
    me.addAgent(ma2, "A");
    me.executeAction(ma1, new MoveToAction("B"));

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  }


  @Test
  public void testAlreadyAtGoal() {
    MapEnvironment me = new MapEnvironment(aMap);
    MapAgent ma = new MapAgent(me.getMap(), me, new UniformCostSearch(),
        new String[] { "A" });
    me.addAgent(ma, "A");
    me.addEnvironmentView(new TestEnvironmentView());
    me.stepUntilDone();

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  }


  @Test
  public void testNormalSearch() {
    MapEnvironment me = new MapEnvironment(aMap);
    MapAgent ma = new MapAgent(me.getMap(), me, new UniformCostSearch(),
        new String[] { "D" });
    me.addAgent(ma, "A");
    me.addEnvironmentView(new TestEnvironmentView());
    me.stepUntilDone();

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  }


  @Test
  public void testNoPath() {
    MapEnvironment me = new MapEnvironment(aMap);
    MapAgent ma = new MapAgent(me.getMap(), me, new UniformCostSearch(),
        new String[] { "A" });
    me.addAgent(ma, "E");
    me.addEnvironmentView(new TestEnvironmentView());
    me.stepUntilDone();

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Related Classes of aima.core.search.uninformed.UniformCostSearch

aima.core.search.framework.GraphSearch

aima.gui.applications.search.map.SearchFactory

aima.test.core.unit.environment.map.MapAgentTest

aima.test.core.unit.environment.map.MapEnvironmentTest

aima.test.core.unit.search.uninformed.UniformCostSearchTest

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