Examples of aima.core.search.framework.Problem

aima.core.search.framework.Problem
Artificial Intelligence A Modern Approach (3rd Edition): page 66.

A problem can be defined formally by five components:
- The initial state that the agent starts in.
- A description of the possible actions available to the agent. Given a particular state s, ACTIONS(s) returns the set of actions that can be executed in s.
- A description of what each action does; the formal name for this is the transition model, specified by a function RESULT(s, a) that returns the state that results from doing action a in state s.
- The goal test, which determines whether a given state is a goal state.
- A path cost function that assigns a numeric cost to each path. The problem-solving agent chooses a cost function that reflects its own performance measure. The step cost of taking action a in state s to reach state s' is denoted by c(s,a,s')
@author Ravi Mohan @author Ciaran O'Reilly @author Mike Stampone

  }


  private static void nQueensHillClimbingSearch() {
    System.out.println("\nNQueensDemo HillClimbing  -->");
    try {
      Problem problem = new Problem(new NQueensBoard(8),
          NQueensFunctionFactory.getIActionsFunction(),
          NQueensFunctionFactory.getResultFunction(),
          new NQueensGoalTest());
      HillClimbingSearch search = new HillClimbingSearch(
          new AttackingPairsHeuristic());

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  }


  private static void eightPuzzleDLSDemo() {
    System.out.println("\nEightPuzzleDemo recursive DLS (9) -->");
    try {
      Problem problem = new Problem(boardWithThreeMoveSolution, EightPuzzleFunctionFactory
          .getActionsFunction(), EightPuzzleFunctionFactory
          .getResultFunction(), new EightPuzzleGoalTest());
      Search search = new DepthLimitedSearch(9);
      SearchAgent agent = new SearchAgent(problem, search);
      printActions(agent.getActions());

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  }


  private static void eightPuzzleIDLSDemo() {
    System.out.println("\nEightPuzzleDemo Iterative DLS -->");
    try {
      Problem problem = new Problem(random1, EightPuzzleFunctionFactory
          .getActionsFunction(), EightPuzzleFunctionFactory
          .getResultFunction(), new EightPuzzleGoalTest());
      Search search = new IterativeDeepeningSearch();
      SearchAgent agent = new SearchAgent(problem, search);
      printActions(agent.getActions());

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  private static void eightPuzzleGreedyBestFirstDemo() {
    System.out
        .println("\nEightPuzzleDemo Greedy Best First Search (MisplacedTileHeursitic)-->");
    try {
      Problem problem = new Problem(boardWithThreeMoveSolution,
          EightPuzzleFunctionFactory.getActionsFunction(),
          EightPuzzleFunctionFactory.getResultFunction(),
          new EightPuzzleGoalTest());
      Search search = new GreedyBestFirstSearch(new GraphSearch(),
          new MisplacedTilleHeuristicFunction());

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  private static void eightPuzzleGreedyBestFirstManhattanDemo() {
    System.out
        .println("\nEightPuzzleDemo Greedy Best First Search (ManhattanHeursitic)-->");
    try {
      Problem problem = new Problem(boardWithThreeMoveSolution,
          EightPuzzleFunctionFactory.getActionsFunction(),
          EightPuzzleFunctionFactory.getResultFunction(),
          new EightPuzzleGoalTest());
      Search search = new GreedyBestFirstSearch(new GraphSearch(),
          new ManhattanHeuristicFunction());

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  private static void eightPuzzleAStarDemo() {
    System.out
        .println("\nEightPuzzleDemo AStar Search (MisplacedTileHeursitic)-->");
    try {
      Problem problem = new Problem(random1, EightPuzzleFunctionFactory
          .getActionsFunction(), EightPuzzleFunctionFactory
          .getResultFunction(), new EightPuzzleGoalTest());
      Search search = new AStarSearch(new GraphSearch(),
          new MisplacedTilleHeuristicFunction());
      SearchAgent agent = new SearchAgent(problem, search);

View Full Code Here

  }


  private static void eightPuzzleSimulatedAnnealingDemo() {
    System.out.println("\nEightPuzzleDemo Simulated Annealing  Search -->");
    try {
      Problem problem = new Problem(random1, EightPuzzleFunctionFactory
          .getActionsFunction(), EightPuzzleFunctionFactory
          .getResultFunction(), new EightPuzzleGoalTest());
      SimulatedAnnealingSearch search = new SimulatedAnnealingSearch(
          new ManhattanHeuristicFunction());
      SearchAgent agent = new SearchAgent(problem, search);

View Full Code Here


  private static void eightPuzzleAStarManhattanDemo() {
    System.out
        .println("\nEightPuzzleDemo AStar Search (ManhattanHeursitic)-->");
    try {
      Problem problem = new Problem(random1, EightPuzzleFunctionFactory
          .getActionsFunction(), EightPuzzleFunctionFactory
          .getResultFunction(), new EightPuzzleGoalTest());
      Search search = new AStarSearch(new GraphSearch(),
          new ManhattanHeuristicFunction());
      SearchAgent agent = new SearchAgent(problem, search);

View Full Code Here

        MapFunctionFactory.getResultFunction(), new DefaultGoalTest(
            goalState), new MapStepCostFunction(aMap));


    map = aMap;


    reverseProblem = new Problem(goalState,
        MapFunctionFactory.getActionsFunction(aMap),
        MapFunctionFactory.getResultFunction(), new DefaultGoalTest(
            initialState), new MapStepCostFunction(aMap));
  }

View Full Code Here

 */
public class UniformCostSearchTest {


  @Test
  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);

View Full Code Here

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Related Classes of aima.core.search.framework.Problem

aima.core.environment.map.BidirectionalMapProblem

aima.core.search.uninformed.BidirectionalSearch

aima.gui.applications.search.games.EightPuzzleApp$EightPuzzleController

aima.gui.applications.search.games.NQueensApp$NQueensController

aima.gui.demo.search.EightPuzzleDemo

aima.gui.demo.search.NQueensDemo

aima.test.core.unit.search.framework.SolutionCheckerTest

aima.test.core.unit.search.informed.AStarSearchTest

aima.test.core.unit.search.informed.GreedyBestFirstSearchTest

aima.test.core.unit.search.uninformed.BreadthFirstSearchTest

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