def depthFirstSearch(problem): """ Search the deepest nodes in the search tree first. Your search algorithm needs to return a list of actions that reaches the goal. Make sure to implement a graph search algorithm. To get started, you might want to try some of these simple commands to understand the search problem that is being passed in: print "Start:", problem.getStartState() print "Is the start a goal?", problem.isGoalState(problem.getStartState()) print "Start's successors:", problem.getSuccessors(problem.getStartState()) """ "*** YOUR CODE HERE ***" from util import Stack nodes = Stack() closed = dict() moves = list() for var in problem.getSuccessors(problem.getStartState()): state = FringeState(var[0]) state.moves.append(Directions.convToDirection(var[1])) nodes.push(state) closed[problem.getStartState()] = True while(False == nodes.isEmpty()): current_node = nodes.pop() #print "Current node:", current_node if(closed.has_key(current_node.pos)): continue if(problem.isGoalState(current_node.pos)): print "Goal reached!" moves = current_node.moves break for var in problem.getSuccessors(current_node.pos): state = FringeState(var[0]) state.moves= copy.deepcopy(current_node.moves) state.moves.append(Directions.convToDirection(var[1])) nodes.push(state) closed[current_node.pos] = True return moves
def uniformCostSearch(problem): """Search the node of least total cost first.""" from util import PriorityQueue nodes = PriorityQueue() closed = dict() moves = list() for var in problem.getSuccessors(problem.getStartState()): state = FringeState(var[0]) state.moves.append(Directions.convToDirection(var[1])) state.cost = var[2] nodes.push(state, state.cost) closed[problem.getStartState()] = True while(False == nodes.isEmpty()): current_node = nodes.pop() #print "Current node:", current_node if(closed.has_key(current_node.pos)): continue if(problem.isGoalState(current_node.pos)): print "Goal reached!" moves = current_node.moves break for var in problem.getSuccessors(current_node.pos): state = FringeState(var[0]) state.moves= copy.deepcopy(current_node.moves) state.moves.append(Directions.convToDirection(var[1])) state.cost = var[2] + current_node.cost nodes.push(state, state.cost) closed[current_node.pos] = True return moves
def aStarSearch(problem, heuristic=nullHeuristic): """Search the node that has the lowest combined cost and heuristic first.""" from util import PriorityQueue nodes = PriorityQueue() closed = dict() moves = list() for var in problem.getSuccessors(problem.getStartState()): state = FringeState(var[0]) state.moves.append(Directions.convToDirection(var[1])) state.cost = var[2] nodes.push(state, state.cost + heuristic(state.pos,problem)) closed[problem.getStartState()] = True while(False == nodes.isEmpty()): current_node = nodes.pop() #print "Current node:", current_node if(closed.has_key(current_node.pos)): continue if(problem.isGoalState(current_node.pos)): print "Goal reached!" moves = current_node.moves break for var in problem.getSuccessors(current_node.pos): state = FringeState(var[0]) state.moves= copy.deepcopy(current_node.moves) state.moves.append(Directions.convToDirection(var[1])) state.cost = var[2] + current_node.cost nodes.push(state, state.cost + heuristic(state.pos,problem)) closed[current_node.pos] = True return moves
def breadthFirstSearch(problem): """Search the shallowest nodes in the search tree first.""" "*** YOUR CODE HERE ***" from util import Queue nodes = Queue() closed = dict() moves = list() for var in problem.getSuccessors(problem.getStartState()): state = FringeState(var[0]) state.moves.append(Directions.convToDirection(var[1])) nodes.push(state) closed[problem.getStartState()] = True while(False == nodes.isEmpty()): current_node = nodes.pop() #print "Current node:", current_node if(closed.has_key(current_node.pos)): continue if(problem.isGoalState(current_node.pos)): print "Goal reached!" moves = current_node.moves break for var in problem.getSuccessors(current_node.pos): state = FringeState(var[0]) state.moves= copy.deepcopy(current_node.moves) state.moves.append(Directions.convToDirection(var[1])) nodes.push(state) closed[current_node.pos] = True return moves