def findPathToClosestCorner(self, gameState):
startPosition = gameState.getPacmanPosition()
food = gameState.getFood()
walls = gameState.getWalls()
problem = CornersProblem(gameState)
#return greedySearch(problem, euclideanHeuristic)
#return search.aStarSearch(problem,cornersHeuristic)
return search.greedySearch(problem,
cornersHeuristic) #Desplazar a search.py
def findPathToClosestDot(self, gameState):
"""
Returns a path (a list of actions) to the closest dot, starting from gameState.
"""
# Here are some useful elements of the startState
startPosition = gameState.getPacmanPosition()
food = gameState.getFood()
walls = gameState.getWalls()
problem = AnyFoodSearchProblem(gameState)
import search
return search.greedySearch(problem)
def registerInitialState(self, state):
"""
This is the first time that the agent sees the layout of the game board. Here, we
choose a path to the goal. In this phase, the agent should compute the path to the
goal and store it in a local variable.
state: a GameState object (pacman.py)
"""
if self.searchFunction == None:
import sys
print "No search function provided for SearchAgent"
sys.exit(1)
# If you wrap your solution in the timing code provided, you'll know how long the pathfinding takes.
starttime = time.time()
self.searchFunction=lambda x: search.greedySearch(x, getFoodHeuristic(state))
problem = self.searchType(state)
self.actions = deque(self.searchFunction(problem))
print 'Path found with total cost of %d in %.1f seconds' % (problem.getCostOfActions(self.actions), time.time() - starttime)
board = []
for _ in range(BOARD_SIZE):
board.append([0] * BOARD_SIZE)
# Set up initial gamestate
game = GameState(snakePos, foodPos, board)
# Repeat search n times
for search_num in range(NUMBER_OF_SEARCHES):
# Get resulting path nodes from performing a search
problem = PositionSearchProblem(game)
#path_nodes = search.depthFirstSearch(problem)
#path_nodes = search.breadthFirstSearch(problem)
path_nodes = search.greedySearch(
problem,
lambda node: manhattanDistance(node.state,
(game.food.x, game.food.y)))
# Print path nodes
'''
for node in path_nodes:
print(node)
'''
# Check if a path was found
if path_nodes is None:
print("Could not find path")
pygame.quit()
exit()
actions = [node.action for node in path_nodes]
def __init__(self, searchFunction=None, searchType=FoodSearchProblem): self.searchFunction = lambda problem: search.greedySearch(problem, foodHeuristic) self.searchType = FoodSearchProblem
def __init__(self):
self.searchFunction = lambda prob: search.greedySearch(prob, greedyfoodHeuristic)
self.searchType = FoodSearchProblem
def greedySearch(problem): return search.greedySearch(problem, greedyHeuristic)
def greedy(problem):
return search.greedySearch(problem, greedyFoodHeuristic)
def __init__(self, searchFunction=None, searchType=FoodSearchProblem): SearchAgent.__init__(self, (lambda x: search.greedySearch(x, getFoodHeuristic(None))), searchType)
