def find_goal(self, state):
"""
arg:
- State: representation of the game at the time t.
Define a way to solve the problem (eat all the food).
return:
- A stack containing the movements.
"""
initState = self.useful_state(state)
fringe = PriorityQueue()
ways = {}
priority = 0
while not state.isWin():
successors = state.generatePacmanSuccessors()
for succ in successors:
"""
Get successors after legal actions of current state.
Push new state, move and current state on the fringe
plus the cost of the edge to this successor.
"""
succState = succ[0]
succMove = succ[1]
x, y = succState.getPacmanPosition()
cost = self.cost_way(state.hasFood(x, y), priority)
fringe.push([succState, succMove, state], cost)
while True:
"""
Pop a new element from the fringe
as long as it has been visited.
"""
priority, popped = fringe.pop()
represCurrState = self.useful_state(popped[0])
represPrevState = self.useful_state(popped[2])
if represCurrState not in ways:
break
ways[represCurrState] = [represPrevState, popped[1]]
state = popped[0]
moves = Stack()
key = self.useful_state(popped[0])
while not key == initState:
"""
Traceback the way to the initial state and store it.
"""
moves.push((ways.get(key))[1])
key = (ways.get(key))[0]
return moves
def __init__(self, args):
"""
Arguments:
----------
- `args`: Namespace of arguments from command-line prompt.
"""
self.args = args
self.way = Stack()
def get_action(self, state):
"""
Given a pacman game state, returns a legal move.
Arguments:
----------
- `state`: the current game state. See FAQ and class
`pacman.GameState`.
Return:
-------
- A legal move as defined in `game.Directions`.
"""
# If no solution has already been calculated.
if self.iterator == -1:
# Initialization of the fringe and the visited nodes.
fringe = Stack()
visited = set()
# Pushing the initial state in the fringe.
fringe.push((state, []))
while not fringe.isEmpty():
# Pop of the next pacman state.
current, self.solution = fringe.pop()
position = current.getPacmanPosition()
food = current.getFood()
# If the state was already visited, we go directly to the next.
if (position, food) in visited:
continue
# Else, we add it to the visited nodes.
visited.add((position, food))
# If all the dots are eaten, we stop: Pacman wins!
if current.isWin():
break
# Otherwise, we add the unvisited states to the fringe.
for (child, action) in current.generatePacmanSuccessors():
position = child.getPacmanPosition()
food = child.getFood()
if (position, food) not in visited:
fringe.push((child, self.solution + [action]))
# If a solution has been found, it is returned.
self.iterator += 1
return self.solution[self.iterator]
def compute_tree(self, state):
"""
Given a pacman state, computes a path from that state to a state
where pacman has eaten all the food dots.
Arguments:
----------
- `state`: the current game state.
Return:
-------
- A list of legal moves as defined in `game.Directions`
"""
fringe = Stack() # a stack
visited = set() # an empty set to maintain visited nodes
# a dictionary to maintain path information :
# key -> (parent state, action to reach child)
meta = dict()
meta[state] = (None, None)
# Append root
fringe.push(state)
# While not empty
while not fringe.isEmpty():
# Pick one available state
current_node = fringe.pop()
# If all food dots found, stop and compute a path
if current_node.isWin():
return self.construct_path(current_node, meta)
# Get info on current node
curr_pos = current_node.getPacmanPosition()
curr_food = current_node.getFood()
if (hash(curr_pos), hash(curr_food)) not in visited:
# Add the current node to the visited set
visited.add((hash(curr_pos), hash(curr_food)))
# For each successor of the current node
successors = current_node.generatePacmanSuccessors()
for next_node, next_action in successors:
# Get info on successor
next_pos = next_node.getPacmanPosition()
next_food = next_node.getFood()
# Check if it was already visited
if (hash(next_pos), hash(next_food)) not in visited:
# If not, update meta and put the successor on the fringe
meta[next_node] = (current_node, next_action)
fringe.push(next_node)
class PacmanAgent(Agent):
def __init__(self, args):
"""
Arguments:
----------
- `args`: Namespace of arguments from command-line prompt.
"""
self.args = args
self.way = Stack()
def useful_state(self, state):
"""
arg:
- State: representation of the game at the time t.
This method extracts important informations from the state.
return:
- The grid of food dots and the pacman position.
"""
return state.getFood(), state.getPacmanPosition()
def find_goal(self, state):
"""
arg:
- State: representation of the game at the time t.
Define a way to solve the problem (eat all the food).
return:
- A stack containing the movements.
"""
initState = self.useful_state(state)
fringe = Queue()
ways = {}
while not state.isWin():
successors = state.generatePacmanSuccessors()
for succ in successors:
"""
Get successors after legal actions of current state.
Push new state, move and current state on the fringe.
"""
succState = succ[0]
succMove = succ[1]
fringe.push([succState, succMove, state])
while True:
"""
Pop a new element from the fringe
as long as it has been visited.
"""
popped = fringe.pop()
represCurrState = self.useful_state(popped[0])
represPrevState = self.useful_state(popped[2])
if represCurrState not in ways:
break
ways[represCurrState] = [represPrevState, popped[1]]
state = popped[0]
moves = Stack()
key = self.useful_state(popped[0])
while not key == initState:
"""
Traceback the way to the initial state and store it.
"""
moves.push((ways.get(key))[1])
key = (ways.get(key))[0]
return moves
def get_action(self, state):
"""
Given a pacman game state, returns a legal move.
Arguments:
----------
- `state`: the current game state. See FAQ and class
`pacman.GameState`.
Return:
-------
- A legal move as defined in `game.Directions`.
"""
if self.way.isEmpty():
self.way = self.find_goal(state)
return self.way.pop()
def find_goal(self, state):
"""
arg:
- State: representation of the game at the time t.
Define a way to solve the problem (eat all the food).
return:
- A stack containing the movements.
"""
initState = self.useful_state(state)
fringe = PriorityQueue()
foodSet = set()
ways = {}
priority = 0
"""
Loop trough the food grid and initialize the set of food positions.
"""
foodPos = state.getFood()
for i in np.arange(foodPos.width):
for j in np.arange(foodPos.height):
if foodPos[i][j]:
foodSet.add((i, j))
popped = [None, None, None, foodSet]
while not state.isWin():
successors = state.generatePacmanSuccessors()
for succ in successors:
"""
Get successors after legal actions of current state.
Push new state, move, current state on the fringe
and the current set of food positions
plus the cost of the edge to this successor.
"""
succState = succ[0]
succMove = succ[1]
x, y = succState.getPacmanPosition()
pacmanPos = [x, y]
food = state.hasFood(x, y)
foodSetCopy = popped[3].copy()
if food:
foodSetCopy.remove((x, y))
cost = self.cost_way(food, pacmanPos, foodSetCopy, priority)
fringe.push([succState, succMove, state, foodSetCopy], cost)
while True:
"""
Pop a new element from the fringe
as long as it has been visited.
"""
priority, popped = fringe.pop()
represCurrState = self.useful_state(popped[0])
represPrevState = self.useful_state(popped[2])
if represCurrState not in ways:
break
ways[represCurrState] = [represPrevState, popped[1]]
state = popped[0]
moves = Stack()
key = self.useful_state(popped[0])
while not key == initState:
"""
Traceback the way to the initial state and store it.
"""
moves.push((ways.get(key))[1])
key = (ways.get(key))[0]
return moves
class PacmanAgent(Agent):
def __init__(self, args):
"""
Arguments:
----------
- `args`: Namespace of arguments from command-line prompt.
"""
self.args = args
self.way = Stack()
def cost_way(self, food, pacmanPos, foodSet, prevCost):
"""
arg:
-Food: boolean argument, true if there is food.
-PacmanPos: position of pacman
-FoodSet: set containing the position of the food dots
-PrevCost: contain the previous cost.
Calculate the cost as the sum of the largest Manhattan distance
and the cost of the edge.
return:
-The global cost of the edge.
"""
cost = prevCost
maxMD = 0
for elmt in foodSet:
MD = manhattanDistance(elmt, pacmanPos)
if MD > maxMD:
maxMD = MD
if food:
cost = cost + maxMD + 1
else:
cost = cost + maxMD + 10
return cost
def useful_state(self, state):
"""
arg:
- State: representation of the game at the time t.
This method extracts important informations from the state.
return:
- The grid of food dots and the pacman position.
"""
return state.getFood(), state.getPacmanPosition()
def find_goal(self, state):
"""
arg:
- State: representation of the game at the time t.
Define a way to solve the problem (eat all the food).
return:
- A stack containing the movements.
"""
initState = self.useful_state(state)
fringe = PriorityQueue()
foodSet = set()
ways = {}
priority = 0
"""
Loop trough the food grid and initialize the set of food positions.
"""
foodPos = state.getFood()
for i in np.arange(foodPos.width):
for j in np.arange(foodPos.height):
if foodPos[i][j]:
foodSet.add((i, j))
popped = [None, None, None, foodSet]
while not state.isWin():
successors = state.generatePacmanSuccessors()
for succ in successors:
"""
Get successors after legal actions of current state.
Push new state, move, current state on the fringe
and the current set of food positions
plus the cost of the edge to this successor.
"""
succState = succ[0]
succMove = succ[1]
x, y = succState.getPacmanPosition()
pacmanPos = [x, y]
food = state.hasFood(x, y)
foodSetCopy = popped[3].copy()
if food:
foodSetCopy.remove((x, y))
cost = self.cost_way(food, pacmanPos, foodSetCopy, priority)
fringe.push([succState, succMove, state, foodSetCopy], cost)
while True:
"""
Pop a new element from the fringe
as long as it has been visited.
"""
priority, popped = fringe.pop()
represCurrState = self.useful_state(popped[0])
represPrevState = self.useful_state(popped[2])
if represCurrState not in ways:
break
ways[represCurrState] = [represPrevState, popped[1]]
state = popped[0]
moves = Stack()
key = self.useful_state(popped[0])
while not key == initState:
"""
Traceback the way to the initial state and store it.
"""
moves.push((ways.get(key))[1])
key = (ways.get(key))[0]
return moves
def get_action(self, state):
"""
Given a pacman game state, returns a legal move.
Arguments:
----------
- `state`: the current game state. See FAQ and class
`pacman.GameState`.
Return:
-------
- A legal move as defined in `game.Directions`.
"""
if self.way.isEmpty():
self.way = self.find_goal(state)
return self.way.pop()