def __init__(self, initial, goal=None):
'''Inicializacion de nuestro problema.'''
Problem.__init__(self, initial, goal)
# Las acciones son movimientos de determinadas piezas:
#
# Movimientos horizontales
# a1xa2
# a2xa3
# b1xb2
# b2xb3
# c1xc2
# c2xc3
#
# Movimientos verticales
# a1xb1
# b1xc1
# a2xb2
# b2xc2
# a3xb3
# b3xc3
self._actions = [
('a1xa2', (0,0), (0,1)), ('a2xa3', (0,1), (0,2)), ('b1xb2', (1,0), (1,1)), ('b2xb3', (1,1), (1,2)), ('c1xc2', (2,0), (2,1)), ('c2xc3', (2,1),(2,2)),
('a1xb1', (0,0), (1,0)), ('b1xc1', (1,0), (2,0)), ('a2xb2', (0,1), (1,1)), ('b2xc2', (1,1), (2,1)), ('a3xb3', (0,2), (1,2)), ('b3xc3', (1,2),(2,2))
]
self.validStates = []
self.cantidadPastelesRicos = 0
def __init__(self, initial, goal=(3, 3, 0, 0, 0)):
""" Define goal state and initialize a problem
(3, 3, 0, 0, 0)
(M, C, M, C, B)
"""
self.goal = goal
Problem.__init__(self, initial, goal)
def __init__(self, initial, goal=None, cities=None):
"""The constructor specifies the initial state, and possibly a goal
state, if there is a unique goal. Your subclass's constructor can add
other arguments."""
self.cities = cities
self.nodes_cnt = 0
self.citiy_num = len(cities)
self.depth = 0
Problem.__init__(self, initial, goal)
def __init__(self, initial, goal=None, random_h=False):
"""The constructor specifies the initial state, and possibly a goal
state, if there is a unique goal. Your subclass's constructor can add
other arguments."""
self.random_h = random_h
self.nodes_cnt = 0
self.depth = 0
Problem.__init__(self, initial, goal)
def __init__(self, initial, goal, grid):
Problem.__init__(self, initial, goal)
"""In the constructor we take in the initial state and goal state.
"""
self.initial = initial
self.goal = goal
self.grid = grid
self.max_speed = (numpy.matrix(self.grid).max())
def __init__(self,
inicial=(0, 0),
meta=(34, 0),
digits=[2, 3],
operands=["*", "+"]):
Problem.__init__(self, inicial, meta)
self.initial = inicial
for operand in operands:
self.acciones.append(operand)
self.digits = digits
def __init__(self, initial, goal=None):
"""The constructor specifies the initial state, and possibly a goal
state, if there is a unique goal. Your subclass's constructor can add
other arguments."""
self.nodes_cnt = 0
self.depth = 0
self.states = [(3, 3, 0), (3, 0, 0), (2, 3, 0), (2, 2, 0), (2, 0, 0),
(1, 3, 0), (1, 1, 0), (1, 0, 0), (0, 3, 0), (0, 0, 0),
(3, 3, 1), (3, 0, 1), (2, 3, 1), (2, 2, 1), (2, 0, 1),
(1, 3, 1), (1, 1, 1), (1, 0, 1), (0, 3, 1), (0, 0, 1)]
Problem.__init__(self, initial, goal)
def __init__(self, initial, gridSize, maxTime, weight):
""" Define goal state and initialize a problem """
self.gridSize = gridSize
self.maxTime = maxTime
self.numEvents = len(
[s for s in initial if isinstance(s, tuple) if 'event' in s])
self.numCars = len(
[s for s in initial if isinstance(s, tuple) if 'car' in s])
self.epsilon = 0.01
self.numSteps = 0
self.weight = weight
Problem.__init__(self, initial)
def main():
rawClauses = read_stdin()
clauseInst = Clause(rawClauses)
resolution = Problem(initialState=[],
possibleActions=clauseInst.clausesList,
goalState=[])
status = Search.bfs(resolution)
print("\n{}".format(status))
def main():
problem = Problem('p2.txt')
csp = CSP(problem.vars, problem.domains, problem.neighbors,
problem.constraints)
result = backtracking_search(csp,
select_unassigned_variable=mrv,
order_domain_values=lcv,
inference=mac)
for result_index in range(problem.board_length):
row = ''
for value_index in range(len(result[result_index])):
row = row + str(result[result_index][value_index])
print(row)
def __init__(self, initial, goal=None):
""" Define goal state and initialize a problem """
self.goal = goal
self.matrix_size = int(math.sqrt(len(initial)))
self.total_iterations = 0
self.cars = Queue(
self.matrix_size
) # o coada in care salvam ordinea in care se muta masinile
self.delta = {
'UP': -self.matrix_size,
'DOWN': self.matrix_size,
'LEFT': -1,
'RIGHT': 1,
'JUMPLEFT': -2,
'JUMPRIGHT': 2,
'JUMPDOWN': 2 * self.matrix_size,
'JUMPUP': -2 * self.matrix_size,
'STAY': 0
}
for i in range(1, self.matrix_size + 1):
self.cars.put(i) # umplem coada cu masini de la 1 la matrix_size+1
Problem.__init__(self, initial, goal)
def __init__(self, initial, goal, map, diagonal_moves=False, shuffle_actions_list=False):
assert(index_by(initial, map) == START)
assert(index_by(goal, map) == GOAL)
self.map = map
self.height = len(map) # number of rows (m)
self.width = len(map[0]) # number of columns (n)
self.initial = initial
self.goal = goal
self.diagonal_moves = diagonal_moves
self.shuffle_actions_list = shuffle_actions_list
if diagonal_moves:
self.directions = [(-1, -1), (-1, 0), (-1, 1),
( 0, -1), ( 0, 1),
( 1, -1), ( 1, 0), ( 1, 1)]
else:
self.directions = [ (-1, 0),
( 0, -1), ( 0, 1),
( 1, 0), ]
Problem.__init__(self, self.initial, self.goal)
def __init__(self, initial, goal):
self.goal = goal
self.initial = initial
self.visited_states = []
Problem.__init__(self, self.initial, self.goal)
def __init__(self, initial, goal, matrix, heuristic=1):
Problem.__init__(self, initial, goal)
self.matrix = matrix
self.heuristic = heuristic
def __init__(self, initial):
size = len(initial)
Problem.__init__(self, initial, goal=bytes((1, ) * size))
self.transform_map = build_transform_map(int(sqrt(size)))
self._actions = tuple(range(size))
def __init__(self, init):
#self.old_tables = {}
#self.best_value = 0
Problem.__init__(self, get_init_state_from_file(init))
def __init__(self, initial=(0, 0), goal=(30, 30), obstacles=(), **kwds):
Problem.__init__(self, initial=initial, goal=goal, **kwds)
self.obstacles = obstacles - {initial, goal}
def __init__(self, initial, goal, image):
self.initial = initial
self.goal = goal
self.image = image
Problem.__init__(self, initial, goal)
def __init__(self, domain_problem):
self.dp = domain_problem
self.goals = {tuple(atom.predicate) for atom in self.dp.goals()}
initial = tuple([tuple(atom.predicate) for atom in self.dp.initialstate()])
Problem.__init__(self, initial)
def value(self):
Problem.value(self)
def __init__(self, init):
#self.old_tables = {}
#self.best_value = 0
Problem.__init__(self, get_init_state_from_file(init))
def __init__(self, initial, m, n, x, goal=None):
Problem.__init__(self, initial, goal)
self.m = m
self.n = n
self.x = x
def __init__(self, initial, goal=None):
"""Inicializacion de nuestro problema."""
Problem.__init__(self, initial, goal)
# cada accion tiene un texto "lindo", y despues una tupla con la
# cantidad de misioneros y canibales que se mueven en la canoa
self._actions = [("1c", (0, 1)), ("1m", (1, 0)), ("2c", (0, 2)), ("2m", (2, 0)), ("1m1c", (1, 1))]
def __init__(self, N):
self.N = N
self.initial = tuple([-1] * N)
Problem.__init__(self, self.initial)
def __init__(self, initial, goal, graph, heuristics):
Problem.__init__(self, initial, goal)
self.graph = graph
self.heuristics = heuristics
def __init__(self, init_state, final_state, board_size):
Problem.__init__(self, init_state, final_state)
self.board_size = board_size
def __init__(self, initial, goal, graph):
Problem.__init__(self, initial, goal)
self.graph = graph
def __init__(self, initial, goal):
Problem.__init__(self, initial, goal)
def __init__(self, initial, goal=(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 0)):
""" Define goal state and initialize a problem """
self.goal = goal
Problem.__init__(self, initial, goal)
def __init__(self, inicial=(2, 3, 0), meta=(2, 3, 13)):
Problem.__init__(self, inicial, meta)
self.acciones = ["+A", "+B", "*A", "*B"]
def __init__(self, initial=[], goal=[], size=5):
Problem.__init__(self, initial, goal)
self.size = size
def __init__(self, initial, goal):
Problem.__init__(self, initial, goal)
def __init__(self, init_state, final_state, max_qty):
Problem.__init__(self, init_state, final_state)
self.max_qty = max_qty
def __init__(self, initial, goal):
self.goal = goal
self.initial = initial
Problem.__init__(self, self.initial, self.goal)
def __init__(self, initial, goal):
Problem.__init__(self, initial, goal)
self.all_actions = [
MissionariesLeftToRight(1),
MissionariesLeftToRight(2)
]
