def __init__(self):
self.game_tree = LinkedTree() # game_tree is instance of a LinkedTree
start_state = GameState() # Create an empty GameState for the root.
self.game_tree.add_root(start_state) # Add the root.
self.position = self.game_tree.get_root(
) # Keep track of our game's position in the tree
self.populate_tree() # Populate the whole tree.
self.game_over = False
def __init__(self):
self.game_tree = LinkedTree() # game_tree is instance of a LinkedTree
start_state = GameState() # Create an empty GameState for the root.
self.game_tree.add_root(start_state) # Add the root.
self.position = self.game_tree.get_root() # Keep track of our game's position in the tree
self.populate_tree() # Populate the whole tree.
self.game_over = False
class TicTacToe(object):
def __init__(self):
self.game_tree = LinkedTree() # game_tree is instance of a LinkedTree
start_state = GameState() # Create an empty GameState for the root.
self.game_tree.add_root(start_state) # Add the root.
self.position = self.game_tree.get_root(
) # Keep track of our game's position in the tree
self.populate_tree() # Populate the whole tree.
self.game_over = False
def populate_tree(self, node=None):
'''Beginning with root, populate the whole tree with GameStates'''
if node is None:
node = self.game_tree.get_root(
) # If node is None, make the root our starting point.
for game_state in self.game_tree.element(node).direct_derivatives(
): # get all possible game_states from this state.
child = self.game_tree.add_child(
node, game_state) # Add the game state as a child to the node
self.populate_tree(child) # recur on the child returned.
def computer_play(self):
'''Select the best child to move to from the current position.'''
eligible = []
for child in self.game_tree.children(self.position):
#***print('Possible Child:\n' + str(self.game_tree.element(child)))
# Assess if it's a win for the computer, a loss, or just another move.
score = self.game_tree.element(child).score()
if score == 0:
eligible.append(child) # add to our list of eligible options.
self.position = child
elif score == 1:
self.position = child # Take the win.
self.game_over = True
break
if self.game_over == False and len(
eligible) > 0: # If we had any eligible options.
index = random.randint(0, len(eligible) - 1)
self.position = eligible[index] # randomly select an option.
else:
self.game_over = True # The human won.
def user_play(self, row, col):
'''The user selects a spot'''
new_gs = self.game_tree.element(
self.position
) # Create a new GameState to accomodate the user's move.
new_gs.board[row][col] = 'X'
# Compare the new GameState with the possible GameStates. (children of the current position)
found = False
for child in self.game_tree.children(self.position):
if self.game_tree.element(child) == new_gs:
self.position = child
found = True
break
if not found:
raise LookupError('Not a valid play.')
class TicTacToe(object):
def __init__(self):
self.game_tree = LinkedTree() # game_tree is instance of a LinkedTree
start_state = GameState() # Create an empty GameState for the root.
self.game_tree.add_root(start_state) # Add the root.
self.position = self.game_tree.get_root() # Keep track of our game's position in the tree
self.populate_tree() # Populate the whole tree.
self.game_over = False
def populate_tree(self, node=None):
'''Beginning with root, populate the whole tree with GameStates'''
if node is None:
node = self.game_tree.get_root() # If node is None, make the root our starting point.
for game_state in self.game_tree.element(node).direct_derivatives(): # get all possible game_states from this state.
child = self.game_tree.add_child(node, game_state) # Add the game state as a child to the node
self.populate_tree(child) # recur on the child returned.
def computer_play(self):
'''Select the best child to move to from the current position.'''
eligible = []
for child in self.game_tree.children(self.position):
#***print('Possible Child:\n' + str(self.game_tree.element(child)))
# Assess if it's a win for the computer, a loss, or just another move.
score = self.game_tree.element(child).score()
if score == 0:
eligible.append(child) # add to our list of eligible options.
self.position = child
elif score == 1:
self.position = child # Take the win.
self.game_over = True
break
if self.game_over == False and len(eligible) > 0: # If we had any eligible options.
index = random.randint(0, len(eligible) - 1)
self.position = eligible[index] # randomly select an option.
else:
self.game_over = True # The human won.
def user_play(self, row, col):
'''The user selects a spot'''
new_gs = self.game_tree.element(self.position) # Create a new GameState to accomodate the user's move.
new_gs.board[row][col] = 'X'
# Compare the new GameState with the possible GameStates. (children of the current position)
found = False
for child in self.game_tree.children(self.position):
if self.game_tree.element(child) == new_gs:
self.position = child
found = True
break
if not found:
raise LookupError('Not a valid play.')
