def move_to_top(current_node, visited_map, queue):
"""function moves the empty state up one position"""
#The function checks to see if the move is valid (if it is on the board),
#if the move left is valide, it will create a temporary new_state and it will
#call the function to swap the empty position with the left position. The new_state is
#returned and if that state has not been previously visited, the counter is incremented
#for nodes created and the node is put into the queue. This process is the same for each
#possible position: right, down, and left. The only change is math that is done to look
#at each position.
if (current_node.empty_spot - 3) < 0:
return
new_empty_spot = current_node.empty_spot - 3
new_state = current_node.start_state[:]
new_state = swap_empty_position(new_state, current_node.empty_spot,
new_empty_spot)
if not check_visited(visited_map, new_state):
set_glob_counter()
add_to_visited(visited_map, new_state, COUNTER)
new_node = Node(new_state)
new_node.empty_spot = new_node.find_empty_position()
new_node.depth = new_node.set_depth(current_node)
new_node.set_path = new_node.set_path(current_node, new_empty_spot)
queue.append(new_node)
def move_to_left(current_node, visited_map, queue):
"""function moves the empty state left one position if possible."""
if (current_node.empty_spot % 3) == 0:
return
# from this point, the same steps are repeated as the move_to_up function, but now swapping left
new_empty_spot = current_node.empty_spot - 1
new_state = current_node.start_state[:]
new_state = swap_empty_position(new_state, current_node.empty_spot, new_empty_spot)
if not check_visited(visited_map, new_state):
set_glob_counter()
add_to_visited(visited_map, new_state, COUNTER)
new_node = Node(new_state)
new_node.empty_spot = new_node.find_empty_position()
new_node.set_path = new_node.set_path(current_node, new_empty_spot)
new_node.depth = new_node.set_depth(current_node)
new_node.heuristic = new_node.calculate_misplaced_tiles()
Q.heappush(queue, (new_node.heuristic, COUNTER, new_node))
def move_to_bottom(current_node, visited_map, queue):
"""function moves the empty state down one position"""
if (current_node.empty_spot + 3) > 8:
return
new_empty_spot = current_node.empty_spot + 3
new_state = current_node.start_state[:]
new_state = swap_empty_position(new_state, current_node.empty_spot,
new_empty_spot)
# from this point, the same steps are repeated as the move_to_up function, but now swapping down
if not check_visited(visited_map, new_state):
set_glob_counter()
add_to_visited(visited_map, new_state, COUNTER)
new_node = Node(new_state)
new_node.empty_spot = new_node.find_empty_position()
new_node.set_path = new_node.set_path(current_node, new_empty_spot)
new_node.depth = new_node.set_depth(current_node)
new_node.heuristic = new_node.calculate_manhattan_distance()
Q.heappush(queue, (new_node.heuristic, COUNTER, new_node))
def move_to_top(current_node, visited_map, queue):
"""function moves the empty state up one position"""
if (current_node.empty_spot - 3) < 0:
return
new_empty_spot = current_node.empty_spot - 3
#copies the current state to a temporary variable called new_state
new_state = current_node.start_state[:]
#makes the swap for the empty position and tile above the empty spot
new_state = swap_empty_position(new_state, current_node.empty_spot, new_empty_spot)
#if the new_state is not in the visited map then proceed with making a new node and adding it to the queue
if not check_visited(visited_map, new_state):
set_glob_counter()
add_to_visited(visited_map, new_state, COUNTER)
new_node = Node(new_state)
new_node.empty_spot = new_node.find_empty_position()
new_node.set_path = new_node.set_path(current_node, new_empty_spot)
new_node.depth = new_node.set_depth(current_node)
new_node.heuristic = new_node.calculate_misplaced_tiles()
Q.heappush(queue, (new_node.heuristic, COUNTER, new_node))
def move_to_left(current_node, visited_map, queue):
"""function moves the empty state left one position if possible."""
if (current_node.empty_spot % 3) == 0:
return
new_empty_spot = current_node.empty_spot - 1
new_state = current_node.start_state[:]
new_state = swap_empty_position(new_state, current_node.empty_spot,
new_empty_spot)
if not check_visited(visited_map, new_state):
set_glob_counter()
add_to_visited(visited_map, new_state, COUNTER)
new_node = Node(new_state)
new_node.empty_spot = new_node.find_empty_position()
new_node.depth = new_node.set_depth(current_node)
new_node.set_path = new_node.set_path(current_node, new_empty_spot)
queue.append(new_node)
def move_to_bottom(current_node, visited_map, queue):
"""function moves the empty state down one position"""
if (current_node.empty_spot + 3) > 8:
return
new_empty_spot = current_node.empty_spot + 3
new_state = current_node.start_state[:]
new_state = swap_empty_position(new_state, current_node.empty_spot,
new_empty_spot)
if not check_visited(visited_map, new_state):
set_glob_counter()
add_to_visited(visited_map, new_state, COUNTER)
new_node = Node(new_state)
new_node.empty_spot = new_node.find_empty_position()
new_node.depth = new_node.set_depth(current_node)
new_node.set_path = new_node.set_path(current_node, new_empty_spot)
queue.append(new_node)
def move_to_right(current_node, visited_map, stack):
"""function moves the empty state right one position"""
if ((current_node.empty_spot + 1) % 3) == 0:
return
new_empty_spot = current_node.empty_spot + 1
new_state = current_node.start_state[:]
new_state = swap_empty_position(new_state, current_node.empty_spot,
new_empty_spot)
if not check_visited(visited_map, new_state):
set_glob_counter()
add_to_visited(visited_map, new_state, COUNTER)
new_node = Node(new_state)
new_node.empty_spot = new_node.find_empty_position()
new_node.depth = new_node.set_depth(current_node)
if new_node.depth > MAX_DEPTH:
increment_max_depth(new_node.depth)
stack.append(new_node)
def user_search_choice(environment):
"""Menu for the user to decide which type of search they would like to perform"""
#Gives the user choices on which type of search they would like to perform. It checks to see if the user input
#valid. If it is, the appropriate functions are called to perform the search.
print(
"\nYour AI agent can search for the solution to your puzzle by using one of "
"the following search algorithms. ")
print("\nPlease select which search you would like to perform.")
user_choice = input("1. Select 1 for breadth first search.\n"
"2. Select 2 for depth first search\n"
"3. Select 3 for A* Search using misplaced tiles.\n"
"4. Select 4 for A* Search using manhattan distance\n")
while not user_choice in ('1', '2', '3', '4'):
print("\nYou did not select a valid option.")
user_choice = input(
"1. Select 1 for breadth first search\n"
"2. Select 2 for depth first search\n"
"3. Select 3 for A* Search using misplaced tiles.\n"
"4. Select 4 for A* Search using manhattan distance\n")
if user_choice == '1':
visited_map = {}
start_time = time.clock()
current_node = Node(environment)
current_node.empty_spot = current_node.find_empty_position()
current_node.create_state_string()
visited_map.update({current_node.state_string: 1})
begin_breadth_first_search(current_node, visited_map, start_time)
if user_choice == '2':
visited_map = {}
start_time = time.clock()
current_node = Node(environment)
current_node.empty_spot = current_node.find_empty_position()
current_node.create_state_string()
visited_map.update({current_node.state_string: 1})
begin_depth_first_search(current_node, visited_map, start_time)
if user_choice == '3':
visited_map = {}
start_time = time.clock()
current_node = Node(environment)
current_node.empty_spot = current_node.find_empty_position()
current_node.create_state_string()
current_node.heuristic = current_node.calculate_misplaced_tiles()
visited_map.update({current_node.state_string: 1})
begin_a_star_misplaced_tiles(current_node, visited_map, start_time)
if user_choice == '4':
visited_map = {}
start_time = time.clock()
current_node = Node(environment)
current_node.empty_spot = current_node.find_empty_position()
current_node.create_state_string()
current_node.heuristic = current_node.calculate_manhattan_distance()
visited_map.update({current_node.state_string: 1})
begin_a_star_manhattan_distance(current_node, visited_map, start_time)