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TheMatrixUniverse/main_Backtracking.py
2024-11-02 00:09:48 +03:00

78 lines
3.0 KiB
Python

# Initialize global variables for the map grid and minimum distances
grid_map = []
min_distances = []
def observe(x, y):
# Sends a move command and receives information on perceived cells around position (x, y)
print(f"m {x} {y}")
num_items = int(input()) # Number of items perceived in the vicinity
for temp in range(num_items):
# Process each perceived item with coordinates and type
item_info = input().split()
item_x, item_y, item_type = item_info[0], item_info[1], item_info[2]
item_x = int(item_x)
item_y = int(item_y)
item_type = item_type[0]
# Update the grid map with the perceived item at the given position
grid_map[item_y][item_x] = item_type
def find_path(x, y):
# Explore surroundings from the current position (x, y)
observe(x, y)
# Try moving right if within bounds, the cell is safe, and the new distance is shorter
if x + 1 < 9 and grid_map[y][x + 1] not in ('P', 'A', 'S') and min_distances[y][x + 1] > min_distances[y][x] + 1:
min_distances[y][x + 1] = min_distances[y][x] + 1
find_path(x + 1, y) # Recursive call to explore the new position
observe(x, y) # Explore again after returning
# Try moving left with similar conditions
if x - 1 >= 0 and grid_map[y][x - 1] not in ('P', 'A', 'S') and min_distances[y][x - 1] > min_distances[y][x] + 1:
min_distances[y][x - 1] = min_distances[y][x] + 1
find_path(x - 1, y)
observe(x, y) # Explore again after returning
# Try moving down
if y + 1 < 9 and grid_map[y + 1][x] not in ('P', 'A', 'S') and min_distances[y + 1][x] > min_distances[y][x] + 1:
min_distances[y + 1][x] = min_distances[y][x] + 1
find_path(x, y + 1)
observe(x, y) # Explore again after returning
# Try moving up
if y - 1 >= 0 and grid_map[y - 1][x] not in ('P', 'A', 'S') and min_distances[y - 1][x] > min_distances[y][x] + 1:
min_distances[y - 1][x] = min_distances[y][x] + 1
find_path(x, y - 1)
observe(x, y) # Final exploration after checking all directions.
# Create a 9x9 grid map filled with '.'
grid_map = [['.' for temp in range(9)] for temp in range(9)]
# Create a minimum distance grid with initial values set to "infinity" (10000)
min_distances = [[10000 for temp in range(9)] for temp in range(9)]
# Read perception variant
variant = int(input())
# Read Keymaker's position
position_input = input().split()
keymaker_x = int(position_input[0])
keymaker_y = int(position_input[1])
# Set the starting position (0, 0) with a minimum distance of 0
min_distances[0][0] = 0
# Start the recursive pathfinding search from the starting position
find_path(0, 0)
# Output the result based on the minimum distance to the Keymaker's position
if min_distances[keymaker_y][keymaker_x] == 10000:
print("e -1") # If no path is found, output -1
else:
print("e " + str(min_distances[keymaker_y][keymaker_x])) # Output the shortest path length