22202956 - touch up on heuristics, N-QUEENS

Search_Algorithms/Heuristics.py

@@ -3,45 +3,13 @@ import Sucessors
 
 
 def queens_opt(path):
-
-    """
-    Heuristic for the N-Queens problem that calculates the minimum number of moves
-    required to move each queen to a position where it is not in conflict with any other queen.
-
-    Args:
-    path (list): The path taken so far, where the last element is the current state of the N-Queens board.
-
-    Returns:
-    int: The heuristic value, which is the sum of the minimum moves for all queens.
-    """
     state = path[-1]  # Extracting the current state from the path
     n = len(state)  # Size of the board (N x N)
-    total_moves = 0
-
-    for y in range(n):
-        for x in range(n):
-            if state[y][x] == 1:  # If there's a queen at (y, x)
-                min_moves = n  # Max possible moves
-                # Check for a safe spot in each column
-                for col in range(n):
-                    if col != x:
-                        conflict = False
-                        # Check row and diagonals for conflict
-                        for k in range(n):
-                            if state[y][k] and k != x:
-                                conflict = True
-                                break
-                            if y + (col - x) < n and y + (col - x) >= 0 and state[y + (col - x)][col] == 1:
-                                conflict = True
-                                break
-                            if y - (col - x) < n and y - (col - x) >= 0 and state[y - (col - x)][col] == 1:
-                                conflict = True
-                                break
-                        if not conflict:
-                            min_moves = min(min_moves, abs(col - x))
-                total_moves += min_moves
-
-    return total_moves
+    current_queens = 0
+    # Count the number of outstanding Queens
+    for r in state:
+        current_queens = current_queens + r.count(True)
+    return n - current_queens
 
 
 def maze_opt(path):
@@ -64,3 +32,4 @@ def sudoku_opt(path):
                       Sucessors.choose_best_column(path[-1])]
     return max(starting_point, key=lambda w: w[2])[-1]
 
+

Search_Algorithms/solution testing.py

@@ -41,40 +41,45 @@ import time
 #     print(rows)
 
 #
-# board = ((False, False, False, False, False, False, False, False, False, False),
-#          (False, False, False, False, False, False, False, False, False, False),
-#          (False, False, False, False, False, False, False, False, False, False),
-#          (False, False, False, False, False, False, False, False, False, False),
-#          (False, False, False, False, False, False, False, False, False, False),
-#          (False, False, False, False, False, False, False, False, False, False),
-#          (False, False, False, False, False, False, False, False, False, False),
-#          (False, False, False, False, False, False, False, False, False, False),
-#          (False, False, False, False, False, False, False, False, False, False),
-#          (False, False, False, False, False, False, False, False, False, False))
+board = ((False, False, False, False, False, False, False, False, False, False),
+         (False, False, False, False, False, False, False, False, False, False),
+         (False, False, False, False, False, False, False, False, False, False),
+         (False, False, False, False, False, False, False, False, False, False),
+         (False, False, False, False, False, False, False, False, False, False),
+         (True, False, False, False, False, False, False, False, False, False),
+         (False, False, False, False, False, False, False, False, False, False),
+         (False, False, False, False, False, False, False, False, False, False),
+         (False, False, False, False, False, False, False, False, False, False),
+         (False, False, False, False, False, False, False, False, False, True))
 
-# # ===============================================================================================================
-# # BREADTH FIRST SEARCH N QUEENS PROBLEM
-# # ===============================================================================================================
-# sln = (Search_Algorithms.BreadthFirstSearch(
-#     board, Sucessors.queens_successor, is_goal.is_goal_queens)[-1])
-#
-# output_tuple = tuple(tuple("Q" if value else "." for value in sln)
-#                      for sln in sln)
-# for rows in output_tuple:
-#     print(rows)
+# ===============================================================================================================
+# BREADTH FIRST SEARCH N QUEENS PROBLEM
+# ===============================================================================================================
+start_time = time.time()
+sln = (Search_Algorithms.BreadthFirstSearch(
+    board, Sucessors.queens_successor, is_goal.is_goal_queens)[-1])
+
+output_tuple = tuple(tuple("Q" if value else "." for value in sln)
+                     for sln in sln)
+for rows in output_tuple:
+    print(rows)
+end_time = time.time()
+print(end_time - start_time)
 
 
 # ===============================================================================================================
 # DEPTH FIRST SEARCH N-QUEENS
 # ===============================================================================================================
-# sln = (Search_Algorithms.DepthFirstSearch(
-#     board, Sucessors.queens_successor, is_goal.is_goal_queens)[-1])
-#
-# output_tuple = tuple(tuple("Q" if value else "." for value in sln)
-#                      for sln in sln)
-# for rows in output_tuple:
-#     print(rows)
+start_time = time.time()
+sln = (Search_Algorithms.DepthFirstSearch(
+    board, Sucessors.queens_successor, is_goal.is_goal_queens)[-1])
 
+output_tuple = tuple(tuple("Q" if value else "." for value in sln)
+                     for sln in sln)
+for rows in output_tuple:
+    print(rows)
+end_time = time.time()
+print(end_time - start_time)
 
 # # # Sliding Puzzle
 # initial_puzzle = (
@@ -147,20 +152,26 @@ import time
 # # # A* SEARCH QUEENS
 # # # ===============================================================================================================
 
+board = ((False, False, False, False, False, False, False, False, False, False),
+         (False, False, False, False, False, False, False, False, False, False),
+         (False, False, False, False, False, False, False, False, False, False),
+         (False, False, False, False, False, False, False, False, False, False),
+         (False, False, False, False, False, False, False, False, False, False),
+         (True, False, False, False, False, False, False, False, False, False),
+         (False, False, False, False, False, False, False, False, False, False),
+         (False, False, False, False, False, False, False, False, False, False),
+         (False, False, False, False, False, False, False, False, False, False),
+         (False, False, False, False, False, False, False, False, False, True))
 
 
-
-
-board = ((False, False, False, False),
-         (False, False, False, False),
-         (False, False, False, False),
-         (False, False, False, False))
-
+start_time = time.time()
 sln = (Search_Algorithms.A_StarSearch(board, Sucessors.queens_successor,
        is_goal.is_goal_queens, Heuristics.queens_opt))[-1]
 
-print(sln)
 output_tuple = tuple(tuple("Q" if value else "." for value in sln)
                      for sln in sln)
 for rows in output_tuple:
-    print(rows)
\ No newline at end of file
+    print(rows)
+
+end_time = time.time()
+print(end_time - start_time)
\ No newline at end of file