22211572

Search_Algorithms/Heuristics.py

@@ -2,6 +2,45 @@ import is_goal
 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] == 1 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
 
 
 

Search_Algorithms/solution testing.py

@@ -4,140 +4,168 @@ import is_goal
 import Heuristics
 import time
 
-# ===============================================================================================================
-# BREADTH FIRST SEARCH MAZE
-# ===============================================================================================================
-# Maze Problem, note, the maze is fixed in the allowed state.
-print(Search_Algorithms.BreadthFirstSearch((4, 0), Sucessors.maze_successor, is_goal.is_goal_maze))
-
-# Sudoku
-grid = ((5, 3, 0, 0, 7, 0, 0, 0, 0),
-        (6, 0, 0, 1, 9, 5, 0, 0, 0),
-        (0, 9, 8, 0, 0, 0, 0, 6, 0),
-        (8, 0, 0, 0, 6, 0, 0, 0, 3),
-        (4, 0, 0, 8, 0, 3, 0, 0, 1),
-        (7, 0, 0, 0, 2, 0, 0, 0, 6),
-        (0, 6, 0, 0, 0, 0, 2, 8, 0),
-        (0, 0, 0, 4, 1, 9, 0, 0, 5),
-        (0, 0, 0, 0, 8, 0, 0, 0, 0))
-
-# ===============================================================================================================
-# BREADTH FIRST SEARCH SUDOKU
-# ===============================================================================================================
-sln = (Search_Algorithms.BreadthFirstSearch(grid, Sucessors.sudoku_successor, is_goal.is_goal_sudoku)[-1])
-
-for rows in sln:
-    print(rows)
-
-# ===============================================================================================================
-# DEPTH FIRST SEARCH SUDOKU
-# ===============================================================================================================
-sln = (Search_Algorithms.DepthFirstSearch(
-     grid, Sucessors.sudoku_successor, is_goal.is_goal_sudoku)[-1])
-#
-for rows in sln:
-    print(rows)
-
+# # ===============================================================================================================
+# # BREADTH FIRST SEARCH MAZE
+# # ===============================================================================================================
+# # Maze Problem, note, the maze is fixed in the allowed state.
+# print(Search_Algorithms.BreadthFirstSearch(
+#     (4, 0), Sucessors.maze_successor, is_goal.is_goal_maze))
+
+# # Sudoku
+# grid = ((5, 3, 0, 0, 7, 0, 0, 0, 0),
+#         (6, 0, 0, 1, 9, 5, 0, 0, 0),
+#         (0, 9, 8, 0, 0, 0, 0, 6, 0),
+#         (8, 0, 0, 0, 6, 0, 0, 0, 3),
+#         (4, 0, 0, 8, 0, 3, 0, 0, 1),
+#         (7, 0, 0, 0, 2, 0, 0, 0, 6),
+#         (0, 6, 0, 0, 0, 0, 2, 8, 0),
+#         (0, 0, 0, 4, 1, 9, 0, 0, 5),
+#         (0, 0, 0, 0, 8, 0, 0, 0, 0))
 
-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))
+# # ===============================================================================================================
+# # BREADTH FIRST SEARCH SUDOKU
+# # ===============================================================================================================
+# sln = (Search_Algorithms.BreadthFirstSearch(
+#     grid, Sucessors.sudoku_successor, is_goal.is_goal_sudoku)[-1])
 
-# ===============================================================================================================
-# BREADTH FIRST SEARCH N QUEENS PROBLEM
-# ===============================================================================================================
-sln = (Search_Algorithms.BreadthFirstSearch(board, Sucessors.queens_successor, is_goal.is_goal_queens)[-1])
+# for rows in sln:
+#     print(rows)
 
-output_tuple = tuple(tuple("Q" if value else "." for value in sln)
-                     for sln in sln)
-for rows in output_tuple:
-    print(rows)
+# # ===============================================================================================================
+# # DEPTH FIRST SEARCH SUDOKU
+# # ===============================================================================================================
+# sln = (Search_Algorithms.DepthFirstSearch(
+#     grid, Sucessors.sudoku_successor, is_goal.is_goal_sudoku)[-1])
+# #
+# for rows in sln:
+#     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))
 
+# # ===============================================================================================================
+# # BREADTH FIRST SEARCH N QUEENS PROBLEM
+# # ===============================================================================================================
+# sln = (Search_Algorithms.BreadthFirstSearch(
+#     board, Sucessors.queens_successor, is_goal.is_goal_queens)[-1])
 
-# ===============================================================================================================
-# BREADTH FIRST SEARCH PUZZLE PROBLEM
-# ===============================================================================================================
-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)
 
-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 PUZZLE PROBLEM
+# # ===============================================================================================================
+# sln = (Search_Algorithms.DepthFirstSearch(
+#     board, Sucessors.queens_successor, is_goal.is_goal_queens)[-1])
 
-# # Sliding Puzzle
-initial_puzzle = (
-    (7, 2, 4),
-    (5, 0, 6),
-    (8, 3, 1)
-)
-# ===============================================================================================================
-# BREADTH FIRST SEARCH PUZZLE PROBLEM
-# ===============================================================================================================
-sln = (Search_Algorithms.BreadthFirstSearch(initial_puzzle, Sucessors.puzzle_successor, is_goal.is_goal_puzzle))
+# output_tuple = tuple(tuple("Q" if value else "." for value in sln)
+#                      for sln in sln)
+# for rows in output_tuple:
+#     print(rows)
 
-if sln:
-    for rows in sln:
-        for r in rows:
-            print(r)
-else:
-    print("No solution found")
 
+# # # Sliding Puzzle
+# initial_puzzle = (
+#     (7, 2, 4),
+#     (5, 0, 6),
+#     (8, 3, 1)
+# )
+# # ===============================================================================================================
+# # BREADTH FIRST SEARCH PUZZLE PROBLEM
+# # ===============================================================================================================
+# sln = (Search_Algorithms.BreadthFirstSearch(initial_puzzle,
+#        Sucessors.puzzle_successor, is_goal.is_goal_puzzle))
 
-# ===============================================================================================================
-# DEPTH FIRST SEARCH PUZZLE PROBLEM
-# search was timed on Michael's computer and took 211 seconds, Please be patient
-# ===============================================================================================================
-# start_time = time.time()
-sln = (Search_Algorithms.DepthFirstSearch(initial_puzzle, Sucessors.puzzle_successor, is_goal.is_goal_puzzle)[-1])
-# end_time = time.time()
-# print(end_time - start_time)
+# if sln:
+#     for rows in sln:
+#         for r in rows:
+#             print(r)
+# else:
+#     print("No solution found")
 
-if sln:
-    for rows in sln:
-        print(rows)
-else:
-    print("No solution found")
 
+# # ===============================================================================================================
+# # DEPTH FIRST SEARCH PUZZLE PROBLEM
+# # search was timed on Michael's computer and took 211 seconds, Please be patient
+# # ===============================================================================================================
+# # start_time = time.time()
+# sln = (Search_Algorithms.DepthFirstSearch(initial_puzzle,
+#        Sucessors.puzzle_successor, is_goal.is_goal_puzzle)[-1])
+# # end_time = time.time()
+# # print(end_time - start_time)
 
-# ===============================================================================================================
-# A* SEARCH MAZE PROBLEM
-# ===============================================================================================================
-print(Search_Algorithms.A_StarSearch((4, 0), Sucessors.maze_successor, is_goal.is_goal_maze, Heuristics.maze_opt))
+# if sln:
+#     for rows in sln:
+#         print(rows)
+# else:
+#     print("No solution found")
 
 
 # # ===============================================================================================================
-# # A* SEARCH SUDOKU
+# # A* SEARCH MAZE PROBLEM
 # # ===============================================================================================================
-sln = (Search_Algorithms.A_StarSearch(grid, Sucessors.sudoku_successor,
-                                      is_goal.is_goal_sudoku, Heuristics.sudoku_opt))[-1]
+# print(Search_Algorithms.A_StarSearch((4, 0), Sucessors.maze_successor,
+#       is_goal.is_goal_maze, Heuristics.maze_opt))
 
-for rows in sln:
-    print(rows)
 
+# # # ===============================================================================================================
+# # # A* SEARCH SUDOKU
+# # # ===============================================================================================================
+# sln = (Search_Algorithms.A_StarSearch(grid, Sucessors.sudoku_successor,
+#                                       is_goal.is_goal_sudoku, Heuristics.sudoku_opt))[-1]
 
-# =================================================================================================================
-# A* SEARCH PUZZLE
-# =================================================================================================================
-sln = (Search_Algorithms.A_StarSearch(initial_puzzle, Sucessors.puzzle_successor,
-                                      is_goal.is_goal_puzzle, Heuristics.puzzle_opt))[-1]
+# for rows in sln:
+#     print(rows)
 
-if sln:
-    for rows in sln:
-        print(rows)
-else:
-    print("No solution found")
 
+# # =================================================================================================================
+# # A* SEARCH PUZZLE
+# # =================================================================================================================
+# sln = (Search_Algorithms.A_StarSearch(initial_puzzle, Sucessors.puzzle_successor,
+#                                       is_goal.is_goal_puzzle, Heuristics.puzzle_opt))[-1]
+
+# if sln:
+#     for rows in sln:
+#         print(rows)
+# else:
+#     print("No solution found")
 
-# # ===============================================================================================================
-# # A* SEARCH QUEENS
-# # ===============================================================================================================
 
+# # # ===============================================================================================================
+# # # 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),
+         (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))
+
+sln = (Search_Algorithms.A_StarSearch(board, Sucessors.queens_successor,
+       is_goal.is_goal_queens, Heuristics.queens_opt))[-1]
+
+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