From 5d796d50d731e8c3c6dcfc38082db43bcbcada04 Mon Sep 17 00:00:00 2001
From: tnbeats <tnbeatsprod@gmail.com>
Date: Sun, 19 Nov 2023 15:21:54 +0100
Subject: [PATCH] 22211572
---
Search_Algorithms/Heuristics.py | 39 +++
.../__pycache__/Heuristics.cpython-311.pyc | Bin 0 -> 3688 bytes
.../Search_Algorithms.cpython-311.pyc | Bin 1831 -> 2520 bytes
.../__pycache__/Sucessors.cpython-311.pyc | Bin 8246 -> 11320 bytes
.../__pycache__/is_goal.cpython-311.pyc | Bin 1248 -> 1248 bytes
Search_Algorithms/solution testing.py | 252 ++++++++++--------
6 files changed, 179 insertions(+), 112 deletions(-)
create mode 100644 Search_Algorithms/__pycache__/Heuristics.cpython-311.pyc
diff --git a/Search_Algorithms/Heuristics.py b/Search_Algorithms/Heuristics.py
index 1350d1e..ec2ebf6 100644
--- a/Search_Algorithms/Heuristics.py
+++ b/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
diff --git a/Search_Algorithms/__pycache__/Heuristics.cpython-311.pyc b/Search_Algorithms/__pycache__/Heuristics.cpython-311.pyc
new file mode 100644
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diff --git a/Search_Algorithms/solution testing.py b/Search_Algorithms/solution testing.py
index cb98f7f..60914e7 100644
--- a/Search_Algorithms/solution testing.py
+++ b/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
--
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