tempCodeRunnerFile.python

class EightPuzzleDFS:
    def __init__(self, initial_state, goal_state):
        self.initial_state = initial_state
        self.goal_state = goal_state
        self.visited = set()
        self.path = []

    def dfs(self, current_state, depth):
        # Check if the current state is the goal state
        if current_state == self.goal_state:
            return True

        # Avoid revisiting states to prevent infinite loops
        if current_state in self.visited:
            return False

        # Mark the current state as visited
        self.visited.add(current_state)

        # Perform DFS for each possible move
        for next_state in self.generate_possible_moves(current_state):
            if self.dfs(next_state, depth + 1):
                self.path.append(next_state)
                return True

        return False

    def generate_possible_moves(self, state):
        # Implement the logic to generate possible moves from the current state
        # This will depend on your specific representation of the puzzle and legal moves

    def solve(self):
        # Start DFS from the initial state
        if self.dfs(self.initial_state, 0):
            # Reverse the path to get the correct order
            self.path = self.path[::-1]
            return self.path
        else:
            return None


# Example usage:
initial_state = "120345678"
goal_state = "012345678"

solver = EightPuzzleDFS(initial_state, goal_state)
solution_path = solver.solve()

if solution_path:
    print("DFS Algorithm")
    print("-----------------")
    print(f"Path Cost: {len(solution_path)}")
    print(f"No of Node Visited: {len(solver.visited)}")
    print("-----------------")

    for state in solution_path:
        # Print each state in the solution path
        print_state(state)
        print("-----")
else:
    print("No solution found.")