Introduction For this assignment, you will implement the A* algorithm to solve the sliding tile puzzle game. Your goal is to return the instructions for solving the puzzle and show the configuration after each move.

Requirements

You are to create a program in Python 3 that performs the following (you can use another language you are comfortable with. In either case, make sure to pay close attention to requirements):

1. Loads the mp1input.txt file from the current directory. This represents the starting state of the sliding puzzle. The format of this file is composed of 3 rows of 3 values, each value separated by a single space. The values are the integers 0 through 8 that represent the puzzle. The 0 integer represents an empty space (no tile). Here is an example of the input file contents:

3 1 2

4 7 5

0 6 8

2. Displays heading information to the screen: Artificial Intelligence MP1: A* for Sliding Puzzle SEMESTER: [put semester and year here] NAME: [your name here]

3. Executes the A* algorithm with the Manhattan distance heuristic (as discussed in the textbook).

The goal state is this configuration:

0 1 2

3 4 5

6 7 8

4. Shows the solution in form of the puzzle configurations after each move, the move number, and the action taken. This format should match the sample output shown on the last page. 5. Displays the number of states that A* had to visit in order to get to the solution.

Additional Requirements

1. The name of your source code file should be mp1.py. All your code should be within a single file.

2. You can only import numpy and queue packages.

3. Your code should follow good coding practices, including good use of whitespace and use of both inline and block comments.

4. You need to use meaningful identifier names that conform to standard naming conventions.

5. At the top of each file, you need to put in a block comment with the following information: your name, date, course name, semester, and assignment name.

6. The output should exactly match the sample output shown on the last page. Note that for a different input state, the output may be different. I will be testing on a different input than shown in the sample

HINTS

Its easiest to implement A* if you first define the class of PuzzleState objects. These should contain at least the following: the puzzle configuration (a numpy 2d array), the g/h/f costs, predecessor state reference, and the action that was taken to get to this state from the predecessor. \

Use Pythons built-in PriorityQueue from the queue package to implement the frontier (open) set. Make sure to implement the lt method in your PuzzleState class.

Use Pythons built-in set object to implement the closed set. You will need to make sure you implement the _hash__ method in your PuzzleState class to do this.

What to Turn In You will turn in:

1) solution code and

2) A screencast showing your code execution. Both need to be submitted as one PDF file