Artificial Intelligence

Machine Problem 3 – Course Planning using a Constraint Satisfaction Problem Formulation

Introduction

For this assignment, you will implement a program that uses a Constraint Satisfaction Problem (CSP) formulation to find possible degree plans for students in the M.S. in Data Science program at Lewis University. A degree plan is a mapping of academic terms to courses. For example, “Year 1 Fall 2” to “MATH-51100”. This information can be used to help students pick courses and also to determine a course rotation that allows students to complete the degrees in the specified number of terms.

Requirements

You are to use Python 3 with the python-constraint package to determine the number of possible degree plans for a given start and end term under the constraints given below. Also, your code should generate one possible degree plan that satisfies all constraints. The information needed for formulating the CSP is given within the two sheets of the csp_course_rotations.xlsx file. The first sheet (course_rotations) provides a listing of all available courses, their type (foundation, core, elective, or capstone), and the term availability (0 - unavailable, 1 - available) for each of the terms (1: Fall 1, 2: Fall 2, 3: Spring 1, 4: Spring 2, 5: Summer 1, 6: Summer 2).

The second sheet (prereqs) specifies which course must be taken before another. Note that a course may have multiple prerequisites.

Your program must output the number of possible degree plans and one possible degree plan for a student that starts in Year 1 Fall 1 and finishes in Year 3 Fall 2. The degree plan must satisfy the following requirements:

Student will take one and only one course per term.
Course that has prerequisites must be taken in a term that follows the term in which all prerequisites are done.
The student does not need to repeat courses.
Some terms may be skipped as long as the student finishes in Year 3 Fall 2.
Student needs to take 3 out of the 8 elective courses. It doesn’t matter which ones are included in the degree plan.
1. Those courses which are not taken will be labeled as “Not Taken” (see sample output).
Student must take all foundation and core courses.
The program will generate the output shown in the sample output at the end.

Additional Requirements

The name of your source code file should be mp3.py. All your code should be within a single file.
You can only import numpy, pandas, and constraint packages.
Your code should follow good coding practices, including good use of whitespace and use of both inline and block comments.
You need to use meaningful identifier names that conform to standard naming conventions.
At the top of each file, you need to put in a block comment with the following information:
1. your name,
2. date,
3. course name,
4. semester,
5. and assignment name.

HINTS

You can load an Excel file using pandas’ pd.read_excel function. The sheet is specified by the sheet_name attribute.

Sample Program Output

CLASS: Artificial Intelligence, Lewis University 
NAME: [put your name here]

START TERM = Year 1 Fall 1
Number of Possible Degree Plans is 9488

Sample Degree Plan
Not Taken         CPSC-57400
Not Taken         CPSC-57200
Not Taken         CPSC-57100
Not Taken         CPSC-55200
Not Taken         CPSC-51700
Year 1 Fall 1     CPSC-50600
Year 1 Fall 2     MATH-51100
Year 1 Spring 1   MATH-51000
Year 1 Spring 2   MATH-51200
Year 1 Summer 1   CPSC-50100
Year 2 Fall 1     CPSC-51100
Year 2 Fall 2     CPSC-53000
Year 2 Spring 1   CPSC-54000
Year 2 Spring 2   CPSC-55500
Year 2 Summer 1   CPSC-51000
Year 2 Summer 2   CPSC-52500
Year 3 Fall 1     CPSC-55000
Year 3 Fall 2     CPSC-59000

Dependencies

openpyxl

You will need openpyxl to open the files.

pip install openpyxl

Constraints

Find documentation on constraints used in this solution at https://labix.org/doc/constraint/

amajor/artificial-intelligence-machine-problem-3