About

• Exercise implementing Constraint Satisfaction Problems (CSP) by implementing the N-Queens problem using symbolic constraints in a Jupyter notebook, and solving it using the Backtracking Search algorithm from AIMA.

To launch the notebook, run the following command from a terminal with anaconda3 installed and on the application path:

• Guide on Jupiter Notebook https://www.datacamp.com/community/tutorials/tutorial-jupyter-notebook#gs.WPbJuKE

Setup

• Install Jupyter Notebook App with Miniconda http://jupyter.readthedocs.io/en/latest/install.html

  pip3 install --upgrade pip setuptools
  pip3 install jupyter
  pip3 install matplotlib util sympy
  

• Launch Jupyter Notebook App jupyter notebook AIND-Constraint_Satisfaction.ipynb

• Run code:

  • Click any section containing a code snippet and go to menu: Cells > Run All, then view the outputs shown below the code snippets

Solution - Sympy

• http://localhost:8888/notebooks/Sympy_Intro.ipynb

Warmup: Add to top of code snippet

pip3 install sympy

SymPy Exercises

• Question 1

  • Solution

     A = symbols("A:A0, A:A1, A:A2")
    

• Question 2

  • Solution

     from operator import xor
     x, y = symbols("x y")
     xor_relation = xor(x, y)
     # alternative:
     # xor_relation = x ^ y
     E = xor_relation
    

• Question 3

  • Solution

     a, b, c = symbols(['a', 'b', 'c'])
     maxAbsDiff = constraint("MaxAbsDiff", abs(a - b) < c)
    
     A = symbols("A:A0, A:A1, A:A2")
     maxAbsDiff_copy = maxAbsDiff.subs({a: A[0], b: A[1], c: A[2]})
    

• Question 4

  • Attempt (WRONG) https://discussions.udacity.com/t/sympy-intro-lab-question-4-help/229192/8

Solution

• diffDiag
  • Discussion https://discussions.udacity.com/t/diffdiag-using-symbol/229264/8