CS3520 Project

Team Members of CHOBS:

• Ricardo A. Baeza
• Alec Ortiz
• Alejandro Hernandez
• Steven Chan

Project Demo Presentation & Final Report

• Demo Presentation Link
• Final Report

Technologies:

• Anaconda: Version 4.10.1
• Clingo: Version 5.5.0

Anaconda Installation

$ git clone https://github.com/ricardoaxelbaeza/CHOBS-Project.git

• Anaconda Installation Link: https://docs.anaconda.com/anaconda/install/
• Install Anaconda for Mac OS: https://www.anaconda.com/products/individual#macos
• Install Anaconda for Windows: https://www.anaconda.com/products/individual#windows
• On the command line:
  • $ cd ../path/to/the/file
  • $ conda --v
  • $ conda install -c potassco clingo

Repository Setup

• Clone the repository using 'git clone https://github.com/ricardoaxelbaeza/CHOBS-Project.git'
• Install Anaconda
• Make sure Anaconda is installed, this can be done by entering 'conda --v' into the terminal
• Change Directory to where the project was cloned
• After making sure Anaconda is installed, we then need to install clingo.
• Clingo is installed by entering 'conda install -c potassco clingo' into the terminal command line

Running .lp files

• So after clingo is installed with anaconda:
• To run a .lp file: make sure that you are in the correct folder/path that the .lp file is in
• In the terminal type:
  • $ clingo nameOfFile.lp
• If you wish to see all possible solutions (type 0):
  • $ clingo nameOfFile.lp 0
• Specific amount of solutions (type x: x is 1,2,3 etc.)
  • $ clingo nameOfFile.lp 1

Visualizing files

• Note: Make sure that the python visalization is in the folder that is being tested
  • $ python3 sodoku_viz.py nameOfFile.txt

Running 'Demo' Juypter Notebook

1. Open Command Prompt and change directory to project repository
2. Activate a conda environment that has clingo installed by calling 'conda activate env_name'
3. Enter 'jupyter notebook' on the terminal; A page will open up from the browser
4. Click on the demo.ipynb on the root directory page
5. Press the ▶ Run Button on the toolbar

Achievements:

• Read papers of Answer Set Programming (ASP) with AnsProlog
• Completed first Answer Set Programming example: NQueens.lp
• Visualized output from NQueens.lp
• Completed first successful test sudoku.lp file!
• Visualized output from sudoku.lp
• Initiated Jupyter Notebook
• Completed encoding of classic Sudoku
• Visualized classic Sudoku solutions
• Completed encoding of diagonal Sudoku
• Visualized diagonal Sudoku solutions

Final Goals:

• Encode logic of multiple Sudoku game types with AnsProlog
• Visualize all game type solutions
• Demonstrate encodings & solutions in project demo
• Complete final report