moritzwa / ai-basics-coursework

Coursework AI Basics

Notes

I published my notes for the [Guild] Artificial Intelligence (Fall 2020) lectures and the CS50’s Introduction to Artificial Intelligence with Python course.

• AI Guild
• CS50 AI

Projects

My projects focus on planning because its techniques will be applied in my current CODE project Study Journey. I focused less on reasoning because there isn't much application of its techniques in our project.

Planning

• Maze

  • Inside the Planning/maze directory run python maze.py maze[1-5].txt [DFS | BFS | HS]

• TicTacToe

  • Inside the Planning/tictactoe directory run python runner.py to play against the ai.

Optimization

• Crossword
• Inside the Optimization/minesweeper run python generate.py data/structure1.txt data/words1.txt, to specifying a structure file and a words file. If an assignment is possible, you should see the resulting assignment printed.

This project is an AI to create a crossword puzzle. It's technically speaking, not an optimization but a constraint satisfaction problem (CSP). It would be one if there were a continuous rating of a produced crossword puzzle. However, with this exercise, the outcome was binary.

Reasoning

• Minesweeper
  • Inside the Reasoning/minesweeper directory, run python runner.py

Neural Networks

• Traffic

  • Download the distribution code from https://cdn.cs50.net/ai/2020/x/projects/5/traffic.zip and unzip it.
  • Download the data set for this project and unzip it. Move the resulting gtsrb directory inside of your traffic directory. Inside the traffic directory, run pip3 install -r requirements.txt to install this project’s dependencies: opencv-python for image processing, scikit-learn for ML-related functions, and tensorflow for neural networks.
  • Inside of the Neural_Networks/traffic directory, run python traffic.py gtsrb to train the network.

  This project includes a markdown file in which I document my experimentation process and describe how I was investigating different options.