This repository contains practical tasks for the Artificial Intelligence 1 course, that is based on book by Russel and Norvig Artificial Intellignece: A Modern Approach, 4th Edition. Tasks are designed to review AI algorithms and use them to play games.
All assignments will be written in python. Task were created for python 3.9 however there should not be any problems with backward compatibility. You can solve all assignments while working exclusively with python standard library, however for game visualizations you will need to install modul pygame. For installation you can use pip:
python3 -m pip install -U pygame --user
If you need more detailed, platform-specific instructions you can visit pygame-GettingStarted.
In total there will be 5 programming assignments whose solutions will be submitted via ReCodEx. In each of them you will write an AI agent that plays suitable games for corresponding lecture topic. Moreover there will by partial assignments, in which you will need to implement algorithms, that will allow you to implement suitable agent functions, however your agent implementation can use any approach you like.
Game | Suggested Approach |
---|---|
Dino | rule-based agent |
Pac-Man | uniform-cost search |
Sokoban | A* with custom heuristics |
Cell Wars | minimax or Monte Carlo tree search |
Minesweeper | backtracking search for CSPs |
Note that information provided in the early assignments is omitted in later ones.