- Cosimo Botticelli (Matricula: 685308)
- Maria Colella (Matricula: 684043)
- Michele Mattiello (Matricula: 683950)
- Nazifa Mosharrat (Matricula: 682012)
- Roberto Della Rocca (Matricula: 684001)
Welcome to our exploration of pathfinding algorithms in the Minihack environment. In simple terms, we're checking out four key players: Hill Climb (and its variation with added Backtracking), Local Beam Search, Simulated Annealing, and Genetic Algorithm. Think of these algorithms as GPS systems in the game world, helping the player in finding the best route through challenges of various difficulties. We'll break down each algorithm's strengths and weaknesses, aiming to provide a clear picture of when and where they shine.
We tested the following algorithms:
- Hill Climbing
- Simulated Annealing
- Local Beam Search
- Genetic Algorithm
A specific environment must be set up to run the project. We have provided two files: requirements.txt and environment.yml, where the former you can import with pip via this command
pip install -r requirements.txt
and the latter to set up a Conda environment with this command
conda env create --file environment.yml -n <name_env>.