All material in this repository is made public to be evaluated by other colleagues, for peer-review, to contain homeworks and to take the final exam of the Computational Intelligence @PoliTo course.
Lab 01 (in the set-covering directory): Implement $A^*$ for the Set Covering Problem. The solution can be found in the Lab 01 section of the Notebook.
Lab 02 (in the lab2 directory): Implement a Rule-based agent and an Evolved agent using an ES strategy to play the Nim game. The solution can be found in the Notebook inside the directory.
Lab 03 (in the lab9 directory): Solve the Black-box Problem instances 1, 2, 5, and 10 on a 1000-loci genomes, using a minimum number of fitness calls. The solution can be found in the Notebook inside the directory.
Lab 04 (in the lab10 directory): Use reinforcement learning to devise a Tic-Tac-Toe player. The solution can be found in the Notebook inside the directory.
For the final project, I collaborated with Davide Vitabile s330509. The project can be found at Computational-Intelligence-Project.