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.
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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.