Here, I upload my completed assignments at the Course BE5B33KUI: Cybernetics and Artificial Intelligence of CVUT.
- 🔍 Search in Maze Problem: Implementation of A*-Algorithm into kuimaze2 modules (by CVUT), libraries used: heapq, itertools.
- 🎮 Player Creation for Reversi Game: Implementation of the Minimax Algorithm with Alpha-Beta Pruning.
- 🧩 Search in Maze with Markov Decision Process (MDP): The optimal path to the terminal state is determined by value- and policy-iteration.
- 🤖 Reinforcement Learning by implementing Q-Learning in a maze environment: The optimal policy is determined by running episodes and adjusting the learning rate and discount factor.
- 📊 Machine Learning: Digit recognition using k-Nearest Neighbors (k-NN) clustering and Naive Bayes approaches, and determining the optimal classifier by evaluating the Receiver Operating Characteristic (ROC) curve.