Books, on-line resources, specialization courses will be referenced throughout the lectures - their list is typically at the last slide.
Instead of colorful paper voting cards, you can use the following HTML+Javascript app. Open it on your mobile phone: KUI Voting Cards
| Date | Week | Content | Alternative lecture video from AI@Berkeley |
|---|---|---|---|
| 17.02.2025 BBB rec. | 1 | Rules of the game (grading, assignments, etc.). Cybernetics and AI - very short intro. 01_intro.pdf Solving problems by search. Completeness, Optimality, Complexity. DFS, BFS. 025_search.pdf 025_search_handout_notes.pdf (Updated 2025-02-17) | Uninformed search |
| 24.02.2025 BBB rec. | 2 | Solving problems by search. How to avoid looping forever and how to go faster to the goal. Informed search. Heuristics. A*. 025_search.pdf, 025_search_live_withnotes.pdf, 025_search_handout_notes.pdf | Informed search |
| 03.03.2025 BBB rec. | 3 | Two player-games. Adversarial search - Search when playing against a (rational) opponent. 04_adversarial.pdf 04_adversarial_live_withnotes.pdf 04_adversarial_handout_notes.pdf | Adversarial search |
| 10.03.2025 BBB rec | 4 | Probability and statistics - the required minimum. 045_probability.pdf 045_probability_handout_notes.pdf | Probability |
| 17.03.2025 BBB rec. | 5 | Games with random elements, multi-player games. Expectimax. Utilities. 05_expectimax.pdf 05_expectimax_handout_notes.pdf | Uncertainty and utilities |
| 24.03.2025 BBB rec. | 6 | Decision-making under uncertainty I. Route to goal when action outcome is probabilistic. Value iteration. 06_mdp.pdf 06_mdp_handout_notes.pdf | Markov Decision Processes |
| 31.03.2025 BBB rec. | 7 | Decision-making under uncertainty II. Policy iteration. 07_mdp.pdf 07_mdp_handout_notes.pdf | Markov Decision Processes II |
| 07.04.2025 BBB rec. | 8 | Reinforcement learning I. What if nothing is known about the probability of action outcomes and we have to learn from final success or failure? 08_rl.pdf 08_rl_handout_notes.pdf | Reinforcement learning |
| 14.04.2025 BBB rec. | 9 | Reinforcement learning II. Exploration vs. exploitation. 09_rl.pdf 09_rl_handout_notes.pdf | Reinforcement learning II |
| 21.04.2025 | 10 | Holiday | |
| 28.04.2025 | 11 | Mid-term exam from topics covered up to now. Inspiration: quizzes, lab exercises. | |
| 05.05.2025 BBB rec. | 12 | Bayesian classification and decisions. 10_bayes.pdf 10_bayes_handout_notes.pdf | |
| 12.05.2025 BBB rec. | 13 | Learning from data I. Naive Bayes classifier. Nearest neighbors. Evaluating classifier performance. 11_recog_a.pdf 11_recog_a_handout_notes.pdf | Naive Bayes, ROC curve, video by Andrew Ng, Kernels and Clustering - the nearest neighbors part |
| 19.05.2025 BBB rec. | 14 | Learning from data II. Linear classifiers. 11_recog_b.pdf 11_recog_b_handout_notes.pdf | Perceptrons and Logistic Regression - the logistic regression part |