====== Lectures ====== Instead of colorful paper voting cards, you can use the following HTML+Javascript app. Open it on your mobile phone: [[https://cw.felk.cvut.cz/courses/b3b33kui/KUI_voting_cards.html|KUI Voting Cards]] * Lectures are delivered by [[mailto:petr.posik@cvut.cz|Petr Pošík]] or [[http://cmp.felk.cvut.cz/~svoboda|Tomas Svoboda (TS)]]. * We strongly suggest attending the lectures personally. Active participation in lectures is welcomed and encouraged. * The lectures will have a hybrid form, they will be streamed and recorded. [[http://bigbluebutton.org|BigBlueButton]] integrated in BRUTE will be used to deliver the lectures. * The link to the course room will be available in [[https://cw.felk.cvut.cz/brute/|BRUTE]], at Course => Conference rooms. * The lecture recordings will also be available in BRUTE. * You can also watch the MP4 recordings from the distance teaching during COVID pandemic at the [[https://youtube.com/playlist?list=PLhGZ28DZufNoCmaLlURGOwN2vUo2ARcZb|BE5B33KUI YouTube]] channel. However, beware that the content of the course might have changed slightly since then. * PDF of the slides will be posted on this page. Preliminary version (e.g., last year's) before the lecture. Latest version, including teacher's notes shortly after the lecture. * Please report any mistakes you spot in the lectures. Important corrections may be rewarded with bonus points. [[courses:be5b33kui:literature|Books, on-line resources, specialization courses]] will be referenced throughout the lectures - their list is typically at the last slide. ===== Lecture plan ===== ^ Date ^ Week ^ Content ^ Alternative lecture video from [[https://inst.eecs.berkeley.edu/~cs188/fa18/|AI@Berkeley]] ^ | 16.02.2026 [[https://bbb.fel.cvut.cz//playback/presentation/2.0/playback.html?meetingId=abb8c6e3b26adc86f44bc1ce5f14f0203155748b-1771235101533|BBB rec.]] with tech. issues, [[https://bbb.fel.cvut.cz//playback/presentation/2.0/playback.html?meetingId=ce8f5fe399a024adac20ae566099966c7511d3ac-1739785501499|BBB rec. from last year]] | 1 | **Rules of the game** (grading, assignments, etc.). **Cybernetics and AI** - very short intro. {{ :courses:be5b33kui:lectures:01_intro.pdf |}} **Solving problems by search**. Completeness, Optimality, Complexity. DFS, BFS. {{ :courses:be5b33kui:lectures:025_search.pdf |}} {{ :courses:be5b33kui:lectures:025_search_handout_notes.pdf |}} (Updated 2025-02-17) | [[https://www.youtube.com/watch?v=-Xx0QSFYfIQ&list=PLsOUugYMBBJENfZ3XAToMsg44W7LeUVhF&index=2|Uninformed search]] | | 23.02.2026 | 2 | Solving problems by search. How to avoid looping forever and how to go faster to the goal. Informed search. Heuristics. A*. {{ :courses:be5b33kui:lectures:025_search.pdf |}}, {{ :courses:be5b33kui:lectures:025_search_live_withnotes.pdf |}}, {{ :courses:be5b33kui:lectures:025_search_handout_notes.pdf |}} | [[https://www.youtube.com/watch?v=Mlwrx7hbKPs&list=PLsOUugYMBBJENfZ3XAToMsg44W7LeUVhF&index=3|Informed search]] | | 02.03.2026 | 3 | Two player-games. Adversarial search - Search when playing against a (rational) opponent. {{ :courses:be5b33kui:lectures:04_adversarial.pdf |}} {{ :courses:be5b33kui:lectures:04_adversarial_live_withnotes.pdf |}} {{ :courses:be5b33kui:lectures:04_adversarial_handout_notes.pdf |}} | [[https://www.youtube.com/watch?v=v6RgZBjc8og&list=PLsOUugYMBBJENfZ3XAToMsg44W7LeUVhF&index=6|Adversarial search]] | | 09.03.2026 | 4 | Probability and statistics - the required minimum. {{ :courses:be5b33kui:lectures:045_probability.pdf |}} {{ :courses:be5b33kui:lectures:045_probability_handout_notes.pdf |}}| [[https://www.youtube.com/watch?v=sMNbLXsvRig&list=PLsOUugYMBBJENfZ3XAToMsg44W7LeUVhF&index=12|Probability]] | | 16.03.2026 | 5 | Games with random elements, multi-player games. Expectimax. Utilities. {{ :courses:be5b33kui:lectures:05_expectimax.pdf |}} {{ :courses:be5b33kui:lectures:05_expectimax_handout_notes.pdf |}} | [[https://www.youtube.com/watch?v=n3A29GEzC6g&list=PLsOUugYMBBJENfZ3XAToMsg44W7LeUVhF&index=7|Uncertainty and utilities]] | | 23.03.2026 | 6 | Decision-making under uncertainty I. Route to goal when action outcome is probabilistic. Value iteration. {{ :courses:be5b33kui:lectures:06_mdp.pdf |}} {{ :courses:be5b33kui:lectures:06_mdp_handout_notes.pdf |}} | [[https://www.youtube.com/watch?v=4LW3H_Jinr4&list=PLsOUugYMBBJENfZ3XAToMsg44W7LeUVhF&index=8|Markov Decision Processes]] | | 30.03.2026 | 7 | Decision-making under uncertainty II. Policy iteration. {{ :courses:be5b33kui:lectures:07_mdp.pdf |}} {{ :courses:be5b33kui:lectures:07_mdp_handout_notes.pdf |}} | [[https://www.youtube.com/watch?v=ZToWj64rxvQ&list=PLsOUugYMBBJENfZ3XAToMsg44W7LeUVhF&index=9|Markov Decision Processes II]] | | 06.04.2026 | 8 | **Holiday** | | | 13.04.2025 | 9 | Reinforcement learning I. What if nothing is known about the probability of action outcomes and we have to learn from final success or failure? {{ :courses:be5b33kui:lectures:08_rl.pdf |}} {{ :courses:be5b33kui:lectures:08_rl_handout_notes.pdf |}} | [[https://www.youtube.com/watch?v=TiXS7vROBEg&list=PLsOUugYMBBJENfZ3XAToMsg44W7LeUVhF&index=10|Reinforcement learning]] | | 20.04.2026 | 10 | Reinforcement learning II. Exploration vs. exploitation. {{ :courses:be5b33kui:lectures:09_rl.pdf |}} {{ :courses:be5b33kui:lectures:09_rl_handout_notes.pdf |}} | [[https://www.youtube.com/watch?v=XafrqwHfBKE&list=PLsOUugYMBBJENfZ3XAToMsg44W7LeUVhF&index=11|Reinforcement learning II]] | | 27.04.2026 | 11 | **Mid-term exam** from topics covered up to now. Inspiration: quizzes, lab exercises. | | | 04.05.2026 | 12 | Bayesian classification and decisions. {{ :courses:be5b33kui:lectures:10_bayes.pdf |}} {{ :courses:be5b33kui:lectures:10_bayes_handout_notes.pdf |}} | | | 11.05.2026 | 13 | Learning from data I. Naive Bayes classifier. Nearest neighbors. Evaluating classifier performance. {{ :courses:be5b33kui:lectures:11_recog_a.pdf |}} {{ :courses:be5b33kui:lectures:11_recog_a_handout_notes.pdf |}} | [[https://www.youtube.com/watch?v=1nOb0vwWkAE&list=PLsOUugYMBBJENfZ3XAToMsg44W7LeUVhF&index=20|Naive Bayes]], [[https://www.coursera.org/lecture/python-machine-learning/precision-recall-and-roc-curves-8v6DL| ROC curve]], [[https://youtu.be/W5meQnGACGo |video by Andrew Ng]], [[https://www.youtube.com/watch?v=H9DUTH9lCfg|Kernels and Clustering]] - the nearest neighbors part | | 18.05.2026 | 14 | Learning from data II. Linear classifiers. {{ :courses:be5b33kui:lectures:11_recog_b.pdf |}} {{ :courses:be5b33kui:lectures:11_recog_b_handout_notes.pdf |}} | [[https://www.youtube.com/watch?v=UNr9gHyOnWA&list=PLsOUugYMBBJENfZ3XAToMsg44W7LeUVhF&index=21|Perceptrons and Logistic Regression]] - the logistic regression part | Newer [[https://www.youtube.com/@berkeley-cs188/playlists|recordings of CS188 lectures from Berkeley]]