Lectures

Lectures are delivered by Petr Pošík or Tomas Svoboda (TS).

The course starts in regular contact teaching regime, but might change to distance teaching if needed.

We strongly suggest to attend the lectures personally. But we plan to make the lectures hybrid, such that you can take part also online. BigBlueButton will be used to deliver the lectures and for discussions. You will find the link to the course room in BRUTE, on Course ⇒ Conference rooms. BRUTE will also contain the lecture recordings in several formats:

Internal viewer - full recording, including slides or shared screen, video stream (blackboard), and chat. Please note the BBB player may not work in Safari properly, use another browser. Video stream (blackboard) and the slide screen can be interchanged.
MP4 - video containing only slides/shared screen. No blackboard recording.
PDF - pdf with all drawings made during the on-line session into the slides.

You can also watch the MP4 recordings from the last year distance teaching at the BE5B33KUI YouTube channel.

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. If you spot mistakes in the slides, please report them. Important corrections may be rewarded with bonus points. Active participation in lectures is welcomed and encouraged.

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 AI@Berkeley
14.02.2022 BBB recording	1	Rules of the game (grading, assignments, etc.). Cybernetics and AI - motivation. Course overview. Is every problem solvable? N-puzzle. 01_intro.pdf
21.02.2022 BBB recording	2	Solving problems by search. Trees and graphs. Completeness, Optimality, Complexity. DFS, BFS. 02_search.pdf, 02_search_handout_notes.pdf	Uninformed search
28.01.2022 BBB recording	3	Solving problems by search. How to avoid looping forever and how to go faster to the goal. Informed search. Heuristics. A*. 03_search.pdf 03_search_live_withnotes.pdf	Informed search
07.03.2022 Lecture not recorded. Use BBB recording from previous year.	4	Two player-games. Adversarial search - Search when playing against a (rational) opponent. 04_adversarial.pdf 04_adversarial_live_withnotes.pdf.	Adversarial search
14.03.2022 BBB recording	5	Games with random elements, multi-player games. Expectimax. Utilities. 05_expectimax.pdf 05_expectimax_live_withnotes.pdf	Uncertainty and utilities
21.03.2022 BBB recording	6	Decision-making under uncertainty I. Route to goal when action outcome is probabilistic. Value iteration. 06_mdp.pdf 06_mdp_live_withnotes.pdf	Markov Decision Processes
28.03.2022 BBB recording	7	Decision-making under uncertainty II. Policy iteration. 07_mdp.pdf 07_mdp_live_withnotes.pdf	Markov Decision Processes II
04.04.2022 BBB recording	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_live_withnotes.pdf	Reinforcement learning
11.04.2022 BBB recording	9	Reinforcement learning II. Exploration vs. exploitation. 09_rl.pdf 09_rl_live_withnotes.pdf	Reinforcement learning II
18.04.2022		Holiday - Easter Monday
25.04.2022	10	Mid-term exam from topics covered up to now. Inspiration: quizzes.
02.05.2022 BBB recording	11	Basic concepts of probability. Bayesian classification and decisions. 10_bayes.pdf 10_bayes_live_withnotes.pdf	Probability
09.05.2022 BBB recording	12	Naive Bayesian classification, Laplace smoothing, Precision, Recall and ROC curve. 11_recog_a.pdf 11_recog_a_live_withnotes.pdf	Naive Bayes, ROC curve, video by Andrew Ng
16.05.2022 BBB recording	13	Linear classifiers, perceptron. 11_recog_b.pdf 11_recog_b_live_withnotes.pdf	Perceptrons and Logistic Regression - the perceptron part, or Nearest neighbor (k-nn) classification, watch Kernels and Clustering - the nearest neighbors part