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Computers labs, seminars

Labs are organized into three main topics: i) problem solving by search, ii) sequential decisions under uncertainty, iii) machine learning - classifying simple images. The labs combine seminar-like discussions and solving/discussing coding problems. Students are expected to come with questions.

There are 5 compulsory programming assignments throughout the semeseter (search, reversi (adversarial search), sequential decision making, reiforcement learning, and classification (2 parts - code and report)) that you will have to upload to BRUTE. The deadlines will be listed only there.

The scheduled labs are the primary places for discussions and consultations. The labs are not compulsory but it is expected you come prepared. We will mark your presence, though. Individual consultations are possible after an agreement. Note, however, that the individual consultations are meant to be used mainly under special circumstances like long illness. If you know about longer absence please approach us beforehand.

The course will start as physical teaching, but might change to Distance teaching if needed. The labs won't be in hybrid form unless for exceptionnal reasons such as a student testing positive and not being able to come, in which case the student should warn us in advance.
date week nr. content
14.02.2022 1 (N-1)-puzzle and refresh Python; quiz on search
21.02.2022 2 Search I
28.02.2022 3 Search II
07.03.2022 4 Adversarial search I
14.03.2022 5 Adversarial search II
21.03.2022 6 Sequential decision-making I
28.03.2022 7 Sequential decision-making II
04.04.2022 8 Reinforcement learning I
11.04.2022 9 Reinforcement learning II
18.04.2022 10 Holiday - Easter Monday
25.04.2022 11 Reinforcement learning III
02.05.2022 12 Bayesian decision-making I
09.05.2022 13 Classification I
16.05.2022 14 Classification II


Unless stated otherwise an individual coding work is required. You are encouraged to discuss ideas but coding must be your work only. See the more detailed description what is meant by this.

courses/be5b33kui/labs/start.txt · Last modified: 2022/02/21 10:51 by gamafili