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The goal of this subject is to introduce the basics of symbolic artificial intelligence. We will cover the algorithms of informed and uninformed state space, problem solving methods, reinforcement learning, knowledge representation and (sequential) decision making under uncertainty.
Lectures: Viliam Lisý , Branislav Bošanský , Michal Pěchouček
Seminars: Jaromír Janisch , Michal Šustr , Vojtěch Čermák , Petr Tomášek , Marko Sahan , Vojtěch Jindra
Time tables: Czech English
BRUTE - homework submissions
Labs Notebooks (Google drive)
The students can gain at most 30 points for homework assignments. In order to get the credit (zápočet), they have to submit each task for at least 5 points (before the penalisation for late submissions - penalisation does not prevent getting the credit) and gain at least 15 points for home works overall.
Penalisation for late submission:
Always work on your assignments individually. Plagiarism is being detected and it is not tolerated. If you have an objective reason for difficulties with finishing the assignment on time, contact us, please.
In the middle of the semester, there will be a test similar to the final exam for 15 points.
The final exam is for up to 55 points:
Example past exam tests (since there was a larger change of topics in 2020/2021 and we are gradually updating the content, these can be outdated)
Exam dates:
Example of the questions for midterm test:
(relevant captures mention in individual lectures)