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FSI-VAI-KAcad. year: 2023/2024
The course introduces basic approaches to artificial intelligence algorithms and classical methods used in the field. Main emphasis is given to automated formulas proves, knowledge representation and problem solving. Practical use of the methods is demonstrated on solving simple engineering problems.
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Rules for evaluation and completion of the course
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Basic literature
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Elearning
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Guided consultation in combined form of studies
Teacher / Lecturer
Syllabus
1. Introduction to artificial intelligence.2. State space, uninformed search.3. Informed search in state space.4. Problem solving by decomposition into sub-problems, AND/OR search methods. 5. Game playing methods.6. Constraint satisfaction problems.7. Predicate logic and resolution method.8. Horn logic and logic programming.9. Non-traditional logics. 10. Knowledge representation.11. Representation and processing of uncertainty. 12. Bayesian and decision networks.13. Markov decision processes.
Guided consultation
1. Introductory motivational examples.2. Uninformed methods of state space search.3. Informed methods of state space search.4. A* algorithm and its modifications. 5. Methods of AND/OR graph search.6. Constraint satisfaction problems.7. Game playing methods.8. Predicate logic and resolution method.9. Logic programming and Prolog. 10. Solving AI problems in Prolog.11. Production and expert systems.12. Bayesian networks.13. Presentation of semester projects.