Title: | Fundamentals of Artificial Intelligence |
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Code: | IZU |
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Ac.Year: | 2017/2018 |
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Term: | Summer |
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Curriculums: | |
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Language of Instruction: | Czech |
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Private info: | http://www.fit.vutbr.cz/study/courses/IZU/private/ |
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Credits: | 4 |
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Completion: | credit+exam (written) |
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Type of instruction: | Hour/sem | Lectures | Sem. Exercises | Lab. exercises | Comp. exercises | Other |
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Hours: | 26 | 0 | 0 | 13 | 0 |
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| Examination | Tests | Exercises | Laboratories | Other |
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Points: | 60 | 20 | 20 | 0 | 0 |
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Guarantor: | Zbořil František V., doc. Ing., CSc., DITS |
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Lecturer: | Zbořil František, doc. Ing., Ph.D., DITS Zbořil František V., doc. Ing., CSc., DITS |
Instructor: | Havlena Vojtěch, Ing., DITS Rozman Jaroslav, Ing., Ph.D., DITS Šoková Veronika, Ing., DITS Šůstek Martin, Ing., DITS Uhlíř Václav, Ing. et Ing., DITS Žák Marek, Ing., DITS |
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Faculty: | Faculty of Information Technology BUT |
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Department: | Department of Intelligent Systems FIT BUT |
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Substitute for: | |
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Schedule: | Day | Lesson | Week | Room | Start | End | Lect.Gr. | St.G. | EndG. |
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Mon | comp.lab | 4., 5., 6., 7., 10., 11., 12. of lectures | N204 | 08:00 | 19:50 | | | |
Mon | comp.lab | 4., 5., 6., 7., 10., 11., 12. of lectures | N203 | 08:00 | 09:50 | | | |
Mon | exam - 1. oprava | 2018-05-28 | D105 | 09:00 | 11:50 | 2BIA | | |
Mon | exam - 1. oprava | 2018-05-28 | D105 | 09:00 | 11:50 | 2BIB | | |
Mon | exam - 1. oprava | 2018-05-28 | D105 | 09:00 | 11:50 | 3BIT | | |
Mon | lecture | lectures | E112 | 11:00 | 12:50 | 2BIB | | |
Mon | lecture | lectures | E104 | 11:00 | 12:50 | 2BIB | | |
Mon | lecture | lectures | E105 | 11:00 | 12:50 | 2BIB | | |
Mon | lecture | lectures | E112 | 11:00 | 12:50 | 3BIT | xx | xx |
Tue | comp.lab | 4., 5., 6., 7., 10., 11., 12. of lectures | N204 | 08:00 | 19:50 | | | |
Tue | lecture | lectures | E112 | 13:00 | 14:50 | 2BIA | | |
Tue | lecture | lectures | E104 | 13:00 | 14:50 | 2BIA | | |
Tue | lecture | lectures | E105 | 13:00 | 14:50 | 2BIA | | |
Tue | lecture | lectures | E112 | 13:00 | 14:50 | 3BIT | xx | xx |
Wed | comp.lab | 4., 5., 6., 7., 10., 11., 12. of lectures | N204 | 08:00 | 19:50 | | | |
Wed | exam - 2. oprava | 2018-06-06 | D105 | 14:00 | 16:50 | 2BIA | | |
Wed | exam - 2. oprava | 2018-06-06 | D105 | 14:00 | 16:50 | 2BIB | | |
Wed | exam - 2. oprava | 2018-06-06 | D105 | 14:00 | 16:50 | 3BIT | | |
Thu | comp.lab | 4., 5., 6., 7., 10., 11., 12. of lectures | N204 | 08:00 | 13:50 | | | |
Thu | comp.lab | 4., 5., 6., 7., 10., 11., 12. of lectures | N203 | 08:00 | 09:50 | | | |
Thu | exam - řádná | 2018-05-17 | D105 | 13:00 | 15:50 | 2BIA | | |
Thu | exam - řádná | 2018-05-17 | D105 | 13:00 | 15:50 | 2BIB | | |
Thu | exam - řádná | 2018-05-17 | D105 | 13:00 | 15:50 | 3BIT | | |
Thu | exam - řádná | 2018-05-17 | D0206 | 13:00 | 15:50 | 2BIA | | |
Thu | exam - řádná | 2018-05-17 | D0206 | 13:00 | 15:50 | 2BIB | | |
Thu | comp.lab | 4., 5., 6., 7., 10., 11., 12. of lectures | N203 | 15:00 | 19:50 | | | |
Fri | comp.lab | 4., 5., 6., 7., 10., 11., 12. of lectures | N204 | 08:00 | 13:50 | | | |
Fri | comp.lab | 4., 5., 6., 7., 10., 11., 12. of lectures | N203 | 08:00 | 13:50 | | | |
Fri | Náhradní cvičení | 2018-05-04 | A218 | 14:00 | 15:50 | | | |
Fri | náhradní cvičení | 2018-05-04 | E104 | 14:00 | 15:50 | | | |
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| Learning objectives: |
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| | To give the students the knowledge of fundamentals of artificial intelligence, namely knowledge of problem solving approaches, machine learning principles and general theory of recognition. Students acquire base information about expert systems, computer vision and natural language processing. | Description: |
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| | Problem solving: State space search (BFS, DFS, DLS, IDS, BS, UCS, Backtracking, Forward checking, Min-conflict, BestFS, GS, A*, Hill Climbing, Simulated annealing methods). Solving optimization problems by nature-inspired algorithms (GA, ACO and PSO). Problem decomposition (And Or graphs), games playing (Mini-Max and Alfa-Beta algorithms). AI language PROLOG and implementations of basic search algorithms in this language. Machine learning principles. Statistical and structural pattern recognition. Basic principles of expert systems. Fundamentals of computer vision. Base principles of natural language processing. Application fields of artificial intelligence. | Knowledge and skills required for the course: |
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- Basic knowledge of the programming in any procedural programming language.
- Knowledge of secondary school level mathematics.
| Subject specific learning outcomes and competences: |
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| | | Generic learning outcomes and competences: |
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- Students will acquaint with problem solving methods based on state space search and on decomposition problem into sub-problems.
- Students will acquaint with basic game playing methods of two players.
- Students will learn to solve optimization problems.
- Students will acquaint with fundamentals of propositional and predicate logics and with their applications.
- Students will learn how to use basic methods of machine learning.
- Students will acquaint with fundamentals of machine vision and natural language processing.
| Syllabus of lectures: |
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- Introduction, Artificial Intelligence (AI) definition, types of AI problems, solving problem methods.
- State space search methods.
- Solving methods using decomposition problems into sub-problems.
- Solving optimization problems using algorithms inspired by nature.
- Methods of game playing (two players).
- Logic and AI, resolution and it's application in problem solving and planning.
- PROLOG language and its use in AI.
- Machine learning.
- Pattern recognition.
- Principles of expert systems.
- Principles of computer vision.
- Principles of natural language processing.
- Introduction into agent systems.
| Syllabus of computer exercises: |
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- Problem solving - State Space Search.
- Problem solving - CSP.
- Problem solving - game playing.
- Predicate logic - method of resolution.
- PROLOG language - basic information.
- PROLOG language - simple individual programs.
- Simple programs for pattern recognition.
| Fundamental literature: |
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- Russel,S., Norvig,P.: Artificial Intelligence, Prentice-Hall, Inc., 1995, ISBN 0-13-360124-2, second edition 2003, ISBN 0-13-080302-2, third edition 2010, ISBN 0-13-604259-7
- Ertel, W.: Introduction to Artificial Intelligence, Springer, second edition 2017, ISSN 1863-7310
- Luger,G.F.: Artificial Intelligence - Structures and strategies for Complex Problem Solving, 6th Edition,
Pearson Education, Inc., 2009, ISBN-13: 978-0-321-54589-3, ISBN-10: 0-321-54589-3 | Study literature: |
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- Russel,S., Norvig,P.: Artificial Intelligence, Prentice-Hall, Inc., 1995, ISBN 0-13-360124-2, second edition 2003, ISBN 0-13-080302-2, third edition 2010, ISBN 0-13-604259-7
- Ertel, W.: Introduction to Artificial Intelligence, Springer, second edition 2017, ISSN 1863-7310
| Progress assessment: |
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- Mid-term written examination - 20 points.
- Programs in computer exercises - 20 points.
- Final written examination - 60 points; The minimal number of points which can be obtained from the final written examination is 25. Otherwise, no points will be assigned to a student.
| Exam prerequisites: |
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| | At least 15 points earned during semester (mid-term test + programs in computer exercises). | |
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