Course details

Fundamentals of Artificial Intelligence (in English)

IZUe Acad. year 2026/2027 Winter semester 4 credits

Problem solving, searching state space, decomposition into subtasks, playing games. Logic and resolution methods, basics of the PROLOG language. Principles of machine learning. Feature-based and structural image recognition. Basics of computer vision. Basic principles of working with natural language. Application areas of artificial intelligence.

Why is the course taught
In the IZU course, students should gain knowledge what artificial intelligence is, realize that the artificial intelligence does not mean artificial being, but that it is a serious and very useful branch of computer science. Furthermore, students will learn basic techniques and approaches to solving problems that they can use them for the creation of artificially intelligent systems.

Equiment (freely available)

  • SWI PROLOG - verze 6.2.6, Copyright (c) 1990-2012 University of Amsterdam, VU Amsterdam

Exam prerequisites
To be allowed to take the final exam, the student has to obtain at least

  • 20 points from computer labs and
  • 20 poits from the mid-semester exam

Guarantor

Zbořil František, doc. Ing., Ph.D. (DITS)

Course coordinator

Rozman Jaroslav, Ing., Ph.D. (DITS)

Language of instruction

English

Completion

Credit+Examination (written)

Time span

  • 26 hrs lectures
  • 13 hrs pc labs

Assessment points

  • 60 pts final exam (written part)
  • 20 pts mid-term test (written part)
  • 20 pts numeric exercises

Department

Department of Intelligent Systems (UITS)

Lecturer

Rozman Jaroslav, Ing., Ph.D. (DITS)
Zbořil František, doc. Ing., Ph.D. (DITS)

Instructor

Rozman Jaroslav, Ing., Ph.D. (DITS)

Learning objectives

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 computer vision and natural language processing.
Students acquire knowledge of various approaches of problem solving and base information about machine learning, computer vision and natural language processing. They will be able to create programs using heuristics for problem solving.

Prerequisite knowledge and skills

None.

Study literature

  • Zbořil,F., Hanáček,P.: Umělá inteligence, Skripta VUT v Brně, VUT v Brně, 1990, ISBN 80-214-0349-7
  • Mařík,V., Štěpánková,O., Lažanský,J. a kol.: Umělá inteligence (1)+(2), ACADEMIA Praha, 1993 (1), 1997 (2), ISBN 80-200-0502-1
  • Luger,G.F., Stubblefield,W.A.: Artificial Intelligence, The Benjamin/Cummings Publishing Company, Inc., 1993, ISBN 0-8053-4785-2

Syllabus of lectures

  1. Introduction, agent and environments, types of AI problems.
  2. Uninformed searching methods (BFS, DFS, DLS, IDS, BS, UCS, Backtracking, Forward checking).
  3. Informed searching methods, cont. (BestFS, GS, A*, IDA, SMA, Hill Climbing, Simulated annealing, Heuristic repair).
  4. Solving problem methods, cont. (Problem decomposition, AND/OR graphs, CSP tasks).
  5. Methods of game playing (minimax, alpha-beta, games with unpredictability).
  6. Logic and AI, resolution and it's application in problem solving.
  7. Knowledge representation (representational schemes).
  8. Implementation of basic search algorithms in PROLOG.
  9. Machine learning.
  10. Fundamentals of pattern recognition theory.
  11. Principles of computer vision.
  12. Principles of natural language processing.

Syllabus of computer exercises

  1. Problem solving - uninformed search
  2. Problem solving - informed search
  3. Game play - minmax, alpha-beta pruning
  4. Test
  5. Resolution method
  6. Prolog - simple predicates
  7. Simple programs for image recognition

Progress assessment

  • Mid-term written examination - 20 points
  • Programs in computer exercises - 20 points


Written mid-term exam

Schedule

DayTypeWeeksRoomStartEndCapacityLect.grpGroupsInfo
Mon lecture 1., 2., 4., 5. of lectures M104 M105 14:0015:5041 INTE xx Rozman
Mon lecture 6., 8., 9., 11., 12., 13. of lectures M104 M105 14:0015:5041 INTE xx Zbořil
Mon lecture 7., 10. of lectures M104 M105 14:0015:5041 INTE xx
Mon comp.lab 5., 6., 7., 8., 9., 10., 11. of lectures N203 16:0017:5020 INTE xx Rozman
Wed comp.lab 5., 6., 8., 9., 10., 11. of lectures N203 11:0012:5020 INTE xx Rozman
Thu comp.lab *) lectures N203 11:0012:5020 INTE xx Rozman
It is not possible to register this class in Studis. (Some exercises may be opened later if needed, but this is not guaranteed.)
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