Faculty of Information Technology, BUT

Course details

Fundamentals of Artificial Intelligence

IZU Acad. year 2019/2020 Summer semester 4 credits

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.

Guarantor

Deputy Guarantor

Language of instruction

Czech

Completion

Credit+Examination (written)

Time span

26 hrs lectures, 13 hrs pc labs

Assessment points

60 exam, 20 half-term test, 20 exercises

Department

Lecturer

Instructor

Course Web Pages

Subject specific learning outcomes and competences

  • Students will learn terminology in the Artificial Intelligence field both in Czech and in the English language.
  • Students will learn read and so partly write programs in PROLOG language.

Generic learning outcomes and competences

  • 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 logic and with their applications.
  • Students will learn how to use basic methods of machine learning.
  • Students will acquaint with fundamentals of expert systems, machine vision and natural language processing.
  • Students will acquaint with fundamentals of multiagent systems.

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 expert systems, computer vision and natural language processing.

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.

Prerequisite kwnowledge and skills

  • Basic knowledge of programming in any procedural programming language.
  • Knowledge of secondary school level mathematics.

Study literature

  • 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

Fundamental literature

  • 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
  • Pool, D. L., Mackworth, A. K.: Artificial Intelligence, Cambridge University Press, 2010,  ISBN-13 978-0-521-51900-7

Syllabus of lectures

  1. Introduction, Artificial Intelligence (AI) definition, types of AI problems, solving problem methods.
  2. State space search methods.
  3. Solving methods using decomposition problems into sub-problems.
  4. Solving optimization problems using algorithms inspired by nature.
  5. Methods of game playing (two players).
  6. Logic and AI, resolution and it's application in problem-solving and planning.
  7. PROLOG language and its use in AI.
  8. Machine learning.  
  9. Pattern recognition.
  10. Principles of expert systems.
  11. Principles of computer vision.
  12. Principles of natural language processing.
  13. Introduction to agent systems.

Progress assessment

  • 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.

Controlled instruction

Missed lessons (exercises and tests) can be substituted only exceptionally, after proving that the absences had legitimate reasons.

Exam prerequisites

At least 15 points earned during the semester (mid-term test + programs in computer exercises).

Schedule

DayTypeWeeksRoomStartEndLect.grpGroupsInfo
Moncomp.lablectures N203 08:0009:50 2BIA 2BIB 3BIT xx
Monlecturelectures E104 E105 E112 11:0012:50 2BIB 3BIT xx
Moncomp.lablectures N203 N204 12:0013:50 2BIA 2BIB 3BIT xx
Moncomp.lablectures N203 N204 14:0015:50 2BIA 2BIB 3BIT xx
Moncomp.lablectures N203 N204 16:0017:50 2BIA 2BIB 3BIT xx
Tuecomp.lablectures N203 08:0009:50 2BIA 2BIB 3BIT xx
Tuecomp.lablectures N203 10:0011:50 2BIA 2BIB 3BIT xx
Tuelecturelectures E104 E105 E112 13:0014:50 2BIA 3BIT xx
Tuecomp.lablectures N203 14:0015:50 2BIA 2BIB 3BIT xx
Tuecomp.lablectures N203 16:0017:50 2BIA 2BIB 3BIT xx
Wedcomp.lablectures N203 08:0009:50 2BIA 2BIB 3BIT xx
Wedcomp.lablectures N203 10:0011:50 2BIA 2BIB 3BIT xx
Wedcomp.lablectures N203 12:0013:50 2BIA 2BIB 3BIT xx
Wedcomp.lablectures N203 14:0015:50 2BIA 2BIB 3BIT xx
Wedcomp.lablectures N203 N204 16:0017:50 2BIA 2BIB 3BIT xx
Thucomp.lablectures N104 N203 08:0009:50 2BIA 2BIB 3BIT xx
Thucomp.lablectures N104 N203 10:0011:50 2BIA 2BIB 3BIT xx
Fricomp.lablectures N203 N204 08:0009:50 2BIA 2BIB 3BIT xx
Fricomp.lablectures N203 N204 10:0011:50 2BIA 2BIB 3BIT xx
Fricomp.lablectures N203 N204 12:0013:50 2BIA 2BIB 3BIT xx
Fricomp.lablectures N203 14:0015:50 2BIA 2BIB 3BIT xx

Course inclusion in study plans

  • Programme BIT, 2nd year of study, Compulsory
  • Programme IT-BC-3, field BIT, 2nd year of study, Compulsory
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