MS1EKS - Expert Systems

Course specification
Course title Expert Systems
Acronym MS1EKS
Study programme Electrical Engineering and Computing
Module Software Engineering
Type of study master academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
    Lecturer/Associate (for OTC)
      ESPB 6.0 Status elective
      Condition none
      The goal Introduce students to the basic concepts and techniques of artificial intelligence and expert systems. During the course, students will study the implementation of the popular models of these types of applications.
      The outcome Students will be able to recognize a problem that belongs to the field of artificial intelligence and expert systems, and based on their knowledge apply the most appropriate and most effective method for its solution.
      Contents of lectures Search strategies: algorithms, performance, efficiency, complexity. Game theory. Formal logic. Planning - types and the problem. Knowledge and reasoning in uncertain environment. Bayesian networks. Production systems. Problem-solving strategies. Induction systems. Introduction to machine learning.
      Contents of exercises Visual simulation of theoretical problems. Solving and demonstrations of practical tasks.
      1. "Artificial Intelligence - A Modern Approach", S. Russel, P. Norvig (Original title)
      2. "Zbirka zadataka iz Ekspertskih sistema", D. Bojić, M. Gligorić, B. Nikolić, Akademska misao, 2009 (Original title)
      Number of hours per week during the semester/trimester/year
      Lectures Exercises OTC Study and Research Other classes
      2 2 1
      Methods of teaching Lectures, presentations, practical exercises visual simulations, individual work on projects
      Knowledge score (maximum points 100)
      Pre obligations Points Final exam Points
      Activites during lectures 0 Test paper 40
      Practical lessons 0 Oral examination 0
      Projects 20
      Colloquia 40
      Seminars 0