13E083MOAR - Mathematical Basis of Automatic Reasoning

Course specification
Course title Mathematical Basis of Automatic Reasoning
Acronym 13E083MOAR
Study programme Electrical Engineering and Computing
Module Signals and Systems
Type of study bachelor academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
ESPB 3.0 Status elective
Condition Mathematics 1
The goal Familiarize students with basic concepts of logical modeling and reasoning that are used in automated control and management of systems.
The outcome Students get a mathematical basis and also practical hints in treating problems within the scope of their discipline.
Contents of lectures Formalisations, modelling of knowledge and problems using classical nad nonclassical logic (fuzzy logic, linear logic, modal and temporal logic). Uncertain knowledge and reasoning (kvantification, probability reasoning). Automated reasoning, perception, planning and acting.
Contents of exercises Through examples, tasks and problems student learns how to apply theorems and basic concepts that are learnt through theoretical contents.
  1. P. Janicic: Mathematical logic in computer science, Faculty of Mathematics, Beograd, 2009.
  2. D. Cvetkovic, S. simic: Selected topics from discrete Mathematics, Akademska misao, 2004.
  3. S. Russel, P. Norvig: Artificial Intelligence, Pearson Education, 2010.
  4. F. Jensen: Bayesian Networks and Decision Graphs, Springer-Verlag, 2007.
Number of hours per week during the semester/trimester/year
Lectures Exercises OTC Study and Research Other classes
1 1 0.5
Methods of teaching Lectures, tutorials and discussions.
Knowledge score (maximum points 100)
Pre obligations Points Final exam Points
Activites during lectures 25 Test paper 50
Practical lessons Oral examination
Seminars 25