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)		professor PhD Tatjana Lutovac asst. professor PhD Bojana Mihailović
Lecturer/Associate (for practice)		asst. professor PhD Bojana Mihailović professor PhD Tatjana Lutovac
Lecturer/Associate (for OTC)		asst. professor PhD Bojana Mihailović professor PhD Tatjana Lutovac
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
URL to lectures		https://teams.microsoft.com/l/team/19%3AWRqgnEGraPh2ro-IH4klN_ZyYR_5D5IbyeBmhJUwkn41%40thread.tacv2/conversations?groupId=c835f050-df19-4379-9507-09521ee9be3c&tenantId=1774ef2e-9c62-478a-8d3a-fd2a495547ba
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.
Literature
P. Janicic: Mathematical logic in computer science, Faculty of Mathematics, Beograd, 2009. D. Cvetkovic, S. simic: Selected topics from discrete Mathematics, Akademska misao, 2004. S. Russel, P. Norvig: Artificial Intelligence, Pearson Education, 2010. 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
Projects
Colloquia
Seminars		25