Logic and automated deduction
Course: Artificial Intelligence
Structural unit: Faculty of Computer Science and Cybernetics
Title
Logic and automated deduction
Code
Module type
Обов’язкова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2021/2022
Semester/trimester when the component is delivered
3 Semester
Number of ECTS credits allocated
5
Learning outcomes
Form of study
Full-time form
Prerequisites and co-requisites
1. To know: basic methods of mathematical logic, methods of theorem proving in predicate logic, methods of formalization of program systems and systems of Artificial Intelligence.
2. To be able to: prove theorems in predicate logic, develop program systems and systems of Artificial Intelligence based on their formal models and prove properties of such systems.
Course content
Discipline aim. The aim of the discipline is to provide up-to-date knowledge of mathematic logic, methods of automated deduction and their application for solving problems of Artificial Intelligence, to develop ability to formulate scientific problem and working hypotheses on the basis of understanding of existing and creation of new holistic knowledge, as well as professional practice, to develop and implement new competitive ideas in the field of information technology.
As a result of studying the discipline the student must:
to know the basic concepts and methods of mathematical logic, the hierarchy of logics, logical calculus, methods and tools of proving theorems, methods of describing subject areas, software systems and systems of Artificial Intelligence;
to be able to formalize the properties of subject areas, software systems, and systems of Artificial Intelligence using the apparatus of logic, to use the apparatus of logic to solve problems of artificial intelligence.
Recommended or required reading and other learning resources/tools
3. Schneider K.: Verification of Reactive Systems. Formal Methods and Algorithms. – Berlin-Heidelberg: Springer-Verlag, 2004.
4. Nielson H.R. Semantics with Applications: A Formal Introduction / H.R. Nielson, F. Nielson // John Wiley & Sons Inc. P. 240., 1992
5. Dijkstra E.W. A Discipline of Programming / E.W. Dijkstra // Prentice-Hall, Englewwod Cliffs, New Jersey, 1976.
Planned learning activities and teaching methods
Lectures, independent work, Test, current evaluation, exam.
Assessment methods and criteria
1. Test 1: LO 1.1, LO 2.1, LO3.1 - 20 балів/12 балів.
2. Test 2: LO1.2, LO2.2, LO3.1 - 20 балів/12 балів.
2. Test 3: LO1.2, LO2.2, LO3.1 - 15 балів/9 балів.
3. Current evaluation: LO3.1, LO4.1, LO4.2 - 5 points / 3 points.
An applicant may not be admitted to the final assessment if during the semester he: 1) has not reached
the minimum threshold level (60%) of the assessment of those learning outcomes that cannot be assessed
during the final control; 2) scored the number of points, which is insufficient to obtain a positive assessment,
even if he achieves the maximum possible result in the final control.
The recommended minimum is 36 points.
Language of instruction
Ukrainian
Lecturers
This discipline is taught by the following teachers
Mykola
S.
Nikitchenko
Theory and Technology of Programming
Faculty of Computer Science and Cybernetics
Faculty of Computer Science and Cybernetics
Departments
The following departments are involved in teaching the above discipline
Theory and Technology of Programming
Faculty of Computer Science and Cybernetics