Infopaket

Non-classical logics and their application in software development

ДВС.1.04

Вибіркова дисципліна для ОП

Second

2023/2024

3 Semester

3

PLO01. Know and systematically apply methods of analysis and modeling of the application area, identifying information needs and collecting source data for software design. PLO08. Conduct analytical research on the parameters of software systems for their validation and verification, as well as analyze the selected methods, tools for automated design and implementation of software. PLO13. Prepare research results in the form of articles in scientific journals and abstracts of reports at scientific and technical conferences PLO14. Explain, analyze, purposefully search for and select the necessary for the solution of professional scientific and applied problems of information and reference and scientific and technical resources and sources of knowledge, taking into account modern advances in science and technology.

Distance form

1. Know: basics of elementary mathematics, discrete mathematics, algebra, mathematical logic and theory of algorithms, elements of categorical analysis and fuzzy logic. 2. Be able to: apply in practice the tools of design and development of fuzzy software, design and develop categorical models of algorithmization and knowledge representation. 3. To have skills: to design and develop fuzzy models of knowledge representation, to apply in practice categorical means of research of computability of basic constructions of construction of algorithms.

The purpose of the discipline - "Non-classical logics and their application in software development" is to expand knowledge of category theory and fuzzy logic to build appropriate mathematical models of knowledge representation. As a result of studying the discipline the student must: know the basic concepts and definitions of categorical and fuzzy logic, the principles of construction and research of fuzzy inference systems, tools for integrating categorical and fuzzy models in the software product. Be able to use tools to integrate categorical and fuzzy models in the software product, build and research categorical and fuzzy models of knowledge representation.

1. D. Rutkovskaya, M. Pilinsky, L. Rutkovsky. Neural networks, genetic algorithms and fuzzy systems. M .: Telekom, 2006. - 382 p. 2. J. Leski. Systemy neuronowo-rozmyte. Warszawa: Naukowo-Techniczne, 2008. – 690 c. 3. Zadeh L.A. Fuzzy sets as a basis for a theory of possibility // Fuzzy Sets and Systems, 1978, N1, p. 3–28. 4. Goldblatt R. Topoi. Categorical analysis of logic. – M. – Mir. – 1983. 5. Johnston P. The theory of topoi. – M. – Mir. –1978. 6. Kuts A.G. Topoi. Tasks and guidelines . - Omsk. University. – 1989. 7. Bartosz Milewski. Category Theory for Programmers. Version v1.0.0-0-g41e0fc3. October 21, 2018. 8. Lutz M. We study Python, 4th edition. - SP .: Simvol-Plus, 2011.

Lectures, independent work, tests, homework, defense of independent work (project), credit.

1. Test 1: LO 1.1, LO1.2 - 20 points / 12 points. 2. Test 2: LO 1.2, LO1.3 - 20 points / 12 points. 3. Independent work 1: LO2.1, LO3.1, LO4.1, LO4.2 – 30 points /18 points. 4. Independent work 2: LO2.1, LO3.1, LO4.1, LO4.1 – 20 points /18 points. - final evaluation (in the form of a test)

Ukrainian