Infopaket

Expert systems

ВК 1.9

Вибіркова дисципліна для ОП

First

2024/2025

8 Semester

5

Apply soft computing and expert evaluation technologies to solve practical problems in various subject areas under deterministic conditions, uncertainty, risk, and conflict.

Full-time form

Know the basics of mathematical analysis; basics of linear algebra; basics of discrete analysis; basics of decision theory; basics of artificial intelligence. Be able to algorithmize mathematical problems; implement algorithms in software. Possess basic skills in building algorithms; programming.

The discipline is devoted to the study of the basics of expert systems, methods of their construction and use for solving applied problems in various fields of human activity. Particular attention is paid to the construction of expert systems, in particular the implementation of methods, models and algorithms for decision support, methods of obtaining and systematizing knowledge, methods of aggregating group expert opinions with competence and feedback, the architecture of modern expert systems. The course also considers the peculiarities of using expert systems in various poorly structured subject areas. Modern software tools for expert decision support are studied, including their use in the field of sustainable development and information security. Laboratory work is aimed at acquiring the skills of students to programmatically implement methods of aggregating group expert opinions, methods, models and algorithms for decision support (R, Python), as well as to build problem-oriented knowledge bases using software tools of expert systems.

1. Zgurovsky M.Z., Pankratova N.D. System analysis: problems, methodology, application. 2nd edition / Kyiv: Nauk.dumka - 2011. - 728 p. 2. Totsenko V.G. Decision support methods and systems. Algorithmic aspect / K.: Nauk. dumka, 2002. - 382 p. 3. Pankratova N.D. , Savchenko I.O. Morphological analysis. Theory, problems, application. / K.: Nauk. dumka, 2015. - 248 p. 4. Hnatienko H.M., Snityuk V.E. Expert technologies of decision-making technologies: Monograph / K.: Maklaut LLC, 2008. - 444 p. 5. Thomas L. Saaty, Kirti Peniwati Group decision making: Drawing Out and Reconciling Differences / RWS Publications, 2007. – 385 p. 6. Gerasimov B.M., Lokaziuk V.M., Oksiyuk O.G., Pomorova O.V. Intelligent decision support systems / K.: Ed. in Europe. University, 2007. – 335 p.

Lectures, Laboratory classes, Student's work independently

During the semester, upon completion of the relevant modules, two written (module) control works are conducted in test form. At the same time, to determine the level of achievement of learning outcomes 2 and 3, some questions are formulated in the form of situational tasks. For students who have not reached the minimum grade level during the semester (60% of the maximum possible number of points, i.e. 48 points), a final semester test is conducted, the maximum grade for which may not exceed 40% of the final grade (up to 40 points on a stobal scale). The condition for obtaining a positive final grade for the discipline is to achieve at least 60% of the maximum possible number of points, while the grade for learning outcomes 2 and 3 cannot be less than 50% of the maximum level.

Ukrainian