Infopaket

Decision making theory

ННД.21

Обов’язкова дисципліна для ОП

First

2022/2023

7 Semester

3

- Use modern mathematical apparatus of continuous and discrete analysis, linear algebra, and analytical geometry to solve theoretical and applied problems in the design and implementation of informatization objects. - Demonstrate knowledge about regularities of random phenomena, their properties, and operations on them, about models of random processes and modern software environments for solving some problems of statistical data processing and predictive models construction.

Full-time form

1. Know materials from standard courses in mathematical analysis, linear algebra, discrete mathematics, differential equations, operations research, probability theory, and mathematical statistics. 2. Be able to build and research decision-making models based on decision-making theory, utility theory, and expert procedures in conditions of certainty, risk, uncertainty, and in conditions of conflict. 3. Possess basic skills of building decision-making models.

Acquaintance and assimilation of the basic principles of decision-making model research, acquisition of practical decision-making skills in various spheres of activity. The basics of the theory of utility, decision-making in conditions of certainty, risk, uncertainty, conflict, and vagueness of data are considered. As a result of studying the academic discipline, the student should know basic concepts and methods of decision-making theory, utility theory, expert procedures in conditions of certainty, risk, uncertainty, conflict, and vagueness of data; expert information processing methods and voting methods; cooperative decision-making methods; be able to: build and research decision-making models based on decision-making theory, utility theory, expert procedures in conditions of certainty, risk, uncertainty, in conditions of conflict and vagueness of data.

1. Voloshyn O.F., Mashchenko S.O. Modeli ta metody pryiniattia rishen. Pidruchnyk. - Kyiv: VPTs „Kyivskyi universytet”, 2010. - 336 p. 2. Voloshyn O.F., Mashchenko S.O. Teoriia pryiniattia rishen. Navchalnyi posibnyk. - Kyiv: VPTs „Kyivskyi universytet”, 2006. - 304 p. 3. Voloshyn O.F., Mashchenko S.O. Metodychni rekomendatsii do vykonannia praktychnykh i laboratornykh robit z teorii pryiniattia rishen. - Kyiv: VPTs „Kyivskyi universytet”, 2001. - 46 p. 4. Diakon V.M., Kovalov L.Ye. Modeli i metody teorii pryiniattia rishen. Pidruchnyk. – Kyiv: ANF HRUP, 2013. – 603 p. 5. Skott Dzh. Konflikti. Kiev: Vneshnetorgizdat, 1991. - 190 p. 6. Volkovich V.L., Voloshin A.F. i dr. Modeli i metodi optimizatsii slozhnikh sistem.- Kiev, Naukova dumka,1993. - 312 p. 7. Voloshyn O.F., Panchenko M.V. Ekspertna systema yakisnoho otsiniuvannia na osnovi bahato parametrychnykh zalezhnostei // «Problemy matematychnykh mashyn i system», 2002, №2. - pp.83-89.

Lectures, practical classes, independent work.

Semester assessment: Test paper 1 18/10 points. Control work 2 18/10 points. Test 18/10 points. Abstract 6/4 points. Final evaluation in the form of credit: the maximum number of points that can be received by a student: 40 points; form of conduct and types of tasks: written work. Types of tasks: 4 tasks. A student receives an overall positive grade in the discipline if his grade for the exam is at least 24 points. A student is admitted to the exam if during the semester he scored at least 36 points in total; completed and on time submitted at least 2 (two) independent works from the list of proposed works.

Ukrainian