Decision theory
Description: The course is one of the main disciplines and covers the study of mathematical programming problems, solving nonlinear programming problems, fuzzy numbers and sets, operations on them. The basic concepts and definitions of game theory and methods for solving matrix games, the mathematical apparatus of queuing theory for applying probabilistic and statistical methods for describing uncertainties are considered in more detail.
Amount of credits: 5
Пререквизиты:
- Of Informatively-communication technologies
Course Workload:
Types of classes | hours |
---|---|
Lectures | 30 |
Practical works | 15 |
Laboratory works | |
SAWTG (Student Autonomous Work under Teacher Guidance) | 30 |
SAW (Student autonomous work) | 75 |
Form of final control | Exam |
Final assessment method |
Component: University component
Cycle: Profiling disciplines
Goal
- The study of applied sections of mathematics, the use of which will improve technological solutions to ensure the information security of automated systems.
Objective
- getting an idea about the role of decision-making methods in modern applied sciences and about the connection of the discipline with special sections;
- mastering practical computing skills for solving applied decision-making problems in various conditions;
- acquisition of skills to independently replenish knowledge in the field of decision-making methods;
- formation of the ability to analyze the task and choose ways to solve it, as well as optimize the used computational algorithms;
- deepening practical programming skills
Learning outcome: knowledge and understanding
- Possession of the ability to use modern computer technologies for information retrieval to solve the problem, critical analysis of this information and substantiation of the accepted ideas and approaches to decision
- knowledge of the basic methods of mathematical programming
Learning outcome: applying knowledge and understanding
- possession of a systematic approach, mathematical, statistical and heuristic methods in the process decision making.
- ability to use mathematical models of acceptance solutions.
Learning outcome: formation of judgments
- analyze and use in practice the methods of processing, analysis and synthesis of results.
Learning outcome: communicative abilities
- The ability to work in a team in the process of solving practical problems, to express and correctly defend one's point of view in controversial issues.
Learning outcome: learning skills or learning abilities
- be able to use modern computer technologies when searching, justifying and making optimal decisions in practice;
- be able to organize workplaces, the work of small teams and quality control in the development of systems
- strive for professional and personal growth by mastering the techniques and skills for solving specific problems from different areas of the discipline, helping to further solve engineering, production and scientific problems
Teaching methods
Problem-based learning: The creation of problem situations in educational activities and the organization of active independent activity of students to resolve them, as a result of which there is a creative mastery of knowledge, skills, abilities, and mental abilities develop. Information and communication technologies: Changing and unlimited enrichment of the content of education, the use of integrated courses, access to the INTERNET.
Assessment of the student's knowledge
Teacher oversees various tasks related to ongoing assessment and determines students' current performance twice during each academic period. Ratings 1 and 2 are formulated based on the outcomes of this ongoing assessment. The student's learning achievements are assessed using a 100-point scale, and the final grades P1 and P2 are calculated as the average of their ongoing performance evaluations. The teacher evaluates the student's work throughout the academic period in alignment with the assignment submission schedule for the discipline. The assessment system may incorporate a mix of written and oral, group and individual formats.
Period | Type of task | Total |
---|---|---|
1 rating | Практическое задание 1 | 0-100 |
Практическое задание 2 | ||
Практическое задание 3 | ||
РК 1 | ||
2 rating | Практическое задание 4 | 0-100 |
Практическое задание 5 | ||
Практическое задание 6 | ||
РК 2 | ||
Total control | Exam | 0-100 |
The evaluating policy of learning outcomes by work type
Type of task | 90-100 | 70-89 | 50-69 | 0-49 |
---|---|---|---|---|
Excellent | Good | Satisfactory | Unsatisfactory |
Evaluation form
The student's final grade in the course is calculated on a 100 point grading scale, it includes:
- 40% of the examination result;
- 60% of current control result.
The final grade is calculated by the formula:
FG = 0,6 | MT1+MT2 | +0,4E |
2 |
Where Midterm 1, Midterm 2are digital equivalents of the grades of Midterm 1 and 2;
E is a digital equivalent of the exam grade.
Final alphabetical grade and its equivalent in points:
The letter grading system for students' academic achievements, corresponding to the numerical equivalent on a four-point scale:
Alphabetical grade | Numerical value | Points (%) | Traditional grade |
---|---|---|---|
A | 4.0 | 95-100 | Excellent |
A- | 3.67 | 90-94 | |
B+ | 3.33 | 85-89 | Good |
B | 3.0 | 80-84 | |
B- | 2.67 | 75-79 | |
C+ | 2.33 | 70-74 | |
C | 2.0 | 65-69 | Satisfactory |
C- | 1.67 | 60-64 | |
D+ | 1.33 | 55-59 | |
D | 1.0 | 50-54 | |
FX | 0.5 | 25-49 | Unsatisfactory |
F | 0 | 0-24 |
Topics of lectures
- Постановка задачи математического программиро-вания
- Задача линейного программирования
- Задачи нелинейного программирования
- Методы нелинейного программирования при наличии ограничений
- Нечеткие множества и числа
- Операции над нечеткими числами и нечеткими бинарными отношениями
- Нечеткие булевы переменные
- Основные понятия и определения в теории игр
- Простейшие игры, стратегии игроков
- Многошаговые процессы принятия решений
- Принятие решений в кооперативных играх
- Математический аппарат теории массового обслуживания
- Системы массового обслуживания (СМО) Основные понятия и определения в СМО: требования, входящий поток требований, время обслуживания
- Анализ систем массового обслуживания
- Сети массового обслуживания
Key reading
- Глобальная культура кибербезопасности : , Москва: Горячая линия -Телеком, 2018
- Основы политики безопасности критических систем информационной инфраструктуры. Курс лекций. : учеб. пособие для вузов., Москва: Горячая линия -Телеком, 2018
- Черняк В.З. Методы принятия управленческих решений : Учебник для студ. учреждений высш. проф. образования / В. З. Черняк, И. В. Довдиенко. - М.: ИЦ "Академия", 2013. - 240 с. - (Бакалавриат). - Список лит.: с. 232.
Further reading
- Орлов А.И. Теория принятия решений [Электронный ресурс]: Учебное пособие /. - М.: Изд-во «Март», 2004. -656с. // ЭБС ЕДИНОЕ ОКНО- http://www.window.edu.ru/resource/907/65907 (дата обращения: 21.08.2015).- Режим доступа: свободный
- Зуб А. Т. Принятие управленческих решений. Теория и практика [Электронный ресурс]: учеб. пособие. - М.: ИД «ФОРУМ» : ИНФРА-М, 2014. – 400 с. : ил.- (Высшее образование). // ЭБС Znanium.com. – URL: http://www. znanium.com/ (дата обращения: 17.08.2015).- Режим доступа: ограниченный по логину и паролю.