Decision-making

Course: Computer science

Structural unit: Faculty of information Technology

Title
Decision-making
Code
ВБ1.2
Module type
Вибіркова дисципліна для ОП
Educational cycle
First
Year of study when the component is delivered
2022/2023
Semester/trimester when the component is delivered
5 Semester
Number of ECTS credits allocated
5
Learning outcomes
Understand the principles of modeling organizational and technical operations; use operations research methods, solving single- and multi-criteria optimization problems of linear, integer, nonlinear, stochastic programming. Apply the technologies of "soft computing" and expert evaluation to solve practical problems in various subject areas in deterministic conditions, conditions of uncertainty, risk and in conditions of conflict. Ability to make informed decisions. Ability to system thinking, application of system analysis methodology for researching complex problems of various nature, methods of formalization and solving system problems that have conflicting goals, uncertainties and risks. Ability to use modern intelligent information technologies to create applied intelligent systems
Form of study
Prerequisites and co-requisites
Know the basics of higher mathematics (linear algebra, basics of mathematical analysis, differential equations, integral and differential calculus) and research operations To be able to perform the analysis of simple tasks to determine the input and output structure information, selection of methods and algorithms for their software processing. Have the skills to work with tools for implementing single-criteria optimization methods and algorithms, develop appropriate programs in high-level languages, in particular, packages for scientific research
Course content
During the study of the discipline, the basic concepts of the theory of decision-making are considered methods, algorithms and formal models of decision-making algorithms in conditions uncertainty, risk, multicriteria, conflict and vagueness. Generalized schemes and features of existing algorithmic decision-making strategies. The goal of the discipline is to provide students with thorough mathematical training and knowledge of theoretical, methodical and algorithmic foundations of information technologies for their use when solving applied and scientific tasks for acceptance solutions In particular, familiarization with the basic principles of construction and research decision-making models. The basic foundations of decision-making, theories are considered usefulness, expert procedures for decision-making, decision-making in conditions certainty, risk, uncertainty, conflict and data fuzziness. The application of the methodology of system analysis for the study of complex problems of various nature, methods of formalization and solving of system problems that have conflicting goals, uncertainties and risks. Apply decision-making technologies in weakly structured subject areas when creating intelligent information systems; application of modern intelligent information technologies for the creation of applied intelligent systems.
Recommended or required reading and other learning resources/tools
1. BLAS (Basic Linear Algebra Subprograms). URL: http://www.netlib.org/blas/sblat1 (Дата звернення:19.11.2018). 2. GNU Multiple Precision (GMP). URL: www.swox.com/gmp/. (Дата звернення:19.11.2018). 3. Multiple Precision Integer Library (MPI), Michael Fromberger. URL: http://thayer.dartmouth.edu/~sting/mpi/. (Дата звернення:19.11.2018). 4. Large Integer Package. URL: http://home.hetnet.nl/~ecstr/LIP.zip (Дата звернення:19.11.2018).
Planned learning activities and teaching methods
The total volume is 150 hours, including: Lectures – 28 hours. Laboratory classes – 28 hours. Individual work - 80 hours. Consultations - 14 hours.
Assessment methods and criteria
A student is not allowed to take the exam if he scored less than 36 points during the semester (less than 60% of the maximum possible number of points that the student can receive for work in the semester). If a student received less than 24 points during the exam, he is given an "unsatisfactory" grade, and the points scored are not counted. During the semester, after the completion of the corresponding modules, two are held written (modular) test papers in written form. At the same time, for definition level of achievement of learning outcomes include 1 theoretical question. A condition for obtaining a positive final grade for a discipline is the achievement of no less than 60% of the maximum possible number of points. The recommended minimum for admission to the exam is 36 points, the critical calculated minimum is 20 points. At the same time, it is mandatory to perform all laboratory work and independent work, to receive a positive evaluation from control work.
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Departments

The following departments are involved in teaching the above discipline