Statistical theory of decision making
Course: Systems and methods of decision making
Structural unit: Faculty of Computer Science and Cybernetics
Title
Statistical theory of decision making
Code
ОК.05
Module type
Обов’язкова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2024/2025
Semester/trimester when the component is delivered
1 Semester
Number of ECTS credits allocated
3
Learning outcomes
The student must know the formulation of STDM tasks, definition of utility functions, risk functions. The student must know the methods of finding optimal solutions for observations. The student must know the elements of consistent analysis and Markov optimal solutions.
Form of study
Full-time form
Prerequisites and co-requisites
The student must know: basic concepts of mathematical analysis, algebra and geometry, differential equations, operations research, control theory, decision theory.
The student must be able to solve typical problems from these courses.
Course content
Utility and risk functions. Optimal solutions for observations. Consistent solutions. Optimal rules of stopping. Optimal solutions for Markov sequences. Bellman's equation. Optimal solutions for Markov processes.
Recommended or required reading and other learning resources/tools
1. Nakonechny O.G. Optimal control and estimation in partial differential equations: A textbook. - Kyiv: VPC "Kyiv University", 2004. - 103 p.
4. French S., Insua D.R. Statistical Decision Theory. – London, Arnold, 2000.
5. Raiffa H., Schlacfer R. Applied Statistical Decision Theory. - New York, John Wiley and sons, 2000.
Planned learning activities and teaching methods
Lecture, independent study.
Assessment methods and criteria
Test, pass/fail examinations.
Language of instruction
ukrainian
Lecturers
This discipline is taught by the following teachers
Departments
The following departments are involved in teaching the above discipline