Бакалавриат
2022/2023
Теория выбора и принятия решений
Лучший по критерию «Новизна полученных знаний»
Статус:
Курс по выбору (Прикладная математика и информатика)
Направление:
01.03.02. Прикладная математика и информатика
Кто читает:
Департамент математики
Где читается:
Факультет компьютерных наук
Когда читается:
3-й курс, 1, 2 модуль
Формат изучения:
без онлайн-курса
Охват аудитории:
для своего кампуса
Язык:
английский
Кредиты:
5
Контактные часы:
60
Course Syllabus
Abstract
This course presents an introduction to individual and social choice and decision theory. We will introduce and analyse models of individual decision making in forms of binary relations and choice functions, their rationalization by utility functions and properties of rational choice, methods of collective decision making and their properties, problem of power evaluation and theory of matchings as an example of applied problem.
Learning Objectives
- to familiarize students with the basic concepts, models and statements of the theory of choice and decision making
- to familiarize students with the power assessment in voting and in network structures
- to familiarize students with the matching theory
Expected Learning Outcomes
- students will be able to choose rational options in practical decision-making problems
- students will be able to apply principles of models construction in decision analysis
- students will be able to use choice functions and their rationalization by utility functions and binary relations
- students will be able to use social choice functions and be aware of their properties and deficies
- students will be familiar with the concept of manipulation in collective decision making
Course Contents
- Mathematical Model of the Decision Making Situation
- Utility, Preference and Choice
- Social Choice Theory
- Political Decision Making
- Polarization in parliaments: uni- and multidimensional cases
- Networks
- Assignment problem
Bibliography
Recommended Core Bibliography
- Aleskerov F., Bouyssou D., Monjardet B. ‘Utility Maximization, Choice and Preference’, Springer Verlag, Berlin, 2007
- Aleskerov, F., Meshcheryakova, N., & Shvydun, S. (2016). Centrality measures in networks based on nodes attributes, long-range interactions and group influence.
- Aleskerov, F., Meshcheryakova, N., Nikitina, A., & Shvydun, S. (2018). Key Borrowers Detection by Long-Range Interactions.
- Polarization and optimal allocation of migrants. Препринт WP7/2017/01, Aleskerov, F., 2017
- Power and preferences : an experimental approach. Препринт WP7/2010/05, Aleskerov, F., 2010
- Power distribution in the weimar reichstag in 1919-1933. Препринт WP7/2010/08, Aleskerov, F., 2010
Recommended Additional Bibliography
- Aleskerov, F., Meshcheryakova, N., & Shvydun, S. (2016). Centrality measures in networks based on nodes attributes, long-range interactions and group influence.