2023/2024
Игры и решения в задачах анализа данных и моделирования
Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»
Лучший по критерию «Новизна полученных знаний»
Статус:
Маго-лего
Кто читает:
Департамент математики
Когда читается:
3, 4 модуль
Онлайн-часы:
30
Охват аудитории:
для своего кампуса
Язык:
английский
Кредиты:
6
Контактные часы:
64
Course Syllabus
Abstract
The aim of the course "Games and Decisions in Data Analysis and Modeling" is to familiarize students with modern models of game theory and decision theory, their applications in modeling and analyzing socio-economic problems, as well as their use in analytical and decision support systems. The course covers fundamental topics in decision theory: individual preferences modelling using binary relations and choice functions, social choice theory, especially the theory of local voting procedures and the theory of majority rule-based solutions. Also, students will consider the problems of decision-making in the network models of participants interaction and models of strategic behavior of players, taking into account the network structure of connections. Game theory studies the strategic interaction of rational agents and plays a central role in the economics, but it is also widely used in biology, political science, military affairs, etc. In this course, we will study non-cooperative and cooperative games, as well as the mechanism design, which is the reverse task, i.e. the development of rules for the interaction of agents that leads to the desired result. Successful completion of the course contributes to the development of useful strategic thinking in life.
Learning Objectives
- familiarize students with modern models of game theory and decision theory, their applications in modeling and analyzing socio-economic problems, as well as their use in analytical and decision support systems
Expected Learning Outcomes
- Knows how to find Nash equilibtia in normal form games
- Knows the main centrality measures in networks
- Knows the main solution concepts in cooperative games
- Knows the main voting procedures and voting properties
- Knows the models of individual preferences
Course Contents
- Preference modelling
- Social choice theory
- Networks
- Basics of game theory
- Mechanism design
- Cooperative game theory
- Dynamics in games
Assessment Elements
- mid-term examThe mid-term is a written test in StartExam platform with asynchronous proctoring by Examus. The rules of the mid-term are available at https://elearning.hse.ru/en/student_steps/ The mi-term consists of several questions. In some of them students should provide a short answer, in others they have to do a matching or answer the multiple choice questions. Students are not allowed to use a mobile phone or any other devices and communicate with classmates and any other people during the mid-term.
- Home assignmentsHome assignments should be done by students individually
- Final examinationThe examination shall be held in writing (test) with the use of asynchronous proctoring on the StartExam platform. StartExam is an online platform for conducting test tasks of various levels of complexity. The link to pass the exam task will be available to the student in the RUZ. Asynchronous proctoring means that all the student's actions during the exam will be “watched” by the computer. The exam process is recorded and analyzed by artificial intelligence and a human (proctor). Please be careful and follow the instructions (https://elearning.hse.ru/en/student_steps/) clearly!
Interim Assessment
- 2023/2024 4th module0.5 * Final examination + 0.3 * Home assignments + 0.2 * mid-term exam
Bibliography
Recommended Core Bibliography
- Fuad Aleskerov, Denis Bouyssou, & Bernard Monjardet. (2007). Utility Maximization, Choice and Preference. Post-Print. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.p.hal.journl.halshs.00197186
- Maschler,Michael, Solan,Eilon, & Zamir,Shmuel. (2013). Game Theory. Cambridge University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.cup.cbooks.9781107005488
Recommended Additional Bibliography
- Aleskerov, F., Meshcheryakova, N., & Shvydun, S. (2016). Centrality measures in networks based on nodes attributes, long-range interactions and group influence.