2023/2024![Learning Objectives](/f/src/global/i/edu/objectives.svg)
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Компьютерное моделирование в социальных и политических науках: продвинутый уровень
Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»
Лучший по критерию «Новизна полученных знаний»
Статус:
Маго-лего
Кто читает:
Департамент социологии
Когда читается:
2 модуль
Охват аудитории:
для своего кампуса
Преподаватели:
Серова Елена Геннадьевна
Язык:
английский
Кредиты:
3
Контактные часы:
24
Course Syllabus
Abstract
To be effective, studying the complicated nature of interactions in society must be accurate. Often the results lead to solutions that lag the dynamically-changing issue they are meant to address. Computational modeling of social and political processes and its dynamics can be considered as one of the keys to detailed analysis, valuable insights and effective research. Modeling allows the creation of new intellectual data analysis which can be open, flexible and adaptive, and integrated with information systems.
This course focuses on a broad discourse of modern computational modeling paradigms and simulation systems, its applications in social and political sciences and data analysis.
Learning Objectives
- The main goal of the course is to provide participants with a broader understanding of computational modeling approaches, procedures, and methods, including its application in social and political sciences and data analysis.
Expected Learning Outcomes
- Learn from case studies and applications
- to get knowledge about the course structure and the main goal, indicative assessment methods and strategy
- be introduced to the main paradigms of modern computer modeling and to basic concepts of discrete simulation, system dynamics, agent modeling;
- get knowledge about how to use computer modeling in social science researches and to apply agent-based modeling for social data analysis;
- to work out of models of complicated systems referring to different areas of social researches, to use computer modelling as a tool of their work in practice and science.
- Learn Computational Modeling algorithms, procedures, and techniques, their types, and their usage in social and political studies.
- Learn to design computer models of systems existing in reality and analyze different scenarios of socio-economic development
- Be taught methods of how to present the results of simulation experiments.
- Get knowledge about how to use computer modeling in social and political sciences research and to apply agent-based modeling for data analysis.
- Use of a combined approach, which takes into account the macroeconomic processes
- Analyze how Computational Modeling shapes a decision maker's role, including its ethical ramifications.
Course Contents
- Course Structure and Course Introduction.
- The basics of Computational Modeling
- Computer models design and simulation experiments
- Multi-Agent based Models
- New modeling paradigms for data analysis in social and political sciences
- Review of the course
Assessment Elements
- Courseworktests/ quizzes, laboratory works/exercises, case-studies, panel discussion
- EssayAn essay is a written self-study on a topic offered by the teacher or by the participant him/herself approved by teacher. The topic for essay includes development of skills for critical thinking and written argumentation of ideas. An essay should include clear statement of a research problem; include an analysis of the problem by using concepts and analytical tools within the subject that generalize the point of view of the author. Essay structure: 1. Introduction and formulation of a research question. 2. Body of the essay and theoretical foundation of selected problem and argumentation of a research question. 3. Conclusion and argumentative summary about the research question and possibilities for further use or development
- Written ExamExam is held as a written test based on all course issues and materials. Participants have to show their knowledge or ability in a particular subject, or to obtain a qualification.
Bibliography
Recommended Core Bibliography
- Davide Secchi, Martin Neumann. Agent-Based Simulation of Organizational Behavior. New Frontiers of Social Science Research. 2016. Springer. https://proxylibrary.hse.ru:2184/search?query=organizational+behavior
- Eric Silverman. (2018). Methodological Investigations in Agent-Based Modelling: With Applications for the Social Sciences. Web server without geographic relation, Web server without geographic relation (org): Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.36B944A9
- Hiroki Sayama - Introduction to the Modeling and Analysis of Complex Systems - CCBY4_055 - Open Educational Resources: libretexts.org - 2022 - 390841 - https://ibooks.ru/bookshelf/390841/reading - iBOOKS
- Klein, D., Marx, J., & Fischbach, K. (2018). Agent-Based Modeling in Social Science, History, and Philosophy. An Introduction. Historical Social Research, 43(1), 7–27. https://doi.org/10.12759/hsr.43.2018.1.7-27
- Sterman, J. (2012). Business dynamics : systems thinking and modeling for a complex world. Slovenia, Europe: Irwin. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.6D02A33C
Recommended Additional Bibliography
- Bala BK, Arshad FM, Noh KM. System dynamics. Springer Texts in Business and Economics. 2017.
- Fisunoğlu, A. (2019). System Dynamics Modeling in International Relations. All Azimuth: A Journal of Foreign Policy & Peace, 8(2), 231–253. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=poh&AN=137302377
- Jordi Cabot, Cristina Gómez, Oscar Pastor, Maria Ribera Sancho, & Ernest Teniente. (2017). Conceptual Modeling Perspectives. Springer.
- Wilensky, U., & Rand, W. (2015). An Introduction to Agent-Based Modeling : Modeling Natural, Social, and Engineered Complex Systems with NetLogo. Cambridge, Massachusetts: The MIT Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=976350
- Боев, В. Д. Моделирование в среде AnyLogic : учебное пособие для вузов / В. Д. Боев. — Москва : Издательство Юрайт, 2023. — 298 с. — (Высшее образование). — ISBN 978-5-534-02560-6. — Текст : электронный // Образовательная платформа Юрайт [сайт]. — URL: https://urait.ru/bcode/514023 (дата обращения: 28.08.2023).