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4.00 credits
30.0 h + 15.0 h
Q2
Teacher(s)
Language
French
Main themes
As a matter of illustration, here are possible topics:
- conflict and cooperation
- voting
- measurement of power
- social choice
- fair division
Learning outcomes
At the end of this learning unit, the student is able to : | |
| 1 | This course is an introduction to mathematical modelization in social sciences at large (economics, political science, sociology, law). It is not a course in mathematics and the prerequisite do not go beyond the basic college mathematics. Its aim is to help students to develop an analytical capacity through a systematic and rigorous use of simple concepts of game and decision theory. |
Content
At the end of this course, students will be able to
- to understand the value of formalization for the social sciences and to recognize the main tools used in this field,
- to build models of strategic situations and analyze them using cooperative and non-cooperative game theory,
- to use computer simulation of social phenomena using a programming environment (NetLogo).
- The notion of "model" in social sciences
- Basic mathematical concepts useful for social sciences: sets, truth tables, relations, matrices, functions, permutations and combinations, etc.
- Rational choice model in non-cooperative game theory: how to predict the outcome of a strategic situation involving several players?
- Models of games with coalitional structure (Shapley value): how to distribute fairly the gains from a joint effort?
- Matching models (Gale-Shapley algorithm): how to match requesters and givers?
- Models of voting games and power indices: how to measure power?
- Models of collective choice and voting procedures: how to decide collectively?
- Social science simulations: why and how to simulate our social universe?
- Models of transition between states (SIR model): how to predict the evolution of an epidemic?
- Growth models: what are linear and exponential growths?
- Statistical models: how to make simple predictions in statistics?
Teaching methods
The course is structured around lectures and practical work. Participation in sessions of practical work is required.
Evaluation methods
A written exam organized in the regular session, combining practical exercises and multiple-choice questions.
Other information
Prerequisite: None
Rating: written examination.
Support: lecture notes
Bibliography
- Bonacich, P. and Lu, P., Introduction to Mathematical Sociology, 2012, Princeton University Press
- Dehez, P. Théorie des jeux, 2017, Economica
- Gura E. and M. Maschler. Insights into Game Theory: An Alternative Mathematical Experience. Cambridge University Press, 2008.
- Lave L. and J.G. March. An introduction to models in the social sciences. University Press of America, 1993.
Faculty or entity
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Minor in Human and Social Sciences
