Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
Please read the published information on the individual courses carefully.

851-0585-37L  Social Modelling, Agent-Based Simulation and Collective Intelligence

SemesterSpring Semester 2016
LecturersD. Helbing, O. C. Rouly
Periodicityyearly recurring course
Language of instructionEnglish
CommentThis course is thought be primarily for PhD students with quantitative skills and interests in modeling and computer simulations.
Particularly suitable for students of D-INFK, D-ITET, D-MAVT, D-MTEC, D-PHYS

AbstractFormal models of societies greatly improved our understanding of social processes, the conditions under which they have negative outcomes, and the design of mechanisms that hamper unfavorable dynamics. In each course session, a societal problem (e.g. residential segregation, crowd disasters, economic bubbles) is discussed and students learn how to develop mechanisms that help prevent the problem.
ObjectiveThe course has three aims. First, students will be introduced to key formal models of social processes. Second, students learn how to analyze formal models in order to derive predictions about the conditions under which societal problems emerge. Third, students learn to use formal modeling to develop mechanisms that hamper problems. The course will consist of two parts. Part I introduces students to the most important formal models of social processes. Each session will focus on one particular societal problem, introducing existing models, their predictions about the conditions under which the problem emerges, and potential interventions. In Part II students will work on small projects, either developing and analyzing a new model or extending existing formal models.