851-0101-86L  Complex Social Systems: Modeling Agents, Learning, and Games

SemesterAutumn Semester 2023
LecturersD. N. Dailisan, D. Carpentras, D. Helbing
Periodicityyearly recurring course
Language of instructionEnglish
CommentPrerequisites: Basic programming skills, elementary probability and statistics.


851-0101-86 SComplex Social Systems: Modeling Agents, Learning, and Games Special students and auditors need a special permission from the lecturers.2 hrs
Mon16:15-18:00ML H 44 »
D. N. Dailisan, D. Carpentras, D. Helbing

Catalogue data

AbstractThis course introduces mathematical and computational models to study techno-socioeconomic systems and the process of scientific research. Students develop a significant project to tackle techno-socio-economic challenges in application domains of complex systems. They are expected to implement a model and to communicate their results through a project report and a short oral presentation.
ObjectiveSee your own field of study in a wider context (“Science in Perspective”), e.g. see the psychological, social, economic, environmental, historical, ethical,or philosophical connections and implications. Learn to think critically and out of the box. Question what you believe you know for sure. Get to know surprising, counterintuitive properties of complex (non-linearly interacting, networked, multi-component) systems. Learn about collaboration.
ContentBy the end of the course, the students should be able to better understand the literature on complex social systems, develop their own models for studying specific phenomena and report results according to the standards of the relevant scientific literature by presenting their results both numerically and graphically.

At the end of the course, the students will deliver a report, computer code and a short oral presentation. To collect credit points, students will have to actively contribute and give a circa 30 minutes presentation in the course on a subject agreed with the lecturers, after which the presentation will be discussed. The presentation will be graded.

Students are expected to implement themselves models of techno-socio-economic processes and systems, particularly agent-based models, complex networks models, decision making, group dynamics, human crowds, or game-theoretical models. Credit points are finally earned for the implementation of a mathematical or empirical model from the complexity science literature, its presentation, and documentation by a project report.
Lecture notesThe lecture slides will be presented on the course Moodle after each lecture.
LiteratureAgent-Based Modeling

Social Self-Organization

Traffic and related self-driven many-particle systems
Reviews of Modern Physics 73, 1067

An Analytical Theory of Traffic Flow (collection of papers)

Pedestrian, Crowd, and Evacuation Dynamics

The hidden geometry of complex, network-driven contagion phenomena (relevant for modeling pandemic spread)
Prerequisites / NoticeThe number of participants is limited to the size of the available computer teaching room. The source code related to the seminar thesis should be well enough documented.

Good programming skills and a good understanding of probability & statistics and calculus are expected.

Students need to present a new subject, for which they have not earned any credit points before.

Good scientific practices, in particular citation and quotation rules, must be properly complied with.

Chatham House rules apply to this course. Materials may
not be shared without previous written permission.
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesassessed
Method-specific CompetenciesAnalytical Competenciesassessed
Media and Digital Technologiesfostered
Project Managementassessed
Social CompetenciesCommunicationassessed
Cooperation and Teamworkassessed
Customer Orientationfostered
Leadership and Responsibilityassessed
Self-presentation and Social Influence assessed
Sensitivity to Diversityassessed
Personal CompetenciesAdaptability and Flexibilityassessed
Creative Thinkingassessed
Critical Thinkingassessed
Integrity and Work Ethicsassessed
Self-awareness and Self-reflection assessed
Self-direction and Self-management assessed

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits3 credits
ExaminersD. Helbing, D. Carpentras, D. N. Dailisan
Typegraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.

Learning materials

Main linkMoodle
Only public learning materials are listed.


No information on groups available.


General : Special students and auditors need a special permission from the lecturers
PlacesLimited number of places. Special selection procedure.
Waiting listuntil 10.10.2023
End of registration periodRegistration only possible until 11.09.2023

Offered in

Doctorate Humanities, Social and Political SciencesSubject SpecialisationWInformation
Science, Technology, and Policy MasterElectivesWInformation
Science in PerspectiveSociologyWInformation
Science in PerspectiveD-INFKWInformation
Science in PerspectiveD-ITETWInformation
Science in PerspectiveD-PHYSWInformation