Agent-Based Modelling for Business, Economics, Informatics and Social Science

Abstract:

Agent-based modelling is a methodology with ample applications in data-intensive fields. Its main focus is not about constructing regressive models to fit observed data. Instead it is about understanding the link between micro-level dynamics (local rules of interaction, behaviour) and (emergent) macro-properties. Therefore, it revolts around the conceptualisation and analysis of stylised - and minimalistic - models that capture specific mechanisms at work.

The course covers topics as variegated as: Product adoption, diffusion of opinions, virus diffusion (in social and computer networks), segregation in society, consensus formation (again in social and computer networks), agent behaviour in financial markets. Interestingly, the techniques described are not only valid for the specific systems under consideration, but they can be easily applied to other focal areas of interest.

The course is highly interactive. All the lectures have first a theoretical part, then, the students must develop (in small groups and always supported by the instructors) the models themselves. This allows them to gain direct experience and familiarity with the concepts taught and the techniques involved. In this participatory environment, multiple exercises and the creation of visualisations play an important role

Instructors:

Prof. Dr Claudio J. Tessone (theory and practice)
Dr Manuel S. Mariani (theory and practice)
Jian-Hong Lin (practice)

Type:
Semester course (seminar-like: highly interactive)

Target Audience:
Master students assigned to “Wahlpflichtbereich" BWL 4

Frequency:
Each spring semester

APS (ECTS):
6

Work load statement:

Part

Workload

Total Time

Course attendance

(Theory)

12 lectures à 2h
(12 sessions)

24h

Course attendance

(Practice)

12 lectures à 3h
(12 sessions)

36h

Home works

3h per session

36h

Literature study

Preparation before class

30h

Assignment

Preparation and Final Work

54h

Total

 

180h

Content:
Topics typically comprised in the course contents include (but are not limited to):

  • Diffusion of innovations and product adoption
    Innovators and imitators
    Models of epidemics (from illnesses to computer viri)
    Consensus (in social groups and computer networks)
    Imitation, herding
    Cellular automata
    Traffic and human dynamics
    Self-organised criticality
    Social Segregation
    Evolution of Culture and Languages

The complete list is in the Syllabus

Language:
English

Prerequisites:
Basic Python and/or R programming skills (or the willingness to develop this knowledge prior to the course) are a necessary requirement. Basic probability theory, linear Algebra

Suggested reading:

  • N. Gilbert. Agent-Based Models (2007, Sage Publications, London)

  • Miller, John H., and Scott E. Page. Complex adaptive systems: An introduction to computational models of social life (2009, Princeton University Press)

  • T.C. Schelling. Micromotives and Macrobehavior (1978, Norton, New York)

  • M. Granovetter. Society and Economy: Framework and Principles (2017, Harvard University Press)

Syllabus

All information on the course is available in the syllabus (PDF, 166 KB). Please carefully read it

Additional Information

Grading:
Participation, oral workshop, presentation,group work, screencasts & materials.

Dates and Location:

  • Mon, 02.03.2020    14:00 - 18:00    
    Mon, 09.03.2020    14:00 - 18:00    
    Mon, 16.03.2020    14:00 - 18:00    
    Mon, 23.03.2020    14:00 - 18:00    
    Mon, 06.04.2020    14:00 - 18:00   
    Mon, 27.04.2020    14:00 - 18:00    
    Mon, 04.05.2020    14:00 - 18:00    
    Mon, 11.05.2020    14:00 - 18:00    
    Mon, 18.05.2020    14:00 - 18:00    
    Mon, 25.05.2020    14:00 - 18:00    
    Mon, 22.06.2020    14:00 - 18:00

Location: SOE E 7 and 22.6 KO2F 109Vorlesungsverzeichnis

Further information:
Network Science

Market Research

Registration:

Join our courses and make up your mind if you want to participate. Then officially register using the “Buchungstool” at the University of Zurich.

Note:
This information in the syllabus supports the official information in the electronic university calendar (VVZ – “Vorlesungsverzeichnis”). In cases of doubt, the official information at the VVZ is valid.