Modelling and analysis of complex networks
Dit is een conceptversie. De vakomschrijving kan nog wijzigen, bekijk deze pagina op een later moment nog eens.
Faculteit  Science and Engineering 
Jaar  2018/19 
Vakcode  TBMACN11 
Vaknaam  Modelling and analysis of complex networks 
Niveau(s)  bachelor 
Voertaal  Engels 
Periode  semester II a 
ECTS  5 
Rooster  rooster.rug.nl 
Uitgebreide vaknaam  Modelling and analysis of complex networks  
Leerdoelen  This course focuses on the modeling and analysis of different complex network systems. Upon finishing the course, students are expected to be able to: 1) Conceptualize the network models when facing data obtained from large interconnected systems; 2) Identify topological features of typical networks arising from engineering, economic or social systems; 3) Use game theory to predict the outcome of strategic interactions in organizations, markets or complex decisionmaking processes; 4) Apply control actions to large network systems; and 5) Work in teams to write a scientific report on different network dynamics. 

Omschrijving  This course introduces students to the emerging field of network science, in particular the tools for the modeling and analysis of complex networks. The main theories to be discussed are graph theory, game theory and systems theory, which are then applied to technological networks, information networks and social networks. Lectures will be based mainly on material in the textbook and there will be supplementary reading materials provided during the teaching. Lectures will follow roughly the same sequence as the material presented in the book, so it can be read in anticipation of the lectures. Three problem sets will be distributed roughly every other week, and they are meant to help the students to better grasp the course material and thus, although not obligatory, strongly encouraged to be worked out. In the second half of the semester, the students will pick project topics and finish project reports in groups. The main topics include: Mathematics of networks Graph theory Largescale structure of networks Game theory Evolutionary game theory Strategic interaction in networks Network dynamics Aggregate behavior in networks Control of complex networks 

Uren per week  
Onderwijsvorm 
Hoorcollege (LC), Opdracht (ASM), Werkcollege (T)
(lecture, tutorial, research project reports, reading and selfstudy) 

Toetsvorm 
Presentatie (P), Schriftelijk tentamen (WE), Verslag (R)
(Final exam, research report, project presentation. Final grade, see remarks.) 

Vaksoort  bachelor  
Coördinator  prof. dr. ir. M. Cao  
Docent(en)  prof. dr. ir. M. Cao  
Verplichte literatuur 


Entreevoorwaarden  The course unit assumes prior knowledge acquired from “calculus for IEM”, “linear algebra and multivariable calculus for IEM”, “algorithms” and “Statistics and stochastics”, “signals and systems for IEM and BMT.” The course unit is often followed by, or prepares students for “control engineering”, “digital and hybrid control sytstems” and “integration project”, in which the learning objectives attained are required as prior knowledge. 

Opmerkingen  The overall course grade is a weighted average of final exam (85%) and research report (15%) with additional possible bonus points for those who made excellent course presentations. The bonus points are meant for the student to apply what learned in the class to a topic that they are most interested in.  
Opgenomen in 
