Modelling and analysis of complex networks

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 decision-making 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 Large-scale 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 self-study)
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	Titel Auteur ISBN Prijs Networks, crowds and markets: Reasoning about a highly connected world David Easley and Jon Kleinberg, Cambridge University Press, (available freely online), 2010 978-0-521-19533-1
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. This course was registered last year with course code TBMACN-11
Opgenomen in	Opleiding Jaar Periode Type BSc Courses for Exchange Students: Engineering: Biomedical-Industrial-Mechanical - semester II a BSc Industrial Engineering and Management  (Production Technology and Logistics) 2 semester II a verplicht