Network Analytics and Game Theory


Course Objective

Topics from OR and Game Theory to be studied include:
• Matching and assignment problems;
• Network design, formation and routing;
• Huge networks;
• Ranking.

Course Content

In recent years, network analysis has gained attention in decision
making in Economics, Game Theory, and Operations Research (OR). The main
aim of this course is to make students acquainted with some frontier
topics in network theory in its relation to Game Theory and OR.

In operations research, networks are primarily discussed from an
algorithmic and optimization viewpoint – how certain problems related to
networks can be efficiently solved. From mathematical economics, the
perspective is primarily game theoretic – how the maximal gains or
minimal costs can be allocated over the individual agents or decision
makers based on strategic (non-cooperative) or fair (cooperative)
principles. In this course, we will discuss networks from both
perspectives and, moreover, we will see how these two perspectives
complement each other.

At the end of the course the students should be able to model new
problem situations mathematically and adapt the methods learned to the
new situation at hand.

Teaching Methods

Lectures and tutorials: Two lectures and one tutorial per week.
Active participation in lectures and working classes is highly
recommended for the successful completion of the course.
Students need to prepare the exercises before coming to the tutorials.

Method of Assessment

Tutorial assignments and written exam.

General Information

Course Code E_EBE3_NAGT
Credits 6 EC
Period P2
Course Level 300
Language of Tuition English
Faculty School of Business and Economics
Course Coordinator dr. M.A. Estevez Fernandez
Examiner dr. M.A. Estevez Fernandez
Teaching Staff dr. N.K. Olver
dr. M.A. Estevez Fernandez

Practical Information

You cannot register for this course yourself; your faculty's education office carries out registration

Last-minute registration is available for this course.

Teaching Methods Lecture, Study Group
Target audiences

This course is also available as: