Courses Master Display 2016-2017

Course Description To PDF
Course title Game Theory and Optimisation
Course code EBC4188
ECTS credits 6,5
Assessement Whole/Half Grades
Period
Period Start End Mon Tue Wed Thu Fri
1 5-9-2016 28-10-2016 X X
Level Advanced
Coordinator Dries Vermeulen, Mathias Staudigl
For more information: d.vermeulen@maastrichtuniversity.nl; m.staudigl@maastrichtuniversity.nl
Language of instruction English
Goals
This course provides a comprehensive overview of optimization techniques such as linear and integer programming, and non-linear programming, with applications in game theory and economics. Students learn optimization techniques from mathematics and operations research, and how to apply them in models from game theory and economic theory.
Description
Topics in optimization include duality theorems in LP, branch and bound and cutting plane algorithms in IP, and Kuhn-Tucker conditions for NLP.

Topics in game theory and economics include computation of Nash equilibrium and refinements, selfish routing in networks and the price of anarchy, and non-emptiness of the core.
Literature
The course will be based on chapters from standard textbooks plus additional readers.

Literature :
Hans Peters : Game Theory : A Multi-Leveled Approach, Springer-Verlag.
David Luenberger and Yinyu Ye : Linear and Nonlinear Programming.
Stephen Boyd and Lieven Vandenberghe : Convex optimization. Cambridge University Press.

Recommended literature for background reading :
Christos H. Papadimitriou and Kenneth Steiglitz : Combinatorial Optimization: Algorithms and Complexity.
Laurence A. Wolsey and George L. Nemhauser : Integer and Combinatorial Optimization, John Wiley & Sons.
Sebastian Bubeck (2015) : Algorithms and complexity. Foundations and trends in machine learning 8 (231-358).
Prerequisites
Only Master students can take this course. Exchange students need to have obtained a BSc degree in Economics, International Business, Econometrics, or a related topic. Familiarity with the basic concepts of optimization and linear programming will be helpful. A solid basis in mathematics and calculus is also recommendable.
Teaching methods PBL / Lecture
Assessment methods Written Exam
Evaluation in previous academic year For the complete evaluation of this course please click "here"
This course belongs to the following programmes / specialisations
Master Business Research Track OR Track Operation Research Compulsory Courses
Master Economic and Financial Research Track Econometrics Electives
Master Economic and Financial Research Track Econometrics Track Econometrics Core Courses
Master Economic and Financial Research Electives
Master Econometrics and OR Actuarial Science
Master Econometrics and OR Econometrics
Master Econometrics and OR Mathematical Economics
Master Econometrics and OR Operations Research