Available Theses Topics

If you are interested in a particular topic listed here for a Bachelor or Master thesis, please contact the corresponding person from the table below.

If you are interested in writing a thesis on another (non-listed) topic within the scope of our group or you want to participate in guided research or an interdisciplinary project, write an email to Mete Ahunbay. Please state your skills and interests and also attach a current CV and a recent grade report. First contact should be established at least one month before registration of the project in order to allow for sufficient time to settle for a suitable topic.

Optimization and Market Design (BSc or MSc thesis) Various topics Prof. Martin Bichler
Computational Social Choice and Algorithmic Game Theory Various topics (having passed "Computational Social Choice", "Algorithmic Game Theory", "Markets Algorithms Incentives and Networks" or "Economics & Computation" is required) Prof. Felix Brandt
Reinforcement Learning in Imperfect Information Markets

One of the most promising paths forward for general capable agents is based on Counterfactual Regret Minimization (CFR) [1]. Among other applications, it was used in the first super-human poker bot [2] and a recent paper by Google Deepmind where an agent is proposed that can learn to act in perfect and imperfect information games [3].

In this project, the CFR approach (and possible extensions) will be explored and applied to economic market simulations (such as sequential auctions). Based on Openspiel [4] and its CFR implementation [5], the first task would be to understand the algorithm and adapt this implantation to our new setting.

Requirements: Excellent python skills, basics of efficient code and optimization, machine learning.

Nils Kohring
Matthias Oberlechner

Simulations and analysis in shared-economy markets

The sharing economy depends on the development of the sharing platform. Different platforms (e.g., ride-hailing, freight exchange, kidney exchange, resource allocation, ... ) have different characteristics. We are committed to abstracting mathematical models from reality to simulate, analyze and provide theory. Research issues include but are not limited to matching strategies, pricing issues, and online prediction.

Requirements: advanced programming skills (e.g., Python, Matlab, at least one), mathematics, operation research

Donghao Zhu
Electricity Market Design Optimization

Electricity Market Design: Electricity market design is dynamic in its nature and has recently been exposed to fundamental changes due to the integration of renewable energy resources. We examine sustainable market designs and the underlying allocation and pricing problems as part of the Kopernikus SynErgie project

Pricing in non-convex markets: Although nonconvex markets (such as electricity markets) are widespread, finding appropriate prices is not trivial. We study different pricing approaches and associated properties.

Requirements: programming skills, operations research

Johannes Knörr
Algorithms for Computing Nash Equilibria

While the computation of Nash Equilibria in matrix games is a PPAD-complete problem, there are several algorithms that compute exact Equilibria for such games.  There are several possibilities for a thesis in this area: a literature review on existing algorithms, or an implementation of a particular algorithm applied to some specific games. Depending on the chosen topic, both bachelor and master theses would be possible.

Requirements: experience in algorithms, mathematics, (depending on the project:) good programming skills in the language of your choice

Maximilian Fichtl

Optimizing coordination groups in cooperative systems

Learning in cooperative systems suffers from the communication overhead to coordinate the agents’ actions. Existing methods reduce the communication bandwidth but still rely on all-to-all communication or heuristics. The focus of the thesis is the analysis of the effects of different groups of agents communicating on learning dynamics in cooperative multi-agent systems and on methods to learn the optimal coordination groups.

Requirements: Knowledge in Game Theory, good programming skills (pref. in Python)

Fabian Pieroth

Learning Algorithms in Games  

There is an extensive literature on algorithms used to learn equilibria in finite games. We are especially interested in algorithms based on gradient dynamics. Depending on the focus of the topic, one could implement different algorithms, compare them and apply them to different games to analyze their specific behavior. A literature review would be also possible.

Requirements: interest in algorithms, mathematical optimization (e.g. gradient descent) and game theory, programming skills (pref. in Python)
Matthias Oberlechner