If you are interested in a particular topic listed here for a Bachelor or Master thesis, please contact the corresponding person from the list 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 Felipe Maldonado. 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.
| Title | Focus | Contact |
|---|---|---|
| Optimization and Market Design (BSc or MSc thesis) |
various topics | |
| 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) | |
| [Reserved] Reinforcement Learning for the Scotland Yard game |
In this project, modern RL techniques will be applied to the board game of Scotland Yard for computing optimal strategies. Previous work on this finite-action imperfect information game [1] was based on Monte-Carlo tree search. In the first stages of the project, the game will be implemented as an environment within a suitable framework (e.g. using [2] or [3]), after which applicable algorithms, computation, and evaluation will be considered. Requirements: Python, Machine Learning, basic RL knowledge |
Nils Kohring |
| 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. |
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Electricity Market Design, Optimization
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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 |
| Interdependencies in Mutli-Agent Reinforcement Learning Systems |
Recent advances in Multi-Agent Reinforcement Learning, such as OpenAI-Five or AlphaStar, demonstrated that high-performing policies can be learned through complex algorithms. However, interpreting resulting policies in terms of cooperative or competitive behavior is an open problem. Study existing and novel interdependency measures ([1], [2]) and use these to tackle problems such as directing communication or exploration in complex environments ([3]). Requirements: Python, Basic knowledge in RL, Machine Learning |
Fabian Pieroth |
| Equilibrium computation in finite partial information games |
Recent advances in algorithmic game theory enabled the computation of approximated Bayesian Nash equilibria in complex settings (e.g., auctions). However, developments in this direction are still at the beginning. Therefore, we want to explore local learning methods, e.g., policy gradient, in partial information sequential games (e.g., Goofspiel, or Hanabi) for equilibrium computation. Requirements: Python, Game Theory, Basic knowledge in RL, Machine Learning |
Fabian Pieroth |
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General Information for Theses