Matthias Oberlechner

E-Mail: matthias.oberlechner@tum.de
Phone: +49 (0) 89 289 - 17532

Office: Room 01.10.054
Boltzmannstr. 3
85748 Munich, Germany

Hours: by arrangement


Short Bio

I'm a Ph.D. student at the DSS chair supervised by Prof. Bichler. My research focuses on the computation of equilibrium strategies in incomplete information games using methods from convex optimization.

Education

  • since 09/2020.   Ph.D. Student, Department of Computer Science, TUM (Munich, Germany)
  • 2017 - 2020:      M.Sc. Mathematics, TUM (Munich, Germany)
  • 2013 - 2017:      B.Sc. Mathematics, TUM (Munich, Germany)

Other Experiences

  • Program Associate supported by the Alfred P. Sloan Foundation in the program Mathematics and Computer Science of Market and Mechanism Design at SLMath
    Berkeley, USA, 08/2023 - 12/2023
  • Associated Member of the DFG Research Training Group AdONE at TUM
    Munich, Germany, since 11/2020
  • Erasmus Student at Uppsala University
    Uppsala, Sweden, 08/2018 - 01/2019

 


Publications

Working Paper

  • Low Revenue in Display Ad Auctions: Algorithmic Collusion vs. Non-Quasilinear Preferences
    Martin Bichler, Alok Gupta, Laura Mathews, Matthias Oberlechner
    Preprint, 2023. [ arXiv ]
     
  • On the Convergence of Learning Algorithms in Bayesian Auction Games
    Martin Bichler, Stephan B. Lunowa, Matthias Oberlechner, Fabian R. Pieroth, Barabara Wohlmut
    Preprint, 2023. [ arXiv ]

Journal Publications

  • Computing Bayes Nash Equilibrium Strategies in Auction Games via Simultaneous Online Dual Averaging
    Martin Bichler, Maximilian Fichtl, Matthias Oberlechner
    Operations Research, 2023, Forthcoming.
     
  • Learning equilibrium in bilateral bargaining games
    Martin Bichler, Nils Kohring, Matthias Oberlechner, Fabian R. Pieroth.
    In European Journal of Operational Research, 2023 [ link ]

Conference Proceedings

  • Computing Bayes Nash Equilibrium Strategies in Auction Games via Simultaneous Online Dual Averaging
    Martin Bichler, Maximilian Fichtl, Matthias Oberlechner
    24th ACM Conference on Economics and Computation (ACM-EC), 2023. [ link | arXiv ]

Peer-Reviewed Workshop Paper

  • Computing Bayes Nash Equilibrium Strategies in Crowdsourcing Contests
    Martin Bichler, Markus Ewert, Matthias Oberlechner.
    In 32nd Workshop on Information Technologies and Systems (WITS-22), Copenhagen, Denmark.
     
  • Computing Distributional Bayes Nash Equilibria in Auction Games via Gradient Dynamics
    Martin Bichler, Maximilian Fichtl, Matthias Oberlechner
    In Workshop on Reinforcement Learning in Games (AAAI-22, Online). [ venue | pdf ]
    Previous Version in Workshop on Learning in Presence of Strategic Behavior (NeurIPS21, Online). [ venue ]

Teaching

Classes

  • Operations Research (IN0024)
    Teaching Assistant: SS21, SS22, SS23
     
  • Auction Theory and Market Design (IN2211)
    Teaching Assistant: WS21/22, WS22/23

Supervised Theses

  • Numerical Experiments for Equilibrium Learning with Bandit-Feedback in Contests
    Thesis, Master - Informatics
  • Equilibrium Learning in Bertrand and Cournot Competition
    Interdisciplinary Project (IDP), Master - Informatics, 2023
  • Development of a DGS Auction Problem Generator
    Thesis, Bachelor - Information Systems, 2023
  • Application-oriented Analysis of Inventory Management in the Context of Strategic Portfolio Planning in the Automotive Sector Using Operations Research
    Thesis, Bachelor - Information Systems, 2023
  • Learning Discrete Equilibrium Strategies in Auction Games
    Thesis, Master Robotics, Cognition, Intelligence, 2022
  • Visualisation of different Learning Algorithms in Matrix Games
    Thesis, Bachelor - Information Systems, 2022
  • Multiplicative Weights Update in Congestion Games
    Thesis, Bachelor Information Systems, 2022
  • Solving the CVRPTW: Quantum Annealing vs. Exact Optimization
    Thesis, Master - Mathematics, 2022
  • Visualization of Different Equilibrium Concepts in Matrix Games
    Thesis, Bachelor Information Systems, 2022
  • A Comparison of No-External-Regret and No-Internal-Regret Learning Algorithmis in Matrix Games
    Thesis, Bachelor - Informatics, 2022
  • No-Regret Learning in Finite Games
    Thesis, Bachelor - Information Systems, 2022
  • Stable Marriage Problem: Fair Algorithms and Applications
    Thesis, Bachelor - Information Systems, 2021

For available theses topics, check out this page.