Short Bio

After receiving my M.Sc. in Mathematics at the Technical University of Munich, I started my my Ph.D. in the computer science department under the supervision of Martin Bichler. In my research, I investigate learning dynamics in multi-agent systems with application to economic settings such as auctions and contests. In particular, I am interested in the underlying structures that allow simple learning algorithms to reach the equilibrium strategies in these games. In most of my projects I rely on methods from online convex optimization and numerical simulations.

Education

• Ph.D. Student in the Department of Computer Science at TUM
  Munich, Germany, since 09/2020
• M.Sc. Mathematics at TUM
  Munich, Germany, 04/2017 - 06/2020
• B.Sc. Mathematics at TUM
  Munich, Germany, 10/2013 - 01/2017

Other Experiences

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

 

Publications

Working Paper

• Online Optimization Algorithms in Repeated Price Competition: Equilibrium Learning and Algorithmic Collusion
  Martin Bichler, Julius Durmann,  Matthias Oberlechner
  Working Paper, 2024 [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 [ DOI | arXiv]
   
• Learning equilibrium in bilateral bargaining games
  Martin Bichler, Nils Kohring, Matthias Oberlechner, Fabian R. Pieroth
  European Journal of Operational Research, 2023 [ DOI ]

Conference Papers

• On the Convergence of Learning Algorithms in Bayesian Auction Games
  Martin Bichler, Stephan B. Lunowa, Matthias Oberlechner, Fabian R. Pieroth, Barabara Wohlmuth
  Accepted at the 39th Annual AAAI Conference on Artificial Intelligence (AAAI-25), 2025, Philadelphia (USA) [ arXiv ]
   
• Low Revenue in Display Ad Auctions: Algorithmic Collusion vs. Non-Quasilinear Preferences
  Martin Bichler, Alok Gupta, Laura Mathews, Matthias Oberlechner
  Conference on Information Systems and Technology (CIST), 2024, Seattle (USA). [ arXiv ]
  Presented at International Conference on Operations Research 2024 (OR2024), 2024, Munich (Germany).
  Previous version presented at Ninth Marketplace Innovation Workshop (MIW), 2024, Online.
   
• 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, London (UK). [ DOI | arXiv ]

Workshop Papers

• Computing Bayes Nash Equilibrium Strategies in Crowdsourcing Contests
  Martin Bichler, Markus Ewert, Matthias Oberlechner 
  In 32nd Workshop on Information Technologies and Systems (WITS-22), 2022, 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), 2022, Online. [ venue | pdf ]
  Previous version in Workshop on Learning in Presence of Strategic Behavior (NeurIPS21), 2021, Online.

Teaching

Classes

• Operations Research (IN0024)
  Teaching Assistant: SS21, SS22, SS23, SS24
   
• Auction Theory and Market Design (IN2211)
  Teaching Assistant: WS21/22, WS22/23

Supervised Theses

• Learning Bayes-Nash Equilibrium Strategies in Auctions using Discontinuous Neural Networks
  Thesis, Bachelor - Information Systems, 2024
• Analyzing the Potentialness of Random Games using the Hodge Decomposition
  Thesis, Bachelor - Informatics, 2024
• Numerical Methods for Variational Inequalities and Application to Equilibrium Learning in Game Theory
  Thesis, Master - Mathematics in Data Science, 2024
• Learning in Continuous Games with Bandit Feedback
  Thesis, Bachelor - Information Systems, 2024
• Numerical Experiments for Equilibrium Learning with Bandit-Feedback in Contests
  Thesis, Master - Informatics, 2023
• 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.