
Fabian Raoul Pieroth
E-Mail: fabian.pieroth at tum.de
Phone: +49 (0) 89 289 - 17530
Office: Room 01.10.056
Boltzmannstr. 3
85748 Munich, Germany
Hours: by arrangement
Short Bio
I am a Ph.D. student supervised by Prof. Bichler. I design scalable algorithms and theory to learn and verify equilibria in auctions and other economic games.
Education:
- 10/2017 - 01/2021: Master in Mathematics (M. Sc.), Technical University Munich
- 10/2013 - 10/2016: Bachelor in Mathematics (B. Sc.), Ludwig-Maximilians-University Munich
Working Experience:
- 08/2018 - 05/2021: Data Science Intern, MaibornWolff
- 09/2017 - 08/2018: Data Science Intern, Horvath&Partners
- 10/2016 - 01/2017: Intern in Credit Risk and Methodology, Bayern LB
Publications
Journal Publications
Deep reinforcement learning for equilibrium computation in multi-stage auctions and contests
Fabian R. Pieroth, Nils Kohring, Martin Bichler
Management Science, 2025
Learning Equilibrium in Bilateral Bargaining Games
Martin Bichler, Nils Kohring, Matthias Oberlechner, Fabian R. Pieroth
European Journal of Operational Research (EJOR), 2022
Peer-Reviewed Conference and Workshop Papers
Algorithmic Predation: Equilibrium Analysis in Dynamic Oligopolies with Smooth Market Sharing
Fabian R. Pieroth, Ole Petersen, Martin Bichler
Accepted at Conference on Information Systems and Technology (CIST), 2025
Beyond Monotonicity: On the Convergence of Learning Algorithms in Standard Auction Games
Martin Bichler, Stephan B. Lunowa, Matthias Oberlechner, Fabian R. Pieroth, Barbara Wohlmuth
Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI), 2025
Alpha-Rank-Collections: Analyzing Expected Strategic Behavior with Uncertain Utilities
Fabian R. Pieroth, Martin Bichler
Proceedings of the 25th ACM Conference on Economics and Computation (EC), 2024
Detecting Influence Structures in Multi-Agent Reinforcement Learning
Fabian R. Pieroth, Katherine Fitch, Lenz Belzner
Proceddings of the 41st International Conference on Machine Learning (ICML), 2024
Enabling First-Order Gradient-Based Learning for Equilibrium Computation in Markets
Nils Kohring, Fabian R. Pieroth, Martin Bichler
Proceedings of the 40th International Conference on Machine Learning, PMLR 202:17327-17342, 2023.
On Learning Stable Cooperation in the Iterated Prisoner's Dilemma with Paid Incentives
Xiyue Sun, Fabian R. Pieroth, Kyrill Schmid, Martin Wirsing, Lenz Belzner
Proceedings of the 42nd IEEE International Conference on Distributed Computing Systems Workshops (ICDCSW), 2022
Selected Talks
- 39th AAAI Conference on Artificial Intelligence, Philadelphia PA USA, "Beyond Monotonicity: On the Convergence of Learning Algorithms in Standard Auction Games", 2025
- 25th ACM Conference on Economics and Computation (EC), New Haven CT USA, "$\alpha$-Rank-Collections: Analyzing Expected Strategic Behavior with Uncertain Utilities", 2024
- International Conference on Operations Research, Munich Germany, "Deep Reinforcement Learning for Equilibrium Computation in Multi-Stage Auctions and Contests", 2024
Referee Services
- Programm committee, ACM Conference on Economics & Computation (EC), 2025
- Reviewer, INFORMS Journal on Computing (JOC), 2024
- Reviewer, Mathematics of Operations Research (MOR), 2024
- Programm committee, Conference on Uncertainty in AI (UAI), 2021
Grants
- German academic exchange serivce (DAAD), International research stays for computer scientists, Sep-2023 -- Mar-2024
Teaching
For available theses topics, check out this page.
Courses
- Operations Research (SS21, SS22, SS23, SS24, SS25)
- Learning in Games Seminar (SS22, SS23, SS24)
- Seminar ITUB - "IT and Management Consulting" (WS 21/22, WS22/23, WS23/24, WS24/25)
- Auction Theory and Market Design (WS21/22, WS22/23)
Supervised Theses
- Learning to Endure - An Analysis of the War of Attrition
Bachelor - Informatics, 2025 - Reinforcement Learning for Equilibrium Computation in the Competitive Inventory Stocking Problem
Master - Informatics, 2025 - Enhanced Policy Optimization using Reasoning with Causal Reinforcement Learning
Master - Electrical Engineering, 2025 - Maximizing Information Gain to Improve Sample Complexity in Two-Player Zero-Sum Games
Bachelor - Information Systems, 2025 - Equilibrium Learning in Stackelberg Colonel Blotto Games
Master - Informatics, 2024 - Effects of Exploration and Exploitation in Sampling Strategies for Monte-Carlo Counterfactual Regret Minimization
Master - Informatics, 2023 - Dynamics of Multi-Agent Reinforcement Learning Algorithms in a Discrete Time Oligopoly Price Competition
Bachelor - Engineering Science, 2023 - Comparison of Deterministic and Distributional Reinforcement Learning Algorithms in Continous Auction Games
Bachelor - Informatics, 2023 - A Comparison Between the Use of Unlabeled and Weakly Labeled Data in Active Learning for a Text Classification Problem (collaboration with MaibornWolff)
Bachelor - Informatics, 2023 - Approximating Equilibrium Strategies in Sequential Colonel Blotto Games with Multi-Agent Reinforcement Learning
Master - Informatics, 2022 - Analyzing Learning Dynamics in Finite N-Player Normal-Form Games with Varying Degrees of Cooperation
Bachelor - Information Systems, 2022 - Imitation Learning for Robust Strategies in Multi-Agent Reinforcement Learning
Master - Informatics, 2022 - Measuring Interdependencies in Multi-Agent Reinforcement Learning Systems in the Discounted Reward Setting
Bachelor - Informatics, 2021 - Learning Dynamics in Two-sided Matching Markets
Bachelor - Information Systems, 2021