Maximilian Fichtl

dblp:284/0954 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2023
0000-0002-9033-210XORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 2 since 2021Theory of computation · 2 · 2 since 2021
YearPublicationVenuePosition
2023 Computing Bayes Nash Equilibrium Strategies in Auction Games via Simultaneous Online Dual Averaging
abstract
Numerous games studied in microeconomic theory, such as auctions and contests, are modeled as Bayesian games with continuous type and action spaces. However, explicit solutions in the form of Bayes-Nash equilibria for such games are only known under highly specific assumptions regarding the agents' prior distributions or utility functions. Given the continuous nature of these games, existing equilibrium solvers cannot be straightforwardly applied and necessitate an additional discretization step.
Martin Bichler, Maximilian Fichtl, Matthias Oberlechner
EC2
2022 Core-Stability in Assignment Markets with Financially Constrained Buyers
abstract
We study markets where a set of indivisible items is sold to bidders with unit-demand valuations, subject to a hard budget limit. Without financial constraints and pure quasilinear bidders, this assignment model allows for a simple ascending auction format that maximizes welfare and is incentive-compatible and core-stable. Introducing budget constraints, the ascending auction requires strong additional conditions on the unit-demand preferences to maintain its properties. We show that, without these conditions, we cannot hope for an incentive-compatible and core-stable mechanism. We design an iterative algorithm that depends solely on a trivially verifiable ex-post condition and demand queries, and with appropriate decisions made by an auctioneer, always yields a welfare-maximizing and core-stable outcome. If these conditions do not hold, we cannot hope for incentive-compatibility and computing welfare-maximizing assignments and core-stable prices is hard: Even in the presence of value queries, where bidders reveal their valuations and budgets truthfully, we prove that the problem becomes NP-complete for the assignment market model. The analysis complements complexity results for markets with more complex valuations and shows that even with simple unit-demand bidders the problem becomes intractable. This raises doubts on the efficiency of simple auction designs as they are used in high-stakes markets, where budget constraints typically play a role.
Eleni Batziou, Martin Bichler, Maximilian Fichtl
EC3