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Frederik Glitzner

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4 papers
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4

AAMAS Conference 2026 Conference Paper

Minimax and Preferential Almost-Stable Matchings

  • Frederik Glitzner
  • David Manlove

In the fundamental Stable Marriage and Stable Roommates problems, there are inherent trade-offs between the size and the stability of solutions. While the existence of desirable stable matchings can famously be determined in linear time when considering strict ordinal preferences, the computation of matchings that minimise the instability, either due to the presence of additional constraints on the size of the matching, or due to restrictive preference cycles, gives rise to a collection of infamously intractable almost-stable matching problems. To better understand and deal with individual and collective incentives in such settings, we introduce two new perspectives on these problems. The first applies a minimax principle, seeking a matching that minimises the maximum number of blocking pairs that any single agent is involved in, thus limiting individual incentives to deviate. The second requires that a given set of agents is in few blocking pairs, or even entirely free of blocking pairs, motivated by contexts where some agents are unwilling or unable to initiate deviations even in the presence of such opportunities. Surprisingly, both of these directions prove computationally intractable in strong ways: for example, it is NP-complete to decide whether a matching exists where no agent is in more than one blocking pair, even under bounded preference lists. On the positive side, we identify polynomial-time and fixed-parameter tractable cases, providing practical algorithmic tools for multi-agent systems where stability cannot be fully guaranteed, and offering new insights into the structure of almost-stable matchings.

AAMAS Conference 2026 Conference Paper

Near-Feasible Stable Matchings: Incentives and Optimality

  • Frederik Glitzner

Stable matching is a fundamental area with many practical applications. Recent work has introduced the paradigm of near-feasibility incapacitatedmatchingsettings, whereagentcapacitiesareslightly modifiedtoensuretheexistenceofdesirableoutcomes. Whileuseful when no stable matching exists or when some agents are left unmatched otherwise, it has not previously been investigated whether near-feasible stable matchings satisfy desirable properties with respect to their stability in the original instance. Furthermore, prior work leaves open the deviation incentive issues that arise when the centralised authority modifies agents’ capacities. We consider these issues in the Stable Fixtures problem model, which generalises many classical models through non-bipartite preferences and capacitated agents. We develop a formal framework combining near-feasibility and almost-stability to analyse and quantify agent incentives to adhere to computed matchings. We study the trade-offs between instability, capacity modifications, and computational complexity. Further, we show that different modification strategies significantly affect stability, but establish that minimal modifications and minimal deviation incentives are compatible and efficiently computable.

AAMAS Conference 2026 Conference Paper

Non-Bipartite Stable Matching and Beyond

  • Frederik Glitzner

Non-bipartite matching problems arise naturally in many multiagent systems, yet they face a fundamental challenge absent from classical bipartite markets: even under strict preferences, stable matchings need not exist. This non-existence requires a careful combinatorial study of preference structures, and calls for the design of advanced algorithms when aiming for alternative fairness or relaxed stability guarantees in such settings. I study the structural origins of instability in non-bipartite preference systems, develop new optimality criteria inspired by both classical social choice theory and by real-world requirements, and design efficient algorithms for the computation of matchings satisfying such criteria if possible.

AAAI Conference 2025 System Paper

MATWA: A Web Toolkit for Matching Under Preferences

  • Frederik Glitzner
  • David Manlove

Matching markets, in which agents are assigned to one another based on preferences and capacity constraints, are pervasive in various domains. This paper introduces MATWA (https://matwa.optimalmatching.com), a web application that offers the most comprehensive collection to date of algorithms for fundamental matching under preference problem classes. MATWA provides results of algorithm executions and visualisations of structural properties. It is intended to be a resource for the community of researchers, educators and practitioners, supporting experimentation, as well as aiding the understanding of matching algorithms.

v2026.09.13