Arrow Research search

Author name cluster

David Manlove

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

8 papers
1 author row

Possible papers

8

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.

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.

IJCAI Conference 2024 Conference Paper

Couples Can Be Tractable: New Algorithms and Hardness Results for the Hospitals/Residents Problem with Couples

  • Gergely Csáji
  • David Manlove
  • Iain McBride
  • James Trimble

In this paper we study the Hospitals/Residents problem with Couples (HRC), where a solution is a stable matching or a report that none exists. We present a novel polynomial-time algorithm that can find a near-feasible stable matching (adjusting the hospitals' capacities by at most 1) in an HRC instance where the couples' preferences are sub-responsive (i. e. , if one member switches to a better hospital, than the couple also improves if the new pair is also acceptable) and sub-complete (i. e. , each pair of hospitals that are individually acceptable to both members are jointly acceptable for the couple) by reducing it to an instance of the Stable Fixtures problem. We also present a polynomial-time algorithm for HRC in a sub-responsive, sub-complete instance that is a Dual Market, or where all couples are one of several possible types. Our polynomial-time solvability results greatly expand the class of known tractable instances of HRC. We complement our algorithms with several hardness results. We show that HRC with sub-responsive and sub-complete couples is NP-hard, even with other strong restrictions. We also show that HRC with a Dual Market is NP-hard under several simultaneous restrictions.

JAAMAS Journal 2024 Journal Article

Envy-freeness in 3D hedonic games

  • Michael McKay
  • Ágnes Cseh
  • David Manlove

Abstract We study the problem of fairly partitioning a set of agents into coalitions based on the agents’ additively separable preferences, which can also be viewed as a hedonic game. We study three successively weaker solution concepts, related to envy, weakly justified envy, and justified envy. In a model in which coalitions may have any size, trivial solutions exist for these concepts, which provides a strong motivation for placing restrictions on coalition size. In this paper, we require feasible coalitions to have size three. We study the existence of partitions that are envy-free, weakly justified envy-free, and justified envy-free, and the computational complexity of finding such partitions, if they exist. We impose various restrictions on the agents’ preferences and present a complete complexity classification in terms of these restrictions.

TCS Journal 2021 Journal Article

Algorithmic aspects of upper edge domination

  • Jérôme Monnot
  • Henning Fernau
  • David Manlove

We study the problem of finding a minimal edge dominating set of maximum size in a given graph G = ( V, E ), called Upper EDS. We show that this problem is not approximable within a ratio of n ε − 1 2, for any ε ∈ ( 0, 1 2 ), assuming P ≠ NP, where n = | V |. On the other hand, for graphs of minimum degree at least 2, we give an approximation algorithm with ratio 1 n, matching this lower bound. We further show that Upper EDS is APX -complete in bipartite graphs of maximum degree 4, and NP -hard in planar bipartite graphs of maximum degree 4.

AAMAS Conference 2021 Conference Paper

On Weakly and Strongly Popular Rankings

  • Sonja Kraiczy
  • Ágnes Cseh
  • David Manlove

Van Zuylen et al. [26] introduced the notion of a popular ranking in a voting context, where each voter submits a strictly-ordered list of all candidates. A popular ranking π of the candidates is at least as good as any other ranking σ in the following sense: if we compare π to σ, at least half of all voters will always weakly prefer π. Whether a voter prefers one ranking to another is calculated based on the Kendall distance. A more traditional definition of popularity—as applied to popular matchings, a well-established topic in computational social choice— is stricter, because it requires at least half of the voters who are not indifferent between π and σ to prefer π. In this paper, we derive structural and algorithmic results in both settings, also improving upon the results in [26]. We also point out connections to the famous open problem of finding a Kemeny consensus with 3 voters.

AAMAS Conference 2016 Conference Paper

Preference Elicitation in Matching Markets via Interviews: A Study of Offline Benchmarks (Extended Abstract)

  • Baharak Rastegari
  • Paul Goldberg
  • David Manlove

In this paper we study two-sided matching markets in which the participants do not fully know their preferences and need to go through some costly deliberation process in order to learn their preferences. We assume that such deliberations are carried out via interviews, thus the problem is to find a good strategy for interviews to be carried out in order to minimize their use, whilst leading to a stable matching. One way to evaluate the performance of an interview strategy is to compare it against a naı̈ve algorithm that conducts all interviews. We argue however that a more meaningful comparison would be against an optimal offline algorithm that has access to agents’ preference orderings under complete information. We show that, unless P=NP, no offline algorithm can compute the optimal interview strategy in polynomial time. If we are additionally aiming for a particular stable matching, we provide restricted settings under which efficient optimal offline algorithms exist.

IS Journal 2013 Journal Article

The Joy of Matching

  • Paul Harrenstein
  • David Manlove
  • Michael Wooldridge

Here, the authors discuss matching problems and how the Gale-Shapley algorithm solves them, while also explaining some matching techniques.

v2026.09.13