Stable Matching with Deviators and Conformists

TL;DR

This paper explores the complexity of finding stable matchings when only certain agents, called deviators, are allowed to block, revealing intractability results and identifying tractable cases in such constrained stability scenarios.

Contribution

It introduces a novel model distinguishing deviators and conformists in stable matching problems and characterizes the computational complexity of related stability questions.

Findings

Deciding the existence of a matching with no deviator blocking is NP-complete.

Polynomial-time algorithms are identified for specific cases.

Fixed-parameter tractability results are established for certain problem variants.

Abstract

In the fundamental Stable Marriage and Stable Roommates problems, there are inherent trade-offs between the size and stability of solutions. While in the former problem, a stable matching always exists and can be found efficiently using the celebrated Gale-Shapley algorithm, the existence of a stable matching is not guaranteed in the latter problem, but can be determined efficiently using Irving's algorithm. However, 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. In practice, however, not every agent is able or likely to initiate deviations caused by blocking pairs. Suppose we knew, for example, due to a set of requirements or estimates based on historical data, which agents are likely to initiate deviations - the deviators - and which are likely to comply with whatever matching they are presented with - the conformists. Can we decide efficiently whether a matching exists in which no deviator is blocking, i.e., in which no deviator has an incentive to initiate a deviation? Furthermore, can we find matchings in which only a few deviators are blocking? We characterise the computational complexity of this question in bipartite and non-bipartite preference settings. Surprisingly, these problems prove computationally intractable in strong ways: for example, unlike in the classical setting, where every agent is considered a deviator, in this extension, we prove that it is NP-complete to decide whether a matching exists where no deviator is blocking. On the positive side, we identify polynomial-time and fixed-parameter tractable cases, providing novel algorithmics for multi-agent systems where stability cannot be fully guaranteed.