The stable roommates problem with choice functions

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Abstract

The stable marriage theorem of Gale and Shapley states that for n men and n women there always exists a stable marriage scheme, that is, a set of marriages such that no man and woman exists that mutually prefer one another to their partners. The stable marriage theorem was generalized in two directions: the stable roommates problem is the "one-sided" version, where any two agents on the market can form a partnership. The generalization by Kelso and Crawford is in the "two-sided" model, but on one side of the market agents have a so-called substitutable choice function, and stability is interpreted in a natural way. It turned out that even if both sides of the market have these substitutable choice functions, there still exists a stable assignment. This latter version contains the "many-to-many" model where up to a personal quota, polygamy is allowed for both men and women in the two-sided market. The goal of this work is to solve the stable partnership problem, a generalization of the one-sided model with substitutable choice functions. We do not quite reach that: besides substitutability, we also need the increasing property for the result. Luckily, choice functions in well-known stable matching theorems comply with this property. The main result is a generalization of Irving's algorithm, that is the first efficient method to solve the stable roommates problem. This general algorithm allows us to deduce a generalization of Tan's result on characterizing the existence of a stable matching and to prove a generalization of the so-called splitting property of many-to-many stable matchings. We show that our algorithm is linear-time in some sense and indicate that for general (i.e. not necessary increasing) substitutable choice functions the stable partnership problem is NP-complete. © 2008 Springer-Verlag Berlin Heidelberg.

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APA

Fleiner, T. (2008). The stable roommates problem with choice functions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5035 LNCS, pp. 385–400). https://doi.org/10.1007/978-3-540-68891-4_27

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