Finding Personalized Good-Enough Solutions to Unsatisfiable Stable Roommates Problems

TL;DR

This paper introduces a method for generating personalized, good-enough solutions to the stable roommates problem, especially when no perfect stable matching exists, by considering agents' preferences and social networks.

Contribution

It proposes a novel approach that incorporates agents' habitual preferences and social networks to compute personalized, acceptable matchings in unsolvable stable roommates problems.

Findings

Method effectively generates personalized matchings.

Empirical evaluations demonstrate practical usefulness.

Approach handles cases without stable solutions.

Abstract

The Stable Roommates problems are characterized by the preferences of agents over other agents as roommates. A solution is a partition of the agents into pairs that are acceptable to each other (i.e., they are in the preference lists of each other), and the matching is stable (i.e., there do not exist any two agents who prefer each other to their roommates, and thus block the matching). Motivated by real-world applications, and considering that stable roommates problems do not always have solutions, we continue our studies to compute "good-enough" matchings. In addition to the agents' habits and habitual preferences, we consider their networks of preferred friends, and introduce a method to generate personalized solutions to stable roommates problems. We illustrate the usefulness of our method with examples and empirical evaluations.