On Robust Popular Matchings with Tie-Bounded Preferences and Stable Matchings with Two-Sided Ties
By: Koustav De
Potential Business Impact:
Finds fair pairings even with tricky choices.
We are given a bipartite graph $G = \left( A \cup B, E \right)$. In the one-sided model, every $a \in A$ (often called agents) ranks its neighbours $z \in N_{a}$ strictly, and no $b \in B$ has any preference order over its neighbours $y \in N_{b}$, and vertices in $B$ abstain from casting their votes to matchings. In the two-sided model with one-sided ties, every $a \in A$ ranks its neighbours $z \in N_{a}$ strictly, and every $b \in B$ puts all of its neighbours into a single large tie, i.e., $b \in B$ prefers every $y \in N_{b}$ equally. In this two-sided model with one-sided ties, when two matchings compete in a majority election, $b \in B$ abstains from casting its vote for a matching when both the matchings saturate $b$ or both leave $b$ unsaturated; else $b$ prefers the matching where it is saturated. A popular matching $M$ is \emph{robust} if it remains popular among multiple instances. We have analysed the cases when a robust popular matching exists in the one-sided model where only one agent alters her preference order among the instances, and we have proposed a polynomial-time algorithm to decide if there exists a robust popular matching when instances differ only with respect to the preference orders of a single agent. We give a simple characterisation of popular matchings in the two-sided model with one-sided ties. We show that in the two-sided model with one-sided ties, if the input instances differ only with respect to the preference orders of a single agent, there is a polynomial-time algorithm to decide whether there exists a robust popular matching. We have been able to decide the stable matching problem in bipartite graphs $G = (A \cup B, E)$ where \textit{both} sides have weak preferences (ties allowed), with the restriction that every tie has length at most $k$.
Similar Papers
Robust Stable Matchings: Dealing with Changes in Preferences
CS and Game Theory
Finds stable pairings even when people change their minds.
On the Equivalence of the Graph-Structural and Optimization-Based Characterizations of Popular Matchings
CS and Game Theory
Finds the best pairings that everyone likes.
Persuading Stable Matching
CS and Game Theory
Helps people find best matches by shaping beliefs.