Name
Abstract | ||
|---|---|---|
The stable marriage problem is a well-known problem of matching men to women
so that no man and woman, who are not married to each other, both prefer each
other. Such a problem has a wide variety of practical applications, ranging
from matching resident doctors to hospitals, to matching students to schools or
more generally to any two-sided market. In the classical stable marriage
problem, both men and women express a strict preference order over the members
of the other sex, in a qualitative way. Here we consider stable marriage
problems with quantitative preferences: each man (resp., woman) provides a
score for each woman (resp., man). Such problems are more expressive than the
classical stable marriage problems. Moreover, in some real-life situations it
is more natural to express scores (to model, for example, profits or costs)
rather than a qualitative preference ordering. In this context, we de?fine new
notions of stability and optimality, and we provide algorithms to find
marriages which are stable and/or optimal according to these notions. While
expressivity greatly increases by adopting quantitative preferences, we show
that in most cases the desired solutions can be found by adapting existing
algorithms for the classical stable marriage problem. |
Year | Venue | Keywords |
|---|---|---|
2010 | Clinical Orthopaedics and Related Research | stable marriage problem,artificial intelligent,profitability |
Field | DocType | Volume |
Stable roommates problem,Mathematical economics,Stable marriage problem,Computer science,Artificial intelligence,Machine learning,Expressivity | Journal | abs/1007.5 |
Citations | PageRank | References |
3 | 0.44 | 10 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maria Silvia Pini | 1 | 353 | 30.28 |
| Francesca Rossi | 2 | 2067 | 176.42 |
| Kristen Brent Venable | 3 | 351 | 37.00 |
| Toby Walsh | 4 | 4836 | 416.00 |