Cycles to compute the full set of many-to-many stable matchings
In a many-to-many matching model in which agents' preferences satisfy substitutability and the law of aggregate demand, we present an algorithm to compute the full set of stable matchings. This algorithm relies on the idea of "cycles in preferences" and generalizes the algorithm presented in Roth and Sotomayor (1990) for the one-to-one model.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Stable Blanket with Hidden Variables and Cycles
Stabilized regression aims to identify a set of predictors whose conditional relationship with a response variable remains invariant across different environments. Existing graphical characterizations of the stable blank…
Two-sided matching with firms' complementary preferences
This paper studies two-sided many-to-one matching in which firms have complementary preferences. We show that stable matchings exist under a balancedness condition that rules out a specific type of odd-length cycles form…
Vocal Bursts Valence PredictionThe All-Paths and Cycles Graph Kernel
With the recent rise in the amount of structured data available, there has been considerable interest in methods for machine learning with graphs. Many of these approaches have been kernel methods, which focus on measuri…
AllLattice operations for the stable set in substitutable matching markets via re-equilibration dynamics
We compute the lattice operations for the (pairwise) stable set in two-sided matching markets where only substitutability on agents' choice functions is imposed. To do this, we use Tarski operators defined on the lattice…
The prevalence of chaotic dynamics in games with many players
We study adaptive learning in a typical p-player game. The payoffs of the games are randomly generated and then held fixed. The strategies of the players evolve through time as the players learn. The trajectories in the …