The stable marriage problem: structure and algorithms
The stable marriage problem: structure and algorithms
On-line algorithms for weighted bipartite matching and stable marriages
Theoretical Computer Science
A sublinear parallel algorithm for stable matching
Theoretical Computer Science
A fixed-point approach to stable matchings and some applications
Mathematics of Operations Research
Social Networks and Stable Matchings in the Job Market
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
Almost Stable Matchings by Truncating the Gale–Shapley Algorithm
Algorithmica - Special Issue: Matching Under Preferences; Guest Editors: David F. Manlove, Robert W. Irving and Kazuo Iwama
Contribution games in social networks
ESA'10 Proceedings of the 18th annual European conference on Algorithms: Part I
Autonomous actor positioning in wireless sensor and actor networks using stable-matching
International Journal of Parallel, Emergent and Distributed Systems - Best papers from the WWASN2009 workshop
Uncoordinated Two-Sided Matching Markets
SIAM Journal on Computing
Market sharing games applied to content distribution in ad hoc networks
IEEE Journal on Selected Areas in Communications
On finding better friends in social networks
SSS'12 Proceedings of the 14th international conference on Stabilization, Safety, and Security of Distributed Systems
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We study stable marriage and roommates problems in graphs with locality constraints. Each player is a node in a social network and has an incentive to match with other players. The value of a match is specified by an edge weight. Players explore possible matches only based on their current neighborhood. We study convergence of natural better-response dynamics that converge to locally stable matchings - matchings that allow no incentive to deviate with respect to their imposed information structure in the social network. For every starting state we construct in polynomial time a sequence of polynomially many better-response moves to a locally stable matching. However, for a large class of oblivious dynamics including random and concurrent better-response the convergence time turns out to be exponential. In contrast, convergence time becomes polynomial if we allow the players to have a small amount of random memory, even for many-to-many matchings and more general notions of neighborhood.