Decentralized Marriage Models

Most matching algorithms are centralized in that a single agent determines how other agents are matched together. This is contrary to how humans form matches in the real world. In this work, we propose three decentralized approaches for finding matchings that are inspired by three techniques that humans use to find matches. The first is to have individuals wander a grid environment, interacting and deciding preferences over potential partners. The second uses affiliation networks where agencies recommend potential partners. The third is based on small-world social networks, where we assume that individuals probabilistically introduce their friends to one another. we introduce a heuristic algorithm that can be used in each of these environments. We also explore how this algorithm can scale to a large number of agents.