Locally Stable Matching with General Preferences

We study stable matching problems with locality of information and control. In our model, each player is a node in a fixed network and strives to be matched to another player. A player has a complete preference list over all other players it can be matched with. Players can match arbitrarily, and they learn about possible partners dynamically based on their current neighborhood. We consider convergence of dynamics to locally stable matchings -- states that are stable with respect to their imposed information structure in the network. In the two-sided case of stable marriage in which existence is guaranteed, we show that reachability becomes NP-hard to decide. This holds even when the network exists only among one partition of players. In contrast, if one partition has no network and players remember a previous match every round, reachability is guaranteed and random dynamics converge with probability 1. We characterize this positive result in various ways. For instance, it holds for random memory and for cache memory with the most recent partner, but not for cache memory with the best partner. Also, it is crucial which partition of the players has memory. Finally, we present a variety of results for centralized computation of locally stable matchings, e.g., computing maximum locally stable matchings in the two-sided case and deciding and characterizing existence in the general roommates case.