Maximizing Social Welfare in Score-Based Social Distance Games

Social distance games have been extensively studied as a coalition formation model where the utilities of agents in each were captured using utility function u that took into account distances given social network. In this paper, we consider non-normalized score-based definition u_v depends on generic scoring vector v, which may be customized to match specifics individual application scenario. As our main technical contribution, establish tractability computing welfare-maximizing partitioning coalitions tree-like networks, for every u_v. We provide more efficient algorithms when dealing with specific choices or simpler and also extend all these results are Nash stable individually rational. view further strong indication usefulness proposed function: even very simple problem remains open originally considered canonical u.