In order to coordinate successfully individuals must first identify a target pattern of behaviour. In this paper we investigate the difficulty of identifying prominent outcomes in two kinds of binary action coordination problems in social networks: pure coordination games and anti-coordination games. For both environments, we determine the computational complexity of finding a strategy profile that (i) maximises welfare, (ii) maximises welfare subject to being an equilibrium, and (iii) maximises potential. We show that the complexity of these objectives can vary with the type of coordination problem. Objectives (i) and (iii) are tractable problems in pure coordination games, but for anti-coordination games are NP-hard. Objective (ii), finding the best Nash equilibrium, is NP-hard for both. Our results support the idea that environments in which actions are strategic complements facilitate successful coordination more readily than those in which actions are strategic substitutes.

翻译：为了实现成功协调，个体必须首先识别出目标行为模式。本文研究社交网络中两类二元行动协调问题中识别显著结果的难度：纯协调博弈与反协调博弈。针对这两种环境，我们确定了寻找以下策略配置的计算复杂度：(i) 最大化社会福利，(ii) 在均衡约束下最大化社会福利，以及(iii) 最大化势函数。研究表明，这些目标的复杂度会随协调问题类型而变化。目标(i)和(iii)在纯协调博弈中是可解问题，但在反协调博弈中为NP难问题。目标(ii)——寻找最优纳什均衡——在两类博弈中均为NP难问题。我们的结论支持如下观点：行动具有战略互补性的环境比行动具有战略替代性的环境更有利于促进成功协调。