 Situations in which a member of a population \(P\) is willing to engage in a certain course of action provided that a large enough portion of \(P\) engages in some appropriate behavior are typical problems of collective action. Consider the case of an agent who is debating whether to join a revolt. Her decision to join or not to join will depend on the number of other agents whom she expects to join the revolt. If such a number is too low, she will prefer not to revolt, while if the number is sufficiently large, she will prefer to revolt. Michael Chwe proposes a model where such a situation is modeled game-theoretically. Players’ knowledge about other players’ intentions depends on a social network in which players are located. The individual ‘thresholds’ for each player (the number of other agents that are needed for that specific player to revolt) are only known by the immediate neighbors in the network. Besides the intrinsic value of the results obtained by Chwe’s analysis regarding the subject of collective action, his model also provides insights about both the relation between social networks and common knowledge and about the role of common knowledge in collective action. For example, in some situations, first-order knowledge of other agents’ personal thresholds is not sufficient to motivate an agent to take action, whereas higher-order knowledge or, in the limit, common knowledge is.