In multiagent scenarios where decision-makers have to coordinate actions (e.g., minority and congestion games), previous works have shown that agents may reach coordination mostly by looking at past decisions. Not many works consider the structure behind agents' connections. When structure is indeed considered, it assumes some kind of random network with a given, fixed connectivity degree. The present paper departs from this approach mainly as follows. First, it considers network topologies based on preferential attachments (especially useful in social networks). Second, the formalism of random Boolean networks is used to allow agents to consider their acquaintances. Our results using preferential attachments and random Boolean networks show that an efficient equilibrium can be achieved, provided agents do experimentation. Also, we show that influential agents tend to consider few inputs in their Boolean functions.
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