CRITICALITY ASSESSMENT VIA OPINION DYNAMICS

In this paper a framework for merging clashing information is introduced based on the Hegelsmann and Krause opinion dynamics model, which represents the social behavior of humans taking decisions together. Such a model differs from traditional consensus models, since the group of agents tends to distribute the opinions into several clusters. With respect to the original model, where the agents were influenced by the estimations of the others provided that their difference in opinion was smaller than a global parameter, in this paper a different value of reliability is associated to each piece of information. In this way it is possible to implement an assessment framework for the criticality of the situation in a critical infrastructure or homeland security scenario based on several clashing information, taking also into account the reliability of the source. The result is a framework able to suitably combine different pieces of information, each with a given reliability in order to derive the most likely value (i.e., the opinion that is reached by the greatest fraction of agents), by resorting to an analogy with human decision making dynamics. Finally the possibility to apply the framework in a distributed fashion is investigated, analyzing different complex network topologies.