In this work we present a study about cognitive agents that have to learn how their different information sources can be more or less trustworthy in different situations and with respect to different hydrogeological phenomena. We introduced an ad-hoc Bayesian trust model that we created and used in the simulations. We also describe the realized platform that can be manipulated in order to shape many possible scenarios. The simulations are populated by a number of agents that have three information sources about forecasts of different hydrogeological phenomena. These sources are: a) their own evaluation/forecast about the hydrogeological event; b) the information about the event communicated by an authority; c) the behavior of other agents as evidence for evaluating the dangerous level of the coming hydrogeological event. These weather forecasts are essential for the agents in order to deal with different and more or less dangerous meteorological events requiring adequate behaviors. We consider in particular in this paper some specific situations in which the authority can be more or less trustworthy and more or less able to deliver its own forecasts to the agents. The simulations will show how, on the basis of a training phase in these different situations, the agents will be able to make a rational use of their different information sources.
