Overcoming Information Overload with Artificial Selective Agents

We describe an approach, based on artificial forms of selective attention, for overcoming the problem of information and interruption overload of intelligent agents. Inspired on natural selective attention studies, we propose a computational model of selective attention that relies on the assumption that uncertain, surprising and motive congruent/incongruent information demands attention from an intelligent agent.