A dynamical cognitive multi-agent system for enhancing ambient intelligence scenarios

Ambient Intelligence (AmI) is born as a computer paradigm that deals with a new world where computing devices are spread everywhere in order to make wider the interaction between human beings and information technology and put together a dynamic computational-ecosystem capable of satisfying the users requirements. However, the AmI systems are more than a simple integration among computer technologies, indeed, their design can strongly depend upon psychology and social sciences aspects able to describe and analyze the human being status during the system´s decision making. Consequently, from a computational point of view, an AmI system can be considered as a distributed cognitive framework composed by a collection of intelligent entities capable of modifying their behaviours by taking into account the user´s cognitive status in a given time. This paper introduces a novel methodology of AmI systems´ design that exploits multi-agent paradigm and a novel extension of Fuzzy Cognitive Maps theory benefiting on the theory of Timed Automata in order to create a collection of dynamical intelligent agents that use cognitive computing to define actions´ patterns able to maximize environmental parameters as, for instance, user´s comfort or energy saving.