A Theoretical Framework for modeling interactions in Collective-Adaptive Systems

Collective adaptive systems are new emerging computational systems consisting of a large number of interacting components and featuring complex behaviour. These systems are usually distributed, heterogeneous, decentralised and interdependent, and are operating in dynamic and possibly unpredictable environments. Finding ways to understand and design these systems and, most of all, to model the interactions of their components, is a difficult but important endeavour. In this talk I present a language-based approach to model the interactions of this class of systems by relying on attribute-based communication; a paradigm that permits a group of partners to communicate by considering their run-time properties and capabilities. I will conclude the talk by giving insights on possible candidate approaches for enabling (compositional verification) of such systems.