  The context-awareness of things that belong to IoT networks have to be
considered in a distributed computation paradigm. In the paper we suggest the
use of graph transformations and temporal logic as a formal framework for a
knowledge representation of user/inhabitant behaviors in multi-agent systems.
IoT networks are considered as graph structures. Dynamic preference models,
understood as a priority in the selecting, is also introduced. Preference
models as a result of observed behaviors base on formal logic, and they are
built on-the-fly by software agents. Software agents gather knowledge about
user preferences expressed in terms of logical specifications as well as
suggest on-the-fly future behavior basing on the logical inference process
using the semantic tableaux method. The predictive processes are result of some
new and important events in the context of IoT systems that should meet a
response. Due to the ubiquitous availability of cyber systems that interact
with physical environments, there is a great need to develop technologies that
target the whole IoT system as a context-awareness system. Formal approach
increases the trustworthy of a system. A simple yet illustrative example is
provided.
