  Much has been said about observability in system theory and control; however,
it has been recently that observability in complex networks has seriously
attracted the attention of researchers. This paper examines the
state-of-the-art and discusses some issues raised due to "complexity" and
"stochasticity". These unresolved issues call for a new practical methodology.
For stochastic systems, a degree of observability may be defined and the
observability problem is not a binary (i.e., yes-no) question anymore. Here, we
propose to employ a goal-seeking system to play a supervisory role in the
network. Hence, improving the degree of observability would be a valid
objective for the supervisory system. Towards this goal, the supervisor
dynamically optimizes the observation process by reconfiguring the sensory
parts in the network. A cognitive dynamic system is suggested as a proper
choice for the supervisory system. In this framework, the network itself is
viewed as the environment with which the cognitive dynamic system interacts.
Computer experiments confirm the potential of the proposed approach for
addressing some of the issues raised in networks due to complexity and
stochasticity.
