Observability of stochastic complex networks under the supervision of cognitive dynamic systems

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 any more. Here, we propose to employ a goal-seeking system to play a supervisory role in the network with the objective of improving the degree of observability. Towards this goal, the supervisor dynamically optimizes the observation process by reconfiguring the sensory parts in the network. A cognitive dynamic system (CDS) is proposed as a proper choice for the supervisory system. In this framework, the network itself is viewed as the environment with which the CDS interacts. Computer experiments confirm the potential of the proposed approach for addressing some of the issues raised in networks due to complexity and stochasticity.