One advantage of applying control theory to our systems is that real user input will affect many parts of systems, not just those directly targeted. Progress in understanding this complexity requires algorithms, mathematics, and the relationship of contextual data to represent the interconnections between systems.
EHLAI complex network is, in part, derived from MIT researchers working on multihop radio networks . A multihop network is a ‘graph’ of interconnected elements, where nodes represent components of a system and edges represent connections or interactions between nodes.
Comparably, in the brain, nodes typically represent neural elements (e.g., neurons or brain regions), and edges represent connections between nodes (e.g., axons, information, or white matter tracts). Network control theory is a guide for the design guide to map the system from an initial state to a target state.
Mind control engineering guide: Part 1
[1] Liu, Y.-Y., Slotine, J.-J. & Barabasi, A.-L. Controllability of complex networks.