[ilaksh]

See the field of AGI.

Networks on top of other networks -- about any recursive neural network could be in that category. Also there are multiple projects exploring metalearning on deep NNs where it learns the network topology, i.e. learning how to learn.

Abstraction in single domains is very commonly achieved with various types of hierarchy in NN and non-NN systems. Correlation between different domains has fewer examples simply because most AI systems do not deal with multiple domains, but they do exist.

Feedback loops are common and fundamental to AI and simpler non-AI control systems.