  Cognitive Autonomous Networks (CAN) deploys learning based Cognitive
Functions (CF) instead of conventional rule-based SON Functions (SF) as Network
Automation Functions (NAF) to increase the system autonomy. These CFs work in
parallel sharing the same resources which give rise to conflicts among them
which cannot be resolved using conventional rule based approach. Our main
target is to design a Controller which can resolve any type of conflicts among
the CFs in a dynamic way.
