  The research community has considered in the past the application of
Artificial Intelligence (AI) techniques to control and operate networks. A
notable example is the Knowledge Plane proposed by D.Clark et al. However, such
techniques have not been extensively prototyped or deployed in the field yet.
In this paper, we explore the reasons for the lack of adoption and posit that
the rise of two recent paradigms: Software-Defined Networking (SDN) and Network
Analytics (NA), will facilitate the adoption of AI techniques in the context of
network operation and control. We describe a new paradigm that accommodates and
exploits SDN, NA and AI, and provide use cases that illustrate its
applicability and benefits. We also present simple experimental results that
support its feasibility. We refer to this new paradigm as Knowledge-Defined
Networking (KDN).
