Network control in artificial intelligence-defined networking

A system comprising:

• one or more processors;
• and
• one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, perform:
• receiving a deployment model selection of a software-defined-network (SDN) control service, wherein the deployment model selection comprises one of a centralized model, a decentralized model, a distributed model, or a hybrid model;
• and
• deploying the SDN control service in the deployment model selection to control a physical computer network, wherein the SDN control service uses a routing agent model,
• wherein:
• the routing agent model is trained (i) using a meta-reinforcement-learning model with variants across training environments and at least one of training traffic, training scenarios, or training data deviation sets, and (ii) with automated degradations to the training environments that comprise synthetic replications of fingerprinted security attacks;
• the routing agent model is trained in portions using respective simulated subsets of the training environments at different times;
• the respective simulated subsets of the training environments are generated using hierarchical algorithmic clustering comprising first-order hierarchical clusters and second-order hierarchical clusters;
• the first-order hierarchical clusters are generated based on first relationship strength metrics between nodes of the training environments;
• and
• the second-order hierarchical clusters are generated based on second relationship strength metrics and dependencies among the first-order hierarchical clusters.