Cognitive automation for networking, security, IoT, and collaboration

An apparatus, comprising:

• a network interface to communicate with a computer network;
• a processor coupled to the network interface and configured to execute one or more processes;
• and
• a memory configured to store a process that is executed by the processor, the process when executed configured to:
• maintain a metamodel that describes a monitored system, the metamodel comprising a plurality of layers ranging from a sub-symbolic space to a symbolic space and a knowledge graph that represents symmetric relations between concepts in the knowledge graph;
• track updates to the metamodel over time comprising an update to a node in the plurality of layers or a relation in the knowledge graph, wherein the apparatus updates the metamodel based in part on sub-symbolic time series data generated by the monitored system;
• receive, from a learning agent, a request for the updates to a particular layer or a particular relation of the metamodel associated with a specified time period;
• and
• provide, to the learning agent, data indicative of one or more updates to the particular layer or the particular relation of the metamodel associated with the specified time period.

A tangible, non-transitory, computer-readable medium storing program instructions that cause a device to execute a process comprising:

• maintaining, by a first learning agent executed by the device, a metamodel that describes a monitored system, the metamodel comprising a plurality of layers ranging from a sub-symbolic space to a symbolic space and a knowledge graph that represents symmetric relations between concepts in the knowledge graph;
• tracking, by the first learning agent, updates to the metamodel over time comprising an update to a node in the plurality of layers or a relation in the knowledge graph, wherein the first learning agent updates the metamodel based in part on sub-symbolic time series data generated by the monitored system;
• receiving, at the first learning agent and from a second learning agent, a request for the updates to a particular layer or a particular relation of the metamodel associated with a specified time period;
• and
• providing, by the first learning agent and to the second learning agent, data indicative of one or more updates to the particular layer or the particular relation of the metamodel associated with the specified time period.