Patent ID: 11956138
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
Field: Digital communication (Electrical engineering)
Classification: CPC H | IPC G  H

Claim 6:
7. A computer program product comprising one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions executable by a processor to cause the processor to perform operations comprising:
establishing a knowledge base based at least in part on sensor data received from a network, wherein the knowledge base comprises network data representative of a plurality of entities in the network and relationships among the plurality of entities in the network;
generating a predicted performance parameter for a designated entity from the plurality of entities using a graph neural network;
monitoring actual performance of the designated entity, wherein the monitoring the actual performance of the designated entity comprises receiving network data via one or more sensors coupled to the designated entity;
generating an actual performance parameter based at least in part on the network data received via the one or more sensors coupled to the designated entity;
comparing the predicted performance parameter to the actual performance parameter for the designated entity;
determining that the actual performance parameter exceeds a threshold difference from the predicted performance parameter; and
generating, responsive to determining that the actual performance parameter exceeds the threshold difference from the predicted performance parameter, an incentive program using a reinforcement learning algorithm, wherein the incentive program comprises at least one action to perform to reduce electrical power usage and at least one of a monetary incentive and a non-monetary incentive to perform the at least one action;
transmitting the incentive program to a user device of a user utilizing the designated entity; and
optimizing the incentive program generated by the reinforcement learning algorithm via an iterative optimization process,
wherein the iterative optimization process comprises determining whether the at least one action to reduce electrical power usage is performed and the actual performance parameter approaches the threshold difference, and
upon a determination that the at least one action to reduce electrical power usage is performed and the actual performance parameter approaches the threshold difference, generating a second incentive program using the reinforcement learning algorithm similar to the incentive program previously generated to transmit at a subsequent iteration.