Automated detection of network anomalies and generation of optimized anomaly-alleviating incentives

Abstract

An embodiment establishes a knowledge base based at least in part on sensor data received from a network. The embodiment generates a predicted performance parameter for a designated entity of the network using a first machine learning algorithm. The embodiment compares the predicted performance parameter to an actual performance parameter and determines whether the actual performance parameter exceeds a threshold difference from the predicted performance parameter. The embodiment generates, responsive to determining that the threshold difference is exceeded, incentive data using a second machine learning algorithm, where the incentive data is representative of an action selected by the second machine learning algorithm using an iterative optimization process, and where the iterative optimization process comprises performing the action and determining that the actual performance parameter approaches the threshold value in response to the action.