Abstract: According to one or more embodiments, a node for a communication network is provided. The node includes processing circuitry configured to determine a plurality of key performance indicators, KPIs, for a plurality of cells in the communication network, predict a trend of values for each of the plurality of KPIs, the predicted trend of values indicating at least one predicted network attribute, and perform at least one action based at least in part on the at least one predicted network attribute.

Abstract: The present disclosure provides a computer-implemented method for determining whether to perform an action proposed by a model. The model is developed using a reinforcement learning process. The method comprises classifying at least one of a plurality of inputs to the model as being supportive or resistant to an action proposed by the model. The method further comprises comparing the classification of the at least one of the plurality of inputs to domain knowledge to determine whether or not the proposed action conflicts with the domain knowledge, and, in response to determining that the proposed action does not conflict with the domain knowledge, initiating the proposed action. In this context, the domain knowledge is indicative of a relationship between the proposed action and the at least one of the plurality of inputs.

Abstract: According to one or more embodiments, a node (15) for a communication network is provided. The node includes processing circuitry (98) configured to determine a plurality of key performance indicators, KPIs, for a plurality of cells in the communication network, predict a trend of values for each of the plurality of KPIs, the predicted trend of values indicating at least one predicted network attribute, and perform at least one action based at least in part on the at least one predicted network attribute.