Abstract: According to an example aspect of the present invention, there is provided an apparatus comprising at least one processing core, at least one memory including computer program code, the at least one memory and the computer program code being configured to, with the at least one processing core, cause the apparatus at least to generate, using a machine learning mechanism, a set of test instructions, wherein each one of the test instructions is configured to trigger a first network to change one or more technical characteristics of the first network, the test instructions not comprising configuration changes in nodes of the first network that are usable in changing the one or more technical characteristics of the first network, and use a block of text as input in the generation of the set of test instructions.

Abstract: An apparatus and a method are provided, by which a controller receives configuration sets from at least two network automation functions, each network automation function determining the configuration set such that it is optimal for achieving an objective of the network automation function. The controller determines an optimal network configuration based on the configuration sets received from the at least two network automation functions.

Abstract: Systems, methods, apparatuses, and computer program products for determining and/or applying optimal configurations in cognitive autonomous networks (CANs) are provided.