A Method and Apparatus for Dynamic Network Configuration and Optimisation Using Artificial Life

A method for recommending configuration changes in a communications network. The method comprises maintaining (102) a plurality of machine-learning processes, wherein an individual machine-learning process operates based on a data model and decision-making rules, and the plurality of machine-learning processes operate based on a plurality of different data models and a plurality of different decision-making rules. The method also comprises obtaining (104) values of Key Performance Indicators, KPIs, from network elements of the communications network and obtaining a goal (106) defining at least one KPI value characterising wanted operation of the communications network. The method also comprises producing (108) by the plurality of machine-learning processes, based on the received values of KPIs and using the data models and decision-making rules, a plurality of individual recommendations; and producing an output recommendation (110) based on the produced individual recommendations. An apparatus realising the above method is also disclosed.