Abstract Traditionally science is done using the reductionism paradigm. Artificial intelligence does not make an exception and it follows the same strategy. At the same time, network science tries to study complex systems as a whole. This Ph.D. research takes an alternative approach to the reductionism strategy, and tries to advance both fields, i.e. artificial intelligence and network science, by searching for the synergy between them, while not ignoring any other source of inspiration, e.g. neuroscience