When Machine Learning Meets Complex Systems: Networks, Chaos and Nonlinear Dynamics

Machine learning is a subset of artificial intelligence and refers to methods that can 'learn' from experience. The advent of machine learning has led to the development of new algorithms/strategies for identification/control, and data analytics of complex systems, which thereby promotes applications in a variety of fields. The research presented below focuses on new machine learning algorithms/strategies /techniques as applied to complex systems as well as on the application of complex systems techniques to leverage the performance of machine learning techniques with high-efficiency. This Focus Issue provides a platform to facilitate interdisciplinary research and to share most recent developments in various related fields.

Guest Editors: Yang Tang, Jürgen Kurths, Wei Lin, Ljupco Kocarev and Ed Ott