Artificial Intelligence for Managing the Complexity of the Socio-Economic Systems towards Horizon 2020 and Agenda 2030

The seeds of modern Artificial Intelligence (AI) were planted by classical philosophers who attempted to describe the process of human thinking as the mechanical manipulation of symbols. AI is an area of computer science that emphasises the creation of intelligent machines that work and react like humans. Some of the activities computers with artificial intelligence are designed for include: Speech Recognition, Learning, Planning, Problem Solving and Fuzzy Sets. In the past 15 years, Amazon, Google and others leveraged machine learning to their huge commercial advantage. In this talk, we discuss Machine learning, and Fuzzy Settings theory. Machine Learning at its most basic is the practice of using algorithms to parse data, learn from it, and then make a determination or prediction about something in the world. Fuzzy Modelling helps us to deal with the phenomena including uncertain parameters and conditions. It gives us enough tools to model a real-world system and approaches our behaviour much closer. The Fuzzy Set represent a class of objects with a continuum of grades of membership. So the above framework of consideration gives us a natural way of dealing with imprecise phenomena, when classes of objects lack precise criteria of membership for their elements. The context to be considered as scientific fertile ground concerns the management of the complexity of modern anthropic socio-economic systems (Cities, Urban areas and their socio-sustainable development)