Hermann Haken, Juval Portugali

Four concepts make the title of this book: Synergetic cities which is a view on cites as complex systems from the perspective of Haken’s theory of synergetics; information, which is a view on cities as complex systems commencing from the perspective of information theory. Next come steady state and phase transition which are two central aspects of complex systems in general and of cities as complex systems. Our aim is to introduce and develop the above four notions and then to discuss their implication to three issues that stand at the core of current discourse on cities as complex systems: urban allometery (or scaling) and smart cities—both attract special attention in the discourse on cities of the last two decades, as part of the attempt to transform the study of cities into a science. The third issue, city planning, attempts to adapt the process of planning to the understanding, and reality, of cities as complex, adaptive self-organizing systems.

Book at: link.springer.com

Milena Oehlers and Benjamin Fabian

Mathematics 2021, 9(8), 895

Research on the robustness of networks, and in particular the Internet, has gained critical importance in recent decades because more and more individuals, societies and firms rely on this global network infrastructure for communication, knowledge transfer, business processes and e-commerce. In particular, modeling the structure of the Internet has inspired several novel graph metrics for assessing important topological robustness features of large complex networks. This survey provides a comparative overview of these metrics, presents their strengths and limitations for analyzing the robustness of the Internet topology, and outlines a conceptual tool set in order to facilitate their future adoption by Internet research and practice but also other areas of network science.

Read the full article at: www.mdpi.com

Urban informatics is an interdisciplinary approach to understanding, managing, and designing the city using systematic theories and methods based on new information technologies. Integrating urban science, geomatics, and informatics, urban informatics is a particularly timely way of fusing many interdisciplinary perspectives in studying city systems. This edited book aims to meet the urgent need for works that systematically introduce the principles and technologies of urban informatics. The book gathers over 40 world-leading research teams from a wide range of disciplines, who provide comprehensive reviews of the state of the art and the latest research achievements in their various areas of urban informatics. The book is organized into six parts, respectively covering the conceptual and theoretical basis of urban informatics, urban systems and applications, urban sensing, urban big data infrastructure, urban computing, and prospects for the future of urban informatics. 

Open Access Book at: link.springer.com

Stefano Nolfi

This book describes how to create robots capable to develop the behavioral and cognitive skills required to perform a task autonomously, while they interact with their environment, through evolutionary and/or learning processes. It focuses on model-free approaches with minimal human-designed intervention in which the behavior used by the robot solve its task and the way in which such behavior is produced is discovered by the adaptive process automatically, i.e. it is not specified by the experimenter.

Read the full book at: bacrobotics.com

Gianluca D’Addese, Laura Sani, Luca La Rocca, Roberto Serra, and Marco Villani

Entropy 2021, 23(4), 398;

The identification of emergent structures in complex dynamical systems is a formidable challenge. We propose a computationally efficient methodology to address such a challenge, based on modeling the state of the system as a set of random variables. Specifically, we present a sieving algorithm to navigate the huge space of all subsets of variables and compare them in terms of a simple index that can be computed without resorting to simulations. We obtain such a simple index by studying the asymptotic distribution of an information-theoretic measure of coordination among variables, when there is no coordination at all, which allows us to fairly compare subsets of variables having different cardinalities. We show that increasing the number of observations allows the identification of larger and larger subsets. As an example of relevant application, we make use of a paradigmatic case regarding the identification of groups in autocatalytic sets of reactions, a chemical situation related to the origin of life problem.

Read the full article at: www.mdpi.com