Bücher der Reihe SpringerBriefs in Complexity

In the face of growing challenges, we need modes of thinking that allow us to not only grasp complexity but also perform it. The author presents a new framework for operationalising complex thinking in a set of dimensions and properties through which it may be enacted.

This book is about improving human decision making and performance in complex, dynamic tasks.

This book deals with the science of science by applying network science methods to citation networks and uniquely presents a physics-inspired model of citation dynamics.

This book deals with artificial intelligence (AI) and its several applications. It is not an organic text that should be read from the first page onwards, but rather a collection of articles that can be read at will (or at need). The idea of this work is indeed to provide some food for thoughts on how AI is impacting few verticals (insurance and financial services), affecting horizontal and technical applications (speech recognition and blockchain), and changing organizational structures (introducing new figures or dealing with ethical issues).The structure of the chapter is very similar, so I hope the reader won't find difficulties in establishing comparisons or understanding the differences between specific problems AI is being used for. The first chapter of the book is indeed showing the potential and the achievements of new AI techniques in the speech recognition domain, touching upon the topics of bots and conversational interfaces. The second and thirds chapter tackle instead verticals that are historically data-intensive but not data-driven, i.e., the financial sector and the insurance one. The following part of the book is the more technical one (and probably the most innovative), because looks at AI and its intersection with another exponential technology, namely the blockchain. Finally, the last chapters are instead more operative, because they concern new figures to be hired regardless of the organization or the sector, and ethical and moral issues related to the creation and implementation of new type of algorithms.

Going beyond the numerical experiments of Steven Wolfram, this book argues that cellular automata must be considered complex dynamical systems in their own right, requiring appropriate analytical models in order to find precise answers and predictions in the universe of cellular automata.

This monograph demonstrates the interplay between Shannon information and semantic information in cognition. In the process of information adaptation, quantitative variations in Shannon's information entail different meanings while different meanings affect the quantity of information.

Using a system dynamics approach, this book illustrates the physics of fundamental accumulation processes (stocks and flows) across the demand and supply sectors of energy systems.

The book is about the key elements required for designing, building and controlling effective artificial swarms comprised of multiple moving physical agents.

This book covers the modelling of human behaviour in the education and labour markets, which due to their interdependency are viewed as one system. The approach of agent-based modelling is presented and compared with standard economic modelling and other simulation techniques in the context of modelling complex adaptive systems.

This book introduces and discusses the analysis of interacting many-body complex systems exhibiting spontaneous synchronization from the perspective of nonequilibrium statistical physics.

This book presents a broad, multidisciplinary review of the factors that have been shown to or might influence sharing information on social media, regardless of its veracity.

This concise monograph introduces and examines social influence from the perspective of the so-called target, rather than from the source, thus providing for the first time a bidirectional account of this pervasive social phenomenon, further bridging simple micro-level dyadic interaction rules with macro-level properties of the (social) system.

This book is a collection of reflections by thought leaders at first-mover organizations in the exploding field of "Data Science for Social Good", meant as the application of knowledge from computer science, complex systems and computational social science to challenges such as humanitarian response, public health, sustainable development. The book provides both an overview of scientific approaches to social impact ΓÇô identifying a social need, targeting an intervention, measuring impact ΓÇô and the complementary perspective of funders and philanthropies that are pushing forward this new sector. This book will appeal to students and researchers in the rapidly growing field of data science for social impact, to data scientists at companies whose data could be used to generate more public value, and to decision makers at nonprofits, foundations, and agencies that are designing their own agenda around data.

This book presents the iterative beauty of fractals and fractal functions graphically with the aid of MATLAB programming. The fractal images generated using the MATLAB codes provide visual delight and highly encourage the fractal lovers for creative thinking. The book compiles five cutting-edge research chapters, each with state-of-the art fractal illustrations. It starts with the fundamental theory for the construction of fractal sets via the deterministic iteration algorithm. Incorporating the theoretical base, fractal illustrations of elementary fractal sets are provided with the explicit MATLAB code. The book gives examples of MATLAB codes to present the fractal surfaces.This book is contributed to all the research beginners as well as the professionals on the field of fractal analysis. As it covers basic fractals like Sierpinski triangle to advanced fractal functions with explicit MATLAB code, the presented fractal illustrations hopefully benefit even the non-field readers. The book is a useful course to all the research beginners on the fractal and fractal-related fields.