Why Society Is A Complex Matter

Society is complicated. But this book argues that this does not place it beyond the reach of a science that can help to explain and perhaps even to predict social behaviour. As a system made up of many interacting agents – people, groups, institutions and governments, as well as physical and technological structures such as roads and computer networks – society can be regarded as a complex system. In recent years, scientists have made great progress in understanding how such complex systems operate, ranging from animal populations to earthquakes and weather. These systems show behaviours that cannot be predicted or intuited by focusing on the individual components, but which emerge spontaneously as a consequence of their interactions: they are said to be ‘self-organized’. Attempts to direct or manage such emergent properties generally reveal that ‘top-down’ approaches, which try to dictate a particular outcome, are ineffectual, and that what is needed instead is a ‘bottom-up’ approach that aims to guide self-organization towards desirable states. This book shows how some of these ideas from the science of complexity can be applied to the study and management of social phenomena, including traffic flow, economic markets, opinion formation and the growth and structure of cities. Building on these successes, the book argues that the complex-systems view of the social sciences has now matured sufficiently for it to be possible, desirable and perhaps essential to attempt a grander objective: to integrate these efforts into a unified scheme for studying, understanding and ultimately predicting what happens in the world we have made. Such a scheme would require the mobilization and collaboration of many different research communities, and would allow society and its interactions with the physical environment to be explored through realistic models and large-scale data collection and analysis. It should enable us to find new and effective solutions to major global problems such as conflict, disease, financial instability, environmental despoliation and poverty, while avoiding unintended policy consequences. It could give us the foresight to anticipate and ameliorate crises, and to begin tackling some of the most intractable problems of the twenty-first century.

This work aims to foster the interdisciplinary dialogue between mathematicians and socio-economic scientists. Interaction among scholars and practitioners traditionally coming from different research areas is necessary more than ever in order to better understand many real-world problems we face today. On the one hand, mathematicians need economists and social scientists to better address the methodologies they design in a more realistic way; on the other hand, economists and social scientists need to be aware of sound mathematical modelling tools in order to understand and, ultimately, solve the complex problems they encounter in their research. With this goal in mind, this work is designed to take into account a multidisciplinary approach that will encourage the transfer of knowledge, ideas, and methodology from one discipline to the other. In particular, the work has three main themes: Demystifying and unravelling complex systems; Introducing models of individual behaviours in the social and economic sciences; Modelling socio-economic sciences as complex living systems. Specific tools examined in the work include a recently developed modelling approach using stochastic game theory within the framework of statistical mechanics and progressing up to modeling Darwinian evolution. Special attention is also devoted to social network theory as a fundamental instrument for the understanding of socio-economic systems.​

Complexity and nonlinearity are prominent features in the evolution of matter, life, and human society. Even our mind seems to be governed by the nonlinear dynamics of the complex networks in our brain. This book considers complex systems in the physical and biological sciences, cognitive and computer sciences, social and economic sciences, and philosophy and history of science. An in terdisciplinary methodology is introduced to explain the emergence of order in nature and mind and in the econ omy and society by common principles. These methods are sometimes said to foreshadow the new sciences of complexity characterizing the scientific deve10pment of the 21 st century. The book critically an alyzes the successes and limits of this approach, its sys tematic foundations, and its historical and philosophical background. An epilogue discusses new standards of eth ical behavior which are demanded by the complex prob lems of nature and mind, economy and society.

This book is about dynamical, social-interactional aspects of the emergence of complexity in language, explained by linguists, cognitivists, and modelers.

Dr Tainter describes nearly two dozen cases of collapse and reviews more than 2000 years of explanations. He then develops a new and far-reaching theory.

This contributed volume highlights two areas of fundamental interest in high-performance computing: core algorithms for important kernels and computationally demanding applications. The first few chapters explore algorithms, numerical techniques, and their parallel formulations for a variety of kernels that arise in applications. The rest of the volume focuses on state-of-the-art applications from diverse domains. By structuring the volume around these two areas, it presents a comprehensive view of the application landscape for high-performance computing, while also enabling readers to develop new applications using the kernels. Readers will learn how to choose the most suitable parallel algorithms for any given application, ensuring that theory and practicality are clearly connected. Applications using these techniques are illustrated in detail, including: Computational materials science and engineering Computational cardiovascular analysis Multiscale analysis of wind turbines and turbomachinery Weather forecasting Machine learning techniques Parallel Algorithms in Computational Science and Engineering will be an ideal reference for applied mathematicians, engineers, computer scientists, and other researchers who utilize high-performance computing in their work.

Originally published in 1983, this clear-sighted study built an understanding of what human behaviour meant at the time: an understanding which can still be of practical use for those who work with people in their everyday lives today. The various influences on the individual are carefully examined, with theoretical approaches from different standpoints considered in relation to one another, from the development of the personality and behaviour patterns to the effect of family and social life, culminating in the picture of a ‘whole’, responsive person. Relationships are seen to be important, and this is reflected in the selection of material. Ford argues that it is the social worker’s role to offer guidance relating to the nature and quality of an individual’s interaction with society, and that this can be done more effectively if there is a practical understanding of how this interaction evolves. Examples of social work practice are given throughout to show how such understandings may be used.

Rethinking familiar frameworks and exploring new perspectives, this book provides a much-needed analysis of European culture, society and politics in a global context. With contributors from across the social sciences and thehumanities, this book highlights key topics and assesses the open ended question of Europe's place in a global age.