Social Self Organization

What are the principles that keep our society together? This question is even more difficult to answer than the long-standing question, what are the forces that keep our world together. However, the social challenges of humanity in the 21st century ranging from the financial crises to the impacts of globalization, require us to make fast progress in our understanding of how society works, and how our future can be managed in a resilient and sustainable way. This book can present only a few very first steps towards this ambitious goal. However, based on simple models of social interactions, one can already gain some surprising insights into the social, ``macro-level'' outcomes and dynamics that is implied by individual, ``micro-level'' interactions. Depending on the nature of these interactions, they may imply the spontaneous formation of social conventions or the birth of social cooperation, but also their sudden breakdown. This can end in deadly crowd disasters or tragedies of the commons (such as financial crises or environmental destruction). Furthermore, we demonstrate that classical modeling approaches (such as representative agent models) do not provide a sufficient understanding of the self-organization in social systems resulting from individual interactions. The consideration of randomness, spatial or network interdependencies, and nonlinear feedback effects turns out to be crucial to get fundamental insights into how social patterns and dynamics emerge. Given the explanation of sometimes counter-intuitive phenomena resulting from these features and their combination, our evolutionary modeling approach appears to be powerful and insightful. The chapters of this book range from a discussion of the modeling strategy for socio-economic systems over experimental issues up the right way of doing agent-based modeling. We furthermore discuss applications ranging from pedestrian and crowd dynamics over opinion formation, coordination, and cooperation up to conflict, and also address the response to information, issues of systemic risks in society and economics, and new approaches to manage complexity in socio-economic systems. Selected parts of this book had been previously published in peer reviewed journals.

Self-organization of systems belonging to quite different discipl ines has been a central topic of synergetics since its beginning. I am therefore particularly plea sed that Hans Ulrich and Gilbert Probst have not only undertaken to organize an interdisciplinary meeting on Self-Organization and Management of Social Systems, but have also edited these articles written by leading scientists after and based upon that symposium. While the previous volumes of the Springer Series in Synergetics were mainly de voted to physical, chemical and biological systems, with only the book by W. Weidlich and G. Haag deal i ng with "Quant i tat i ve Soc i 01 ogy" (Spri nger Ser. Syn., Vo 1. 14), the present volume opens a new perspective. As the reader will notice, the multitude of facets of self-organization is well reflected by various authors belonging to different discipl ines and representing different schools of thought. When such a wide scope of fields - ranging from phy sics to sociology - is covered, it is not surprising that the existence of a "hiatus" between sociology and the natural sciences was felt by some participants.

This te×t presents a collection of Charles Horton Cooley's work, a contribution to the history of ideas - especially to the origin of modern sociological theory - but also to the late-1990s public debate on civil society, community, and democracy.

A proposal that the basic mental models used to structure social interaction result from self-organization in brain activity. In The Self-Organizing Social Mind, John Bolender proposes a new explanation for the forms of social relations. He argues that the core of social-relational cognition exhibits beauty—in the physicist's sense of the word, associated with symmetry. Bolender describes a fundamental set of patterns in interpersonal cognition, which account for the resulting structures of social life in terms of their symmetries and the breaking of those symmetries. He further describes the symmetries of the four fundamental social relations as ordered in a nested series akin to what one finds in the formation of a snowflake or spiral galaxy. Symmetry breaking organizes the neural activity generating the cognitive models that structure our social relationships. Bolender's primary claim is that there exists a social pattern generator analogous to the central pattern generators associated with locomotion in many animal species. Spontaneous symmetry breaking structures the activity of the social pattern generator just as it does in central pattern generators. Bolender's hypothesis that relational cognition results from self-organization is entirely novel, distinct from other theories that describe sociality in terms of evolution or environment. It presents a picture of social-relational cognition as resembling something inorganic. In doing so it reveals deep connections among cognition, biology, and the inorganic world. One can go too far, he acknowledges, in taking a solely dynamical view of the mind; the mind's innate functional complexity must be due to natural selection. But this does not mean that every simple mental feature is the result of natural selection. By noting a descending symmetry subgroup chain at the core of relational cognition, Bolender takes the first step in an important investigation. Bradford Books imprint

Leading theoreticians and researchers present current thinking about the role played by group memberships in people's sense of who they are and what they are worth. The chapters build on the assumption, developed out of social identity theory, that people create a social self that both defines them and shapes their attitudes and behaviors. The authors address new developments in the theoretical frameworks through which we understand the social self, recent research on the nature of the social self, and recent findings about the influence of social context upon the development and maintenance of the social self.

The synchronized flashing of fireflies at night. The spiraling patterns of an aggregating slime mold. The anastomosing network of army-ant trails. The coordinated movements of a school of fish. Researchers are finding in such patterns--phenomena that have fascinated naturalists for centuries--a fertile new approach to understanding biological systems: the study of self-organization. This book, a primer on self-organization in biological systems for students and other enthusiasts, introduces readers to the basic concepts and tools for studying self-organization and then examines numerous examples of self-organization in the natural world. Self-organization refers to diverse pattern formation processes in the physical and biological world, from sand grains assembling into rippled dunes to cells combining to create highly structured tissues to individual insects working to create sophisticated societies. What these diverse systems hold in common is the proximate means by which they acquire order and structure. In self-organizing systems, pattern at the global level emerges solely from interactions among lower-level components. Remarkably, even very complex structures result from the iteration of surprisingly simple behaviors performed by individuals relying on only local information. This striking conclusion suggests important lines of inquiry: To what degree is environmental rather than individual complexity responsible for group complexity? To what extent have widely differing organisms adopted similar, convergent strategies of pattern formation? How, specifically, has natural selection determined the rules governing interactions within biological systems? Broad in scope, thorough yet accessible, this book is a self-contained introduction to self-organization and complexity in biology--a field of study at the forefront of life sciences research.

Technological systems become organized by commands from outside, as when human intentions lead to the building of structures or machines. But many nat ural systems become structured by their own internal processes: these are the self organizing systems, and the emergence of order within them is a complex phe nomenon that intrigues scientists from all disciplines. Unfortunately, complexity is ill-defined. Global explanatory constructs, such as cybernetics or general sys tems theory, which were intended to cope with complexity, produced instead a grandiosity that has now, mercifully, run its course and died. Most of us have become wary of proposals for an "integrated, systems approach" to complex matters; yet we must come to grips with complexity some how. Now is a good time to reexamine complex systems to determine whether or not various scientific specialties can discover common principles or properties in them. If they do, then a fresh, multidisciplinary attack on the difficulties would be a valid scientific task. Believing that complexity is a proper scientific issue, and that self-organizing systems are the foremost example, R. Tomovic, Z. Damjanovic, and I arranged a conference (August 26-September 1, 1979) in Dubrovnik, Yugoslavia, to address self-organizing systems. We invited 30 participants from seven countries. Included were biologists, geologists, physicists, chemists, mathematicians, bio physicists, and control engineers. Participants were asked not to bring manu scripts, but, rather, to present positions on an assigned topic. Any writing would be done after the conference, when the writers could benefit from their experi ences there.

may be complex without being able to be replaced by something »still more simple«. This became evident with the help of computer models of deterministic-recursive systems in which simple mathematical equation systems provide an extremely complex behavior. (2) Irregularity of nature is not treated as an anomaly but becomes the focus of research and thus is declared to be normal. One looks for regularity within irregularity. Non-equilibrium processes are recognized as the source of order and the search for equilibrium is replaced by the search for the dynamics of processes. (3) The classical system-environment model, according to which the adaptation of a system to its environment is controlled externally and according to which the adaptation of the system occurs in the course of a learning process, is replaced by a model of systemic closure. This closure is operational in so far as the effects produced by the system are the causes for the maintenance of systemic organization. If there is sufficient complexity, the systems perform internal self-observation and exert self-control (»Cognition« as understood by Maturana as self-perception and self-limitation, e. g. , that of a cell vis-a. -vis its environment). 22 But any information a system provides on its environment is a system-internal construct. The »reference to the other« is merely a special case of »self-reference«. The social sciences frequently have suffered from the careless way in which scientific ideas and models have been transferred.