The Self Organizing Economy

Written in an informal and conversational style, " The Self-Organizing Economy shows how models of self-organization, "order from stability," can be applied to economic phenomenon. This concept, which has become increasingly influential in the last few years, can explain the formation of cities and business cycles. The book includes powerful insights of conventional economic analysis and strands from many disciplines, from location theory to biology, to create a surprising new view of how the economy forms structures in space and time.

The Self-Organizing Economy In the last few years the concept of self-organizing systems—complex systems in which randomness and chaos seem spontaneously to evolve into unexpected order—has linked together researchers in many fields, from artificial intelligence to chemistry, from evolution to geology. Now leading economist Paul Krugman shows how principles that explain the growth of hurricanes and embryos can also explain the formation of cities and business cycles; how the same principles of “order from random growth” can explain the strangely simple rules that describe the sizes of earthquakes, meteorites, and metropolitan areas. Weaving together strands from many disciplines, from location theory to biology, The Self-Organizing Economy offers a surprising new view of how the economy structures itself in space and time.

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-organized criticality, the spontaneous development of systems to a critical state, is the first general theory of complex systems with a firm mathematical basis. This theory describes how many seemingly desperate aspects of the world, from stock market crashes to mass extinctions, avalanches to solar flares, all share a set of simple, easily described properties. "...a'must read'...Bak writes with such ease and lucidity, and his ideas are so intriguing...essential reading for those interested in complex systems...it will reward a sufficiently skeptical reader." -NATURE "...presents the theory (self-organized criticality) in a form easily absorbed by the non-mathematically inclined reader." -BOSTON BOOK REVIEW "I picture Bak as a kind of scientific musketeer; flamboyant, touchy, full of swagger and ready to join every fray... His book is written with panache. The style is brisk, the content stimulating. I recommend it as a bracing experience." -NEW SCIENTIST

The Self-Organizing School provides ground-breaking insights and guidance about how schools can fulfill their aspirations for quality and productivity in learning and teaching. The book describes a comprehensive decade long school design process and effort that improves teaching quality and student outcomes. The practical guidance and examples employed throughout the book are supported by one of the most extensive longitudinal studies of a school reform process, including data from over 1600 classroom observations, 12,000 student evaluations and research studies of school change, technology use, student achievement, collaboration, and teacher effectiveness.

Self-organisation, self-regulation, self-repair, and self-maintenance are promising conceptual approaches to deal with the ever increasing complexity of distributed interacting software and information handling systems. Self-organising applications are able to dynamically change their functionality and structure without direct user intervention to respond to changes in requirements and the environment. This book comprises revised and extended papers presented at the International Workshop on Engineering Self-Organising Applications, ESOA 2004, held in New York, NY, USA in July 2004 at AAMAS as well as invited papers from leading researchers. The papers are organized in topical sections on state of the art, synthesis and design methods, self-assembly and robots, stigmergy and related topics, and industrial applications.

A clear methodological and philosophical introduction to complexity theory as applied to urban and regional systems is given, together with a detailed series of modelling case studies compiled over the last couple of decades. Based on the new complex systems thinking, mathematical models are developed which attempt to simulate the evolution of towns, cities, and regions and the complicated co-evolutionary interaction there is both between and within them. The aim of these models is to help policy analysis and decision-making in urban and regional planning, energy policy, transport policy, and many other areas of service provision, infrastructure planning, and investment that are necessary for a successful society.