This introductory text is devoted to exposing the underlying nature of price formation in financial markets as a predominantly sociological phenomenon that relates individual decision-making to emergent and co-evolving social and financial structures.

Two different levels of this sociological influence are considered: First, we examine how price formation results from the social dynamics of interacting individuals, where interaction occurs either through the price or by direct communication. Then the same processes are revisited and examined at the level of larger groups of individuals.

In this book, models of both levels of socio-finance are presented, and it is shown, in particular, how complexity theory provides the conceptual and methodological tools needed to understand and describe such phenomena. Accordingly, readers are first given a broad introduction to the standard economic theory of rational financial markets and will come to understand its shortcomings with the help of concrete examples. Complexity theory is then introduced in order to properly account for behavioral decision-making and match the observed market dynamics.

This book is conceived as a primer for newcomers to the field, as well as for practitioners seeking new insights into the field of complexity science applied to socio-economic systems in general, and financial markets and price formation in particular.

This book, edited and authored by a closely collaborating network of social scientists and psychologists, recasts typical research topics in these fields into the language of nonlinear, dynamic and complex systems. The aim is to provide scientists with different backgrounds - physics, applied mathematics and computer sciences - with the opportunity to apply the tools of their trade to an altogether new range of possible applications. At the same time, this book will serve as a first reference for a new generation of social scientists and psychologists wishing to familiarize themselves with the new methodology and the "thinking in complexity".

The overall aim of this book, an outcome of the European FP7 FET Open NESS project, is to contribute to the ongoing effort to put the quantitative social sciences on a proper footing for the 21st century. A key focus is economics, and its implications on policy making, where the still dominant traditional approach increasingly struggles to capture the economic realities we observe in the world today - with vested interests getting too often in the way of real advances. Insights into behavioral economics and modern computing techniques have made possible both the integration of larger information sets and the exploration of disequilibrium behavior. The domain-based chapters of this work illustrate how economic theory is the only branch of social sciences which still holds to its old paradigm of an equilibrium science - an assumption that has already been relaxed in all related fields of research in the light of recent advances in complex and dynamical systems theory and related data mining. The other chapters give various takes on policy and decision making in this context. Written in nontechnical style throughout, with a mix of tutorial and essay-like contributions, this book will benefit all researchers, scientists, professionals and practitioners interested in learning about the 'thinking in complexity' to understand how socio-economic systems really work.

The Forgotten Appeasement of 1920 examines a turning point in East European history: the summer of 1920, when Lenin's Soviet Russia decided to challenge the Versailles system and launch a military attack on the continent. The outcome of this attack might have been the occupation of all of Poland and East Central Europe, and a Red Army sweep further west. This book probes the British-Soviet negotiations and diplomatic operations behind the scenes. Professor Nowak uses hitherto unexamined documents from Russian and British archives to show how (and why) top British politicians were ready to accept a new Russian imperial control over the whole of Eastern Europe. Nowak unravels this previously untold story of that first and forgotten appeasement, stopped only by the Polish military victory over the Red Army. His excellent historical craftsmanship and new sources contribute to the book's quality, filling up a lacuna in contemporary historiography. This book will appeal to researchers of geopolitical affairs and the Great Powers, the history of Poland, and the political mentality of Western elites. It will also be of interest to university students and tutors, scholars of history and international relations and - thanks to the book's brisk and fascinating narrative - amateur historians and history aficionados.

Computational Social Psychology showcases a new approach to social psychology that enables theorists and researchers to specify social psychological processes in terms of formal rules that can be implemented and tested using the power of high speed computing technology and sophisticated software. This approach allows for previously infeasible investigations of the multi-dimensional nature of human experience as it unfolds in accordance with different temporal patterns on different timescales. In effect, the computational approach represents a rediscovery of the themes and ambitions that launched the field over a century ago. The book brings together social psychologists with varying topical interests who are taking the lead in this redirection of the field. Many present formal models that are implemented in computer simulations to test basic assumptions and investigate the emergence of higher-order properties; others develop models to fit the real-time evolution of people's inner states, overt behavior, and social interactions. Collectively, the contributions illustrate how the methods and tools of the computational approach can investigate, and transform, the diverse landscape of social psychology.

Computational Social Psychology showcases a new approach to social psychology that enables theorists and researchers to specify social psychological processes in terms of formal rules that can be implemented and tested using the power of high speed computing technology and sophisticated software. This approach allows for previously infeasible investigations of the multi-dimensional nature of human experience as it unfolds in accordance with different temporal patterns on different timescales. In effect, the computational approach represents a rediscovery of the themes and ambitions that launched the field over a century ago. The book brings together social psychologists with varying topical interests who are taking the lead in this redirection of the field. Many present formal models that are implemented in computer simulations to test basic assumptions and investigate the emergence of higher-order properties; others develop models to fit the real-time evolution of people's inner states, overt behavior, and social interactions. Collectively, the contributions illustrate how the methods and tools of the computational approach can investigate, and transform, the diverse landscape of social psychology.

A dynamical system refers to any fluctuating system in which the elements interact in complex, often non-linear ways to form coherent patterns. Many systems once thought to be chaotic are in fact dynamical systems whose interaction of elements and feedback processes are only now beginning to be understood. Hence dynamical systems is sometimes referred to as "chaos theory." This metatheory has proved useful in understanding phenomenon in meteorology, population biology, chemistry, statistical mechanics, economics, and cosmology. The book demonstrates how the dynamical system perspective can be brought to bear on social psychological research in explaining such complex phenomenon as social relations, attitudes, social cognition, and interpersonal behavior.

There is considerable uncertainty about what level of traffic loading bridges should be designed for. Codes specify notional load models, generally to represent extreme levels of normal traffic, but these are often crude and have inconsistent levels of safety for different load effects. Over the past few decades, increasing quantities of reliable truck weight data has become available and it is now possible to calculate appropriate levels of bridge traffic loading, both for specific bridges and for a road network. Bridge Traffic Loading brings together experts from all over the world to deliver not just the state-of-the-art of vertical loading, but also to provide recommendations of best-practice for all the major challenges in the field - short-span, single and multi-lane bridge loading, dynamic allowance and long-span bridges. It reviews issues that continue to be debated, such as which statistical distribution is most appropriate, whether free-flowing or congested traffic governs and dealing with future traffic growth. Specialist consultants and bridge owners should find this invaluable, as will regulators.

The overall aim of this book, an outcome of the European FP7 FET Open NESS project, is to contribute to the ongoing effort to put the quantitative social sciences on a proper footing for the 21st century. A key focus is economics, and its implications on policy making, where the still dominant traditional approach increasingly struggles to capture the economic realities we observe in the world today - with vested interests getting too often in the way of real advances. Insights into behavioral economics and modern computing techniques have made possible both the integration of larger information sets and the exploration of disequilibrium behavior. The domain-based chapters of this work illustrate how economic theory is the only branch of social sciences which still holds to its old paradigm of an equilibrium science - an assumption that has already been relaxed in all related fields of research in the light of recent advances in complex and dynamical systems theory and related data mining. The other chapters give various takes on policy and decision making in this context. Written in nontechnical style throughout, with a mix of tutorial and essay-like contributions, this book will benefit all researchers, scientists, professionals and practitioners interested in learning about the 'thinking in complexity' to understand how socio-economic systems really work.

This introductory text is devoted to exposing the underlying nature of price formation in financial markets as a predominantly sociological phenomenon that relates individual decision-making to emergent and co-evolving social and financial structures. Two different levels of this sociological influence are considered: First, we examine how price formation results from the social dynamics of interacting individuals, where interaction occurs either through the price or by direct communication. Then the same processes are revisited and examined at the level of larger groups of individuals. In this book, models of both levels of socio-finance are presented, and it is shown, in particular, how complexity theory provides the conceptual and methodological tools needed to understand and describe such phenomena. Accordingly, readers are first given a broad introduction to the standard economic theory of rational financial markets and will come to understand its shortcomings with the help of concrete examples. Complexity theory is then introduced in order to properly account for behavioral decision-making and match the observed market dynamics. This book is conceived as a primer for newcomers to the field, as well as for practitioners seeking new insights into the field of complexity science applied to socio-economic systems in general, and financial markets and price formation in particular.

Conflict is inherent in virtually every aspect of human relations, from sport to parliamentary democracy, from fashion in the arts to paradigmatic challenges in the sciences, and from economic activity to intimate relationships. Yet, it can become among the most serious social problems humans face when it loses its constructive features and becomes protracted over time with no obvious means of resolution. This book addresses the subject of intractable social conflict from a new vantage point. Here, these types of conflict represent self-organizing phenomena, emerging quite naturally from the ongoing dynamics in human interaction at any scale-from the interpersonal to the international. Using the universal language and computational framework of nonlinear dynamical systems theory in combination with recent insights from social psychology, intractable conflict is understood as a system locked in special attractor states that constrain the thoughts and actions of the parties to the conflict. The emergence and maintenance of attractors for conflict can be described by means of formal models that incorporate the results of computer simulations, experiments, field research, and archival analyses. Multi-disciplinary research reflecting these approaches provides encouraging support for the dynamical systems perspective. Importantly, this text presents new views on conflict resolution. In contrast to traditional approaches that tend to focus on basic, short-lived cause-effect relations, the dynamical perspective emphasizes the temporal patterns and potential for emergence in destructive relations. Attractor deconstruction entails restoring complexity to a conflict scenario by isolating elements or changing the feedback loops among them. The creation of a latent attractor trades on the tendency toward multi-stability in dynamical systems and entails the consolidation of incongruent (positive) elements into a coherent structure. In the bifurcation scenario, factors are identified that can change the number and types of attractors in a conflict scenario. The implementation of these strategies may hold the key to unlocking intractable conflict, creating the potential for constructive social relations.

This book, edited and authored by a closely collaborating network of social scientists and psychologists, recasts typical research topics in these fields into the language of nonlinear, dynamic and complex systems. The aim is to provide scientists with different backgrounds - physics, applied mathematics and computer sciences - with the opportunity to apply the tools of their trade to an altogether new range of possible applications. At the same time, this book will serve as a first reference for a new generation of social scientists and psychologists wishing to familiarize themselves with the new methodology and the "thinking in complexity".

Social Entrepreneurship: Theory and Practice details how social entrepreneurship can creatively solve pressing and seemingly insurmountable social problems. Theories of social change are presented to help demystify the magic of making an immense, yet durable and irreversible social impact. In-depth case studies from multiple disciplines and from around the globe document how social entrepreneurs foster bottom-up change that empowers people and societies. The authors review the specific personality traits of social entrepreneurs and introduce the new leadership model required for 21st-century development. This book is valuable to undergraduate, graduate, and post-graduate students, while remaining accessible to non-academic readers due to its clear language, illustrative case studies, and guidelines on how to apply social entrepreneurship, or become a successful social entrepreneur.

This text explores the consequences for language acquisition, language evolution and linguistic theory of taking the underlying architecture of the language faculty to be that of a dynamical system. The authors investigate whether it is possible for a complex adaptive system to identify the categories, structures and rules of a language given access only to instances of grammatical utterances of that language. The linguistic tradition says that this is impossible, but there is a growing body of literature in psychology and computer science arguing that grammar can be uncovered using purely statistical techniques applied to the distribution of forms in a string of words. The book goes on to discuss whether a learner requires information about structure that goes beyond the information that is contained in the meaning. Does the learner have to have knowledge of grammar per se prior to language acquisition, as has been traditionally assumed? The authors ask whether it is possible to adequately describe and explain linguistic phenomena if we restrict ourselves to the relatively impoverished apparatus that we require for language acquisition. They explore the consequences of adopting a radical form of minimalism to try to reconcile the linguistic facts with the book's perspective of language acquisition. Culicover and Nowak investigate to what extent it is possible to account for language variation in dynamical terms, as a consequence of the behaviour of the complex social network in which languages and the properties of languages are acquired by learners through interactions with other speakers over time.

Social Entrepreneurship: Theory and Practice details how social entrepreneurship can creatively solve pressing and seemingly insurmountable social problems. Theories of social change are presented to help demystify the magic of making an immense, yet durable and irreversible social impact. In-depth case studies from multiple disciplines and from around the globe document how social entrepreneurs foster bottom-up change that empowers people and societies. The authors review the specific personality traits of social entrepreneurs and introduce the new leadership model required for 21st-century development. This book is valuable to undergraduate, graduate, and post-graduate students, while remaining accessible to non-academic readers due to its clear language, illustrative case studies, and guidelines on how to apply social entrepreneurship, or become a successful social entrepreneur.

Dynamical Grammar explores the consequences for language acquisition, language evolution, and linguistic theory of taking the underlying architecture of the language faculty to be that of a complex adaptive dynamical system. It contains the first results of a new and complex model of language acquisition which the authors have developed to measure how far language input is reflected in language output and thereby get a better idea of just how far the human language faculty is hard-wired.

Conflict is inherent in virtually every aspect of human relations, from sport to parliamentary democracy, from fashion in the arts to paradigmatic challenges in the sciences, and from economic activity to intimate relationships. Yet, it can become among the most serious social problems humans face when it loses its constructive features and becomes protracted over time with no obvious means of resolution. This book addresses the subject of intractable social conflict from a new vantage point. Here, these types of conflict represent self-organizing phenomena, emerging quite naturally from the ongoing dynamics in human interaction at any scale-from the interpersonal to the international. Using the universal language and computational framework of nonlinear dynamical systems theory in combination with recent insights from social psychology, intractable conflict is understood as a system locked in special attractor states that constrain the thoughts and actions of the parties to the conflict. The emergence and maintenance of attractors for conflict can be described by means of formal models that incorporate the results of computer simulations, experiments, field research, and archival analyses. Multi-disciplinary research reflecting these approaches provides encouraging support for the dynamical systems perspective. Importantly, this text presents new views on conflict resolution. In contrast to traditional approaches that tend to focus on basic, short-lived cause-effect relations, the dynamical perspective emphasizes the temporal patterns and potential for emergence in destructive relations. Attractor deconstruction entails restoring complexity to a conflict scenario by isolating elements or changing the feedback loops among them. The creation of a latent attractor trades on the tendency toward multi-stability in dynamical systems and entails the consolidation of incongruent (positive) elements into a coherent structure. In the bifurcation scenario, factors are identified that can change the number and types of attractors in a conflict scenario. The implementation of these strategies may hold the key to unlocking intractable conflict, creating the potential for constructive social relations.

Traditional approaches to social psychology have proven highly successful in identifying causal mechanisms underlying human thought and behavior. With the recent advent of the dynamical approach, it is now possible to assemble sets of such mechanisms into coherent systems. This book uses innovative concepts and tools to illuminate the processes by which individuals, groups, and societies evolve and change in a systemic, self-sustaining manner, at times seemingly independent of external influences. Readers learn how the dynamical approach facilitates novel predictions and insights into such social psychological phenomena as attitudes, social judgment, goal-directed behavior, attraction, and relationships. Featuring a wealth of charts and figures derived from original research and computer simulations, the volume is grounded in classic and contemporary theories of social psychology.

This book introduces and the new computer-based research methods for studying and modeling complex social phenomena. It is the first coherent collection that surveys the impact that computer-based methods have had on the social and behavioural sciences and illustrates the potential for future research. The methods are presented in an accessible manner and do not assume any background in computer science. The authors introduce each chapter and explain how computers can help to study social processes and each method is described in relation to a substantive issue to show how it can contribute to our understanding of complex problems. The themes covered include computer simulation, neural and social networks and the visualization of complex network data.