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.

A dynamical system refers to a set of elements that interact in complex, often nonlinear ways to form coherent patterns. Because of the complexity of these interactions, the system as a whole may evolve over time in seemingly unpredictable ways as new patterns of behavior emerge. This metatheory has proven useful in understanding diverse phenomena in meteorology, population biology, statistical mechanics, economics, and cosmology. The book demonstrates how the dynamical systems perspective can be applied to theory construction and research in social psychology, and in doing so, provides fresh insight into such complex phenomena as interpersonal behavior, social relations, attitudes, and social cognition.

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.

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.

While many books have discussed methodological advances in nonlinear dynamical systems theory (NDS), this volume is unique in its focus on NDS's role in the development of psychological theory. After an introductory chapter covering the fundamentals of chaos, complexity and other nonlinear dynamics, subsequent chapters provide in-depth coverage of each of the specific topic areas in psychology. A concluding chapter takes stock of the field as a whole, evaluating important challenges for the immediate future. The chapters are written by experts in the use of NDS in each of their respective areas, including biological, cognitive, developmental, social, organizational and clinical psychology. Each chapter provides an in-depth examination of theoretical foundations and specific applications and a review of relevant methods. This edited collection represents the state of the art in NDS science across the disciplines of psychology.

In this book we develop various mathematical models of information dynamics, I -dynamics (including the process of thinking), based on methods of classical and quantum physics. The main aim of our investigations is to describe mathematically the phenomenon of consciousness. We would like to realize a kind of Newton-Descartes program (corrected by the lessons of statistical and quantum mechanics) for information processes. Starting from the ideas of Newton and Descartes, in physics there was developed an adequate description of the dynamics of material systems. We would like to develop an analogous mathematical formalism for information and, in particular, mental processes. At the beginning of the 21st century it is clear that it would be impossible to create a deterministic model for general information processes. A deterministic model has to be completed by a corresponding statistical model of information flows and, in particular, flows of minds. It might be that such an information statistical model should have a quantum-like structure.

Recent years have witnessed the ascendance of a new way to conceptualize and investigate the nature of dynamism at different levels of psychological reality. Areas of inquiry as diverse as cognitive neuroscience, developmental psychology, organizational behavior, and political sociology are being reframed in terms that allow rigorous and precise insight into basic dynamic processes. There are signs that this new approach to dynamics is emerging as a potentially integrative paradigm for personality and social psychology as well. This special issue highlights this new paradigm and illustrates its relevance to a broad spectrum of topics in personality and social psychology.