Princeton Studies in Complexity Series

Robert Axelrod is widely known for his groundbreaking work in game theory and complexity theory. He is a leader in applying computer modeling to social science problems. His book The Evolution of Cooperation has been hailed as a seminal contribution and has been translated into eight languages since its initial publication. The Complexity of Cooperation is a sequel to that landmark book. It collects seven essays, originally published in a broad range of journals, and adds an extensive new introduction to the collection, along with new prefaces to each essay and a useful new appendix of additional resources. Written in Axelrod's acclaimed, accessible style, this collection serves as an introductory text on complexity theory and computer modeling in the social sciences and as an overview of the current state of the art in the field. The articles move beyond the basic paradigm of the Prisoner's Dilemma to study a rich set of issues, including how to cope with errors in perception or implementation, how norms emerge, and how new political actors and regions of shared culture can develop. They use the shared methodology of agent-based modeling, a powerful technique that specifies the rules of interaction between individuals and uses computer simulation to discover emergent properties of the social system. The Complexity of Cooperation is essential reading for all social scientists who are interested in issues of cooperation and complexity.

Peter Albin is known for his seminal work in applying the concepts of adaptive dynamical systems, first developed by biologists and physicists, to the study of economic systems. This book is a collection of his pathbreaking articles on the application of cellular automata and complexity theory to economic problems. Duncan Foley provides a thoughtful introduction in which he reviews the disparate analytical sources of Albin's work in the theories of nonlinear dynamical systems, economic dynamics, cellular automata, linguistic and computational complexity, and bounded rationality. Albin has analyzed economic systems as interactions of highly complex components (i.e., intelligent human beings). He uses the theories of generative linguistics and cellular automata to establish that the complexity level of economic systems is, in principle at least, that of a Turing machine or general-purpose computer, establishing that classic economic approaches to the problems of household and firm choice, macroeconomic prediction, and policy evaluation may give rise to undecidable propositions and uncomputable functions. He develops simple models of dynamic economic interaction based on cellular automata which illustrate the inherent complexity of economic interactions and the resulting challenge they pose to traditional theories of rational economic behavior. These models explore the dynamics of the business cycle, decentralized market trading, and the emergence of cooperation in a novel local-interaction version of the repeated prisoners' dilemma game. Albin's work provides a unique and important perspective on economic systems.

Everyone knows the small-world phenomenon: soon after meeting a stranger, we are surprised to discover that we have a mutual friend, or we are connected through a short chain of acquaintances. In his book, Duncan Watts uses this intriguing phenomenon--colloquially called "six degrees of separation"--as a prelude to a more general exploration: under what conditions can a small world arise in any kind of network? The networks of this story are everywhere: the brain is a network of neurons; organisations are people networks; the global economy is a network of national economies, which are networks of markets, which are in turn networks of interacting producers and consumers. Food webs, ecosystems, and the Internet can all be represented as networks, as can strategies for solving a problem, topics in a conversation, and even words in a language. Many of these networks, the author claims, will turn out to be small worlds. How do such networks matter? Simply put, local actions can have global consequences, and the relationship between local and global dynamics depends critically on the network's structure. Watts illustrates the subtleties of this relationship using a variety of simple models---the spread of infectious disease through a structured population; the evolution of cooperation in game theory; the computational capacity of cellular automata; and the sychronisation of coupled phase-oscillators. Watts's novel approach is relevant to many problems that deal with network connectivity and complex systems' behaviour in general: How do diseases (or rumours) spread through social networks? How does cooperation evolve in large groups? How do cascading failures propagate through large power grids, or financial systems? What is the most efficient architecture for an organisation, or for a communications network? This fascinating exploration will be fruitful in a remarkable variety of fields, including physics and mathematics, as well as sociology, economics, and biology.

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.

Many historical processes are dynamic. Populations grow and decline. Empires expand and collapse. Religions spread and wither. Natural scientists have made great strides in understanding dynamical processes in the physical and biological worlds using a synthetic approach that combines mathematical modeling with statistical analyses. Taking up the problem of territorial dynamics--why some polities at certain times expand and at other times contract--this book shows that a similar research program can advance our understanding of dynamical processes in history. Peter Turchin develops hypotheses from a wide range of social, political, economic, and demographic factors: geopolitics, factors affecting collective solidarity, dynamics of ethnic assimilation/religious conversion, and the interaction between population dynamics and sociopolitical stability. He then translates these into a spectrum of mathematical models, investigates the dynamics predicted by the models, and contrasts model predictions with empirical patterns. Turchin's highly instructive empirical tests demonstrate that certain models predict empirical patterns with a very high degree of accuracy. For instance, one model accounts for the recurrent waves of state breakdown in medieval and early modern Europe. And historical data confirm that ethno-nationalist solidarity produces an aggressively expansive state under certain conditions (such as in locations where imperial frontiers coincide with religious divides). The strength of Turchin's results suggests that the synthetic approach he advocates can significantly improve our understanding of historical dynamics.

Along rivers in Bali, small groups of farmers meet regularly in water temples to manage their irrigation systems. They have done so for a thousand years. Over the centuries, water temple networks have expanded to manage the ecology of rice terraces at the scale of whole watersheds. Although each group focuses on its own problems, a global solution nonetheless emerges that optimizes irrigation flows for everyone. Did someone have to design Bali's water temple networks, or could they have emerged from a self-organizing process? Perfect Order--a groundbreaking work at the nexus of conservation, complexity theory, and anthropology--describes a series of fieldwork projects triggered by this question, ranging from the archaeology of the water temples to their ecological functions and their place in Balinese cosmology. Stephen Lansing shows that the temple networks are fragile, vulnerable to the cross-currents produced by competition among male descent groups. But the feminine rites of water temples mirror the farmers' awareness that when they act in unison, small miracles of order occur regularly, as the jewel-like perfection of the rice terraces produces general prosperity. Much of this is barely visible from within the horizons of Western social theory. The fruit of a decade of multidisciplinary research, this absorbing book shows that even as researchers probe the foundations of cooperation in the water temple networks, the very existence of the traditional farming techniques they represent is threatened by large-scale development projects.

Agent-based computational modeling is changing the face of social science. In Generative Social Science, Joshua Epstein argues that this powerful, novel technique permits the social sciences to meet a fundamentally new standard of explanation, in which one "grows" the phenomenon of interest in an artificial society of interacting agents: heterogeneous, boundedly rational actors, represented as mathematical or software objects. After elaborating this notion of generative explanation in a pair of overarching foundational chapters, Epstein illustrates it with examples chosen from such far-flung fields as archaeology, civil conflict, the evolution of norms, epidemiology, retirement economics, spatial games, and organizational adaptation. In elegant chapter preludes, he explains how these widely diverse modeling studies support his sweeping case for generative explanation. This book represents a powerful consolidation of Epstein's interdisciplinary research activities in the decade since the publication of his and Robert Axtell's landmark volume, Growing Artificial Societies. Beautifully illustrated, Generative Social Science includes a CD that contains animated movies of core model runs, and programs allowing users to easily change assumptions and explore models, making it an invaluable text for courses in modeling at all levels.

All living things are remarkably complex, yet their DNA is unstable, undergoing countless random mutations over generations. Despite this instability, most animals do not grow two heads or die, plants continue to thrive, and bacteria continue to divide. Robustness and Evolvability in Living Systems tackles this perplexing paradox. The book explores why genetic changes do not cause organisms to fail catastrophically and how evolution shapes organisms' robustness. Andreas Wagner looks at this problem from the ground up, starting with the alphabet of DNA, the genetic code, RNA, and protein molecules, moving on to genetic networks and embryonic development, and working his way up to whole organisms. He then develops an evolutionary explanation for robustness. Wagner shows how evolution by natural selection preferentially finds and favors robust solutions to the problems organisms face in surviving and reproducing. Such robustness, he argues, also enhances the potential for future evolutionary innovation. Wagner also argues that robustness has less to do with organisms having plenty of spare parts (the redundancy theory that has been popular) and more to do with the reality that mutations can change organisms in ways that do not substantively affect their fitness. Unparalleled in its field, this book offers the most detailed analysis available of all facets of robustness within organisms. It will appeal not only to biologists but also to engineers interested in the design of robust systems and to social scientists concerned with robustness in human communities and populations.

Party competition for votes in free and fair elections involves complex interactions by multiple actors in political landscapes that are continuously evolving, yet classical theoretical approaches to the subject leave many important questions unanswered. Here Michael Laver and Ernest Sergenti offer the first comprehensive treatment of party competition using the computational techniques of agent-based modeling. This exciting new technology enables researchers to model competition between several different political parties for the support of voters with widely varying preferences on many different issues. Laver and Sergenti model party competition as a true dynamic process in which political parties rise and fall, a process where different politicians attack the same political problem in very different ways, and where today's political actors, lacking perfect information about the potential consequences of their choices, must constantly adapt their behavior to yesterday's political outcomes. Party Competition shows how agent-based modeling can be used to accurately reflect how political systems really work. It demonstrates that politicians who are satisfied with relatively modest vote shares often do better at winning votes than rivals who search ceaselessly for higher shares of the vote. It reveals that politicians who pay close attention to their personal preferences when setting party policy often have more success than opponents who focus solely on the preferences of voters, that some politicians have idiosyncratic "valence" advantages that enhance their electability--and much more.

How do we explain the remarkably abrupt changes that sometimes occur in nature and society--and can we predict why and when they happen? This book offers a comprehensive introduction to critical transitions in complex systems--the radical changes that happen at tipping points when thresholds are passed. Marten Scheffer accessibly describes the dynamical systems theory behind critical transitions, covering catastrophe theory, bifurcations, chaos, and more. He gives examples of critical transitions in lakes, oceans, terrestrial ecosystems, climate, evolution, and human societies. And he demonstrates how to deal with these transitions, offering practical guidance on how to predict tipping points, how to prevent "bad" transitions, and how to promote critical transitions that work for us and not against us. Scheffer shows the time is ripe for understanding and managing critical transitions in the vast and complex systems in which we live. This book can also serve as a textbook and includes a detailed appendix with equations. Provides an accessible introduction to dynamical systems theory Covers critical transitions in lakes, oceans, terrestrial ecosystems, the climate, evolution, and human societies Explains how to predict tipping points Offers strategies for preventing "bad" transitions and triggering "good" ones Features an appendix with equations

This book provides the first clear, comprehensive, and accessible account of complex adaptive social systems, by two of the field's leading authorities. Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.

Two pioneering anthropologists reveal how complexity science can help us better understand how societies change over time Over the past two decades, anthropologist J. Stephen Lansing and geneticist Murray Cox have explored dozens of villages on the islands of the Malay Archipelago, combining ethnographic research with research into genetic and linguistic markers to shed light on how these societies change over time. Islands of Order draws on their pioneering fieldwork to show how the science of complexity can be used to better understand unstable dynamics in culture, language, cooperation, and the emergence of hierarchies. Complexity science has opened exciting new vistas in physics and biology, but poses challenges for social scientists. What triggers fundamental, discontinuous social change? And what brings stable patterns—islands of order—into existence? Lansing and Cox begin with an incisive and accessible introduction to models of change, from simple random drift to coupled interactions, phase transitions, co-phylogenies, and adaptive landscapes. Then they take readers on a series of journeys to the islands of the Indo-Pacific to demonstrate how social scientists can harness these powerful tools to discover out-of-equilibrium social dynamics. Lansing and Cox address empirical questions surrounding the colonization of the Pacific, the relationship of language to culture, the emergence and disappearance of male and female hierarchies, and more. Unlocking new possibilities for the social sciences, Islands of Order is accompanied by an interactive companion website that enables readers to explore the models described in the book.

The Final Volume of the Groundbreaking Trilogy on Agent-Based Modeling In this pioneering synthesis, Joshua Epstein introduces a new theoretical entity: Agent_Zero. This software individual, or "agent," is endowed with distinct emotional/affective, cognitive/deliberative, and social modules. Grounded in contemporary neuroscience, these internal components interact to generate observed, often far-from-rational, individual behavior. When multiple agents of this new type move and interact spatially, they collectively generate an astonishing range of dynamics spanning the fields of social conflict, psychology, public health, law, network science, and economics. Epstein weaves a computational tapestry with threads from Plato, Hume, Darwin, Pavlov, Smith, Tolstoy, Marx, James, and Dostoevsky, among others. This transformative synthesis of social philosophy, cognitive neuroscience, and agent-based modeling will fascinate scholars and students of every stripe. Epstein's computer programs are provided in the book or on its Princeton University Press website, along with movies of his "computational parables.? Agent_Zero is a signal departure in what it includes (e.g., a new synthesis of neurally grounded internal modules), what it eschews (e.g., standard behavioral imitation), the phenomena it generates (from genocide to financial panic), and the modeling arsenal it offers the scientific community. For generative social science, Agent_Zero presents a groundbreaking vision and the tools to realize it.

Earthquakes are a huge global threat. In thirty-six countries, severe seismic risks threaten populations and their increasingly interdependent systems of transportation, communication, energy, and finance. In this important book, Louise Comfort provides an unprecedented examination of how twelve communities in nine countries responded to destructive earthquakes between 1999 and 2015. And many of the book’s lessons can also be applied to other large-scale risks. The Dynamics of Risk sets the global problem of seismic risk in the framework of complex adaptive systems to explore how the consequences of such events ripple across jurisdictions, communities, and organizations in complex societies, triggering unexpected alliances but also exposing social, economic, and legal gaps. The book assesses how the networks of organizations involved in response and recovery adapted and acted collectively after the twelve earthquakes it examines. It describes how advances in information technology enabled some communities to anticipate seismic risk better and to manage response and recovery operations more effectively, decreasing losses. Finally, the book shows why investing substantively in global information infrastructure would create shared awareness of seismic risk and make postdisaster relief more effective and less expensive. The result is a landmark study of how to improve the way we prepare for and respond to earthquakes and other disasters in our ever-more-complex world.