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Ant Encounters: Interaction Networks and Colony Behavior

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Interaction Networks and Colony Behavior

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How do ant colonies get anything done, when no one is in charge? An ant colony operates without a central control or hierarchy, and no ant directs another. Instead, ants decide what to do based on the rate, rhythm, and pattern of individual encounters and interactions--resulting in a dynamic network that coordinates the functions of the colony. Ant Encounters provides a revealing and accessible look into ant behavior from this complex systems perspective.  Focusing on the moment-to-moment behavior of ant colonies, Deborah Gordon investigates the role of interaction networks in regulating colony behavior and relations among ant colonies. She shows how ant behavior within and between colonies arises from local interactions of individuals, and how interaction networks develop as a colony grows older and larger. The more rapidly ants react to their encounters, the more sensitively the entire colony responds to changing conditions. Gordon explores whether such reactive networks help a colony to survive and reproduce, how natural selection shapes colony networks, and how these structures compare to other analogous complex systems.   Ant Encounters sheds light on the organizational behavior, ecology, and evolution of these diverse and ubiquitous social insects.

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From Populations to Ecosystems: Theoretical Foundations for a New Ecological Synthesis (MPB-46)

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Theoretical Foundations for a New Ecological Synthesis (MPB-46)

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The major subdisciplines of ecology--population ecology, community ecology, ecosystem ecology, and evolutionary ecology--have diverged increasingly in recent decades. What is critically needed today is an integrated, real-world approach to ecology that reflects the interdependency of biodiversity and ecosystem functioning. From Populations to Ecosystems proposes an innovative theoretical synthesis that will enable us to advance our fundamental understanding of ecological systems and help us to respond to today's emerging global ecological crisis.  Michel Loreau begins by explaining how the principles of population dynamics and ecosystem functioning can be merged. He then addresses key issues in the study of biodiversity and ecosystems, such as functional complementarity, food webs, stability and complexity, material cycling, and metacommunities. Loreau describes the most recent theoretical advances that link the properties of individual populations to the aggregate properties of communities, and the properties of functional groups or trophic levels to the functioning of whole ecosystems, placing special emphasis on the relationship between biodiversity and ecosystem functioning. Finally, he turns his attention to the controversial issue of the evolution of entire ecosystems and their properties, laying the theoretical foundations for a genuine evolutionary ecosystem ecology.  From Populations to Ecosystems points the way to a much-needed synthesis in ecology, one that offers a fuller understanding of ecosystem processes in the natural world.

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Random matrix theory, both as an application and as a theory, has evolved rapidly over the past fifteen years. Log-Gases and Random Matrices gives a comprehensive account of these developments, emphasizing log-gases as a physical picture and heuristic, as well as covering topics such as beta ensembles and Jack polynomials.

Peter Forrester presents an encyclopedic development of log-gases and random matrices viewed as examples of integrable or exactly solvable systems. Forrester develops not only the application and theory of Gaussian and circular ensembles of classical random matrix theory, but also of the Laguerre and Jacobi ensembles, and their beta extensions. Prominence is given to the computation of a multitude of Jacobians; determinantal point processes and orthogonal polynomials of one variable; the Selberg integral, Jack polynomials, and generalized hypergeometric functions; Painleve transcendents; macroscopic electrostatistics and asymptotic formulas; nonintersecting paths and models in statistical mechanics; and applications of random matrix theory. This is the first textbook development of both nonsymmetric and symmetric Jack polynomial theory, as well as the connection between Selberg integral theory and beta ensembles. The author provides hundreds of guided exercises and linked topics, making Log-Gases and Random Matrices an indispensable reference work, as well as a learning resource for all students and researchers in the field.

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Ramsey theory is a fast-growing area of combinatorics with deep connections to other fields of mathematics such as topological dynamics, ergodic theory, mathematical logic, and algebra. The area of Ramsey theory dealing with Ramsey-type phenomena in higher dimensions is particularly useful. Introduction to Ramsey Spaces presents in a systematic way a method for building higher-dimensional Ramsey spaces from basic one-dimensional principles. It is the first book-length treatment of this area of Ramsey theory, and emphasizes applications for related and surrounding fields of mathematics, such as set theory, combinatorics, real and functional analysis, and topology. In order to facilitate accessibility, the book gives the method in its axiomatic form with examples that cover many important parts of Ramsey theory both finite and infinite.

An exciting new direction for combinatorics, this book will interest graduate students and researchers working in mathematical subdisciplines requiring the mastery and practice of high-dimensional Ramsey theory.

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This book introduces a comprehensive methodology for adaptive control design of parabolic partial differential equations with unknown functional parameters, including reaction-convection-diffusion systems ubiquitous in chemical, thermal, biomedical, aerospace, and energy systems. Andrey Smyshlyaev and Miroslav Krstic develop explicit feedback laws that do not require real-time solution of Riccati or other algebraic operator-valued equations. The book emphasizes stabilization by boundary control and using boundary sensing for unstable PDE systems with an infinite relative degree. The book also presents a rich collection of methods for system identification of PDEs, methods that employ Lyapunov, passivity, observer-based, swapping-based, gradient, and least-squares tools and parameterizations, among others.

Including a wealth of stimulating ideas and providing the mathematical and control-systems background needed to follow the designs and proofs, the book will be of great use to students and researchers in mathematics, engineering, and physics. It also makes a valuable supplemental text for graduate courses on distributed parameter systems and adaptive control.

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Nonnegative and Compartmental Dynamical Systems

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This comprehensive book provides the first unified framework for stability and dissipativity analysis and control design for nonnegative and compartmental dynamical systems, which play a key role in a wide range of fields, including engineering, thermal sciences, biology, ecology, economics, genetics, chemistry, medicine, and sociology. Using the highest standards of exposition and rigor, the authors explain these systems and advance the state of the art in their analysis and active control design.

Nonnegative and Compartmental Dynamical Systems presents the most complete treatment available of system solution properties, Lyapunov stability analysis, dissipativity theory, and optimal and adaptive control for these systems, addressing continuous-time, discrete-time, and hybrid nonnegative system theory. This book is an indispensable resource for applied mathematicians, dynamical systems theorists, control theorists, and engineers, as well as for researchers and graduate students who want to understand the behavior of nonnegative and compartmental dynamical systems that arise in areas such as biomedicine, demographics, epidemiology, pharmacology, telecommunications, transportation, thermodynamics, networks, heat transfer, and power systems.

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Wassim M. Haddad, VijaySekhar Chellaboina, Qing Hui

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Graph Theoretic Methods in Multiagent Networks

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This accessible book provides an introduction to the analysis and design of dynamic multiagent networks. Such networks are of great interest in a wide range of areas in science and engineering, including: mobile sensor networks, distributed robotics such as formation flying and swarming, quantum networks, networked economics, biological synchronization, and social networks. Focusing on graph theoretic methods for the analysis and synthesis of dynamic multiagent networks, the book presents a powerful new formalism and set of tools for networked systems.

The book's three sections look at foundations, multiagent networks, and networks as systems. The authors give an overview of important ideas from graph theory, followed by a detailed account of the agreement protocol and its various extensions, including the behavior of the protocol over undirected, directed, switching, and random networks. They cover topics such as formation control, coverage, distributed estimation, social networks, and games over networks. And they explore intriguing aspects of viewing networks as systems, by making these networks amenable to control-theoretic analysis and automatic synthesis, by monitoring their dynamic evolution, and by examining higher-order interaction models in terms of simplicial complexes and their applications.

The book will interest graduate students working in systems and control, as well as in computer science and robotics. It will be a standard reference for researchers seeking a self-contained account of system-theoretic aspects of multiagent networks and their wide-ranging applications.

This book has been adopted as a textbook at the following universities:
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University of Stuttgart, Germany
Royal Institute of Technology, Sweden
Johannes Kepler University, Austria
Georgia Tech, USA
University of Washington, USA
Ohio University, USA

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Numerical Methods for Stochastic Computations

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The@ first graduate-level textbook to focus on fundamental aspects of numerical methods for stochastic computations, this book describes the class of numerical methods based on generalized polynomial chaos (gPC). These fast, efficient, and accurate methods are an extension of the classical spectral methods of high-dimensional random spaces. Designed to simulate complex systems subject to random inputs, these methods are widely used in many areas of computer science and engineering.

The book introduces polynomial approximation theory and probability theory; describes the basic theory of gPC methods through numerical examples and rigorous development; details the procedure for converting stochastic equations into deterministic ones; using both the Galerkin and collocation approaches; and discusses the distinct differences and challenges arising from high-dimensional problems. The last section is devoted to the application of gPC methods to critical areas such as inverse problems and data assimilation.

Ideal for use by graduate students and researchers both in the classroom and for self-study, Numerical Methods for Stochastic Computations provides the required tools for in-depth research related to stochastic computations.

The first graduate-level textbook to focus on the fundamentals of numerical methods for stochastic computations
Ideal introduction for graduate courses or self-study
Fast, efficient, and accurate numerical methods
Polynomial approximation theory and probability theory included
Basic gPC methods illustrated through examples

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Techniques for deciphering texts by early mathematicians

Writings by early mathematicians feature language and notations that are quite different from what we're familiar with today. Sourcebooks on the history of mathematics provide some guidance, but what has been lacking is a guide tailored to the needs of readers approaching these writings for the first time. How to Read Historical Mathematics fills this gap by introducing readers to the analytical questions historians ask when deciphering historical texts.

Sampling actual writings from the history of mathematics, Benjamin Wardhaugh reveals the questions that will unlock the meaning and significance of a given textWho wrote it, why, and for whom? What was its author's intended meaning? How did it reach its present form? Is it original or a translation? Why is it important today? Wardhaugh teaches readers to think about what the original text might have looked like, to consider where and when it was written, and to formulate questions of their own. Readers pick up new skills with each chapter, and gain the confidence and analytical sophistication needed to tackle virtually any text in the history of mathematics.
Introduces readers to the methods of textual analysis used by historiansUses actual source material as examplesFeatures boxed summaries, discussion questions, and suggestions for further readingSupplements all major sourcebooks in mathematics historyDesigned for easy referenceIdeal for students and teachers

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A fully updated edition of the classic text by acclaimed physicist A. Zee

Since it was first published, Quantum Field Theory in a Nutshell has quickly established itself as the most accessible and comprehensive introduction to this profound and deeply fascinating area of theoretical physics. Now in this fully revised and expanded edition, A. Zee covers the latest advances while providing a solid conceptual foundation for students to build on, making this the most up-to-date and modern textbook on quantum field theory available.

This expanded edition features several additional chapters, as well as an entirely new section describing recent developments in quantum field theory such as gravitational waves, the helicity spinor formalism, on-shell gluon scattering, recursion relations for amplitudes with complex momenta, and the hidden connection between Yang-Mills theory and Einstein gravity. Zee also provides added exercises, explanations, and examples, as well as detailed appendices, solutions to selected exercises, and suggestions for further reading.
The most accessible and comprehensive introductory textbook availableFeatures a fully revised, updated, and expanded textCovers the latest exciting advances in the fieldIncludes new exercisesOffers a one-of-a-kind resource for students and researchers
Leading universities that have adopted this book include:

Arizona State UniversityBoston UniversityBrandeis UniversityBrown UniversityCalifornia Institute of TechnologyCarnegie MellonCollege of William & MaryCornellHarvard UniversityMassachusetts Institute of TechnologyNorthwestern UniversityOhio State UniversityPrinceton UniversityPurdue University - Main CampusRensselaer Polytechnic InstituteRutgers University - New BrunswickStanford UniversityUniversity of California - BerkeleyUniversity of Central FloridaUniversity of ChicagoUniversity of MichiganUniversity of MontrealUniversity of Notre DameVanderbilt UniversityVirginia Tech University

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Over the past twenty years, astronomers have identified hundreds of extrasolar planets--planets orbiting stars other than the sun. Recent research in this burgeoning field has made it possible to observe and measure the atmospheres of these exoplanets. This is the first textbook to describe the basic physical processes--including radiative transfer, molecular absorption, and chemical processes--common to all planetary atmospheres, as well as the transit, eclipse, and thermal phase variation observations that are unique to exoplanets.

In each chapter, Sara Seager offers a conceptual introduction, examples that combine the relevant physics equations with real data, and exercises. Topics range from foundational knowledge, such as the origin of atmospheric composition and planetary spectra, to more advanced concepts, such as solutions to the radiative transfer equation, polarization, and molecular and condensate opacities. Since planets vary widely in their atmospheric properties, Seager emphasizes the major physical processes that govern all planetary atmospheres.

Moving from first principles to cutting-edge research, Exoplanet Atmospheres is an ideal resource for students and researchers in astronomy and earth sciences, one that will help prepare them for the next generation of planetary science.

The first textbook to describe exoplanet atmospheres
Illustrates concepts using examples grounded in real data
Provides a step-by-step guide to understanding the structure and emergent spectrum of a planetary atmosphere
Includes exercises for students

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The Known, the Unknown, and the Unknowable in Financial Risk Management

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Measurement and Theory Advancing Practice

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A clear understanding of what we know, don't know, and can't know should guide any reasonable approach to managing financial risk, yet the most widely used measure in finance today--Value at Risk, or VaR--reduces these risks to a single number, creating a false sense of security among risk managers, executives, and regulators. This book introduces a more realistic and holistic framework called
KuU
--the
K
nown, the
u
nknown, and the
U
nknowable--that enables one to conceptualize the different kinds of financial risks and design effective strategies for managing them. Bringing together contributions by leaders in finance and economics, this book pushes toward robustifying policies, portfolios, contracts, and organizations to a wide variety of
KuU
risks. Along the way, the strengths and limitations of "quantitative" risk management are revealed.

In addition to the editors, the contributors are Ashok Bardhan, Dan Borge, Charles N. Bralver, Riccardo Colacito, Robert H. Edelstein, Robert F. Engle, Charles A. E. Goodhart, Clive W. J. Granger, Paul R. Kleindorfer, Donald L. Kohn, Howard Kunreuther, Andrew Kuritzkes, Robert H. Litzenberger, Benoit B. Mandelbrot, David M. Modest, Alex Muermann, Mark V. Pauly, Til Schuermann, Kenneth E. Scott, Nassim Nicholas Taleb, and Richard J. Zeckhauser.

Introduces a new risk-management paradigm
Features contributions by leaders in finance and economics
Demonstrates how "killer risks" are often more economic than statistical, and crucially linked to incentives
Shows how to invest and design policies amid financial uncertainty

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Francis X. Diebold, Neil A. Doherty, Richard J. Herring

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Forward-Looking Decision Making: Dynamic Programming Models Applied to Health, Risk, Employment, and Financial Stability

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Dynamic Programming Models Applied to Health, Risk, Employment, and Financial Stability

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Individuals and families make key decisions that impact many aspects of financial stability and determine the future of the economy. These decisions involve balancing current sacrifice against future benefits. People have to decide how much to invest in health care, exercise, their diet, and insurance. They must decide how much debt to take on, and how much to save. And they make choices about jobs that determine employment and unemployment levels. Forward-Looking Decision Making is about modeling this individual or family-based decision making using an optimizing dynamic programming model.  Robert Hall first reviews ideas about dynamic programs and introduces new ideas about numerical solutions and the representation of solved models as Markov processes. He surveys recent research on the parameters of preferences--the intertemporal elasticity of substitution, the Frisch elasticity of labor supply, and the Frisch cross-elasticity. He then examines dynamic programming models applied to health spending, long-term care insurance, employment, entrepreneurial risk-taking, and consumer debt.  Linking theory with data and applying them to real-world problems, Forward-Looking Decision Making uses dynamic optimization programming models to shed light on individual behaviors and their economic implications.

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Innovation, Intellectual Property, and Economic Growth

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What drives innovation? How does it contribute to the growth of firms, industries, and economies? And do intellectual property rights help or hurt innovation and growth? Uniquely combining microeconomics, macroeconomics, and theory with empirical analysis drawn from the United States and Europe, this book introduces graduate students and advanced undergraduates to the complex process of innovation. By addressing all the major dimensions of innovation in a single text, Christine Greenhalgh and Mark Rogers are able to show how outcomes at the microlevel feed through to the macro-outcomes that in turn determine personal incomes and job opportunities.

In four sections, this textbook comprehensively addresses the nature of innovation and intellectual property, the microeconomics and macroeconomics of innovation, and economic policy at the firm and macroeconomic levels. Among the topics fully explored are the role of intellectual property in creating incentives to innovate; the social returns of innovation; the creation and destruction of jobs by innovation; whether more or fewer intellectual property rights would give firms better incentives to innovate; and the contentious issues surrounding international treaties on intellectual property.

Clearly organized and highly readable, the book is designed to be accessible to readers without advanced economics backgrounds. Most technical materials appear in boxed inserts and appendixes, and numerous graphs and tables elucidate abstract concepts.

Provides a comprehensive overview of the economic causes and effects of innovation
Covers microeconomics, macroeconomics, theoretical and empirical analysis, and policy
Includes up-to-date coverage of trends and policy in intellectual property and research and development
Features mathematics appendix and keywords and questions to assist learning and teaching
Outline lecture slides are available online

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The Evolution of Banking in the Industrialized World since 1800

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A sweeping look at the evolution of commercial banks over the past two centuries

Commercial banks are among the oldest and most familiar financial institutions. When they work well, we hardly notice; when they do not, we rail against them. What are the historical forces that have shaped the modern banking system? In Unsettled Account, Richard Grossman takes the first truly comparative look at the development of commercial banking systems over the past two centuries in Western Europe, the United States, Canada, Japan, and Australia. Grossman focuses on four major elements that have contributed to banking evolution: crises, bailouts, mergers, and regulations. He explores where banking crises come from and why certain banking systems are more resistant to crises than others, how governments and financial systems respond to crises, why merger movements suddenly take off, and what motivates governments to regulate banks.

Grossman reveals that many of the same components underlying the history of banking evolution are at work today. The recent subprime mortgage crisis had its origins, like many earlier banking crises, in a boom-bust economic cycle. Grossman finds that important historical elements are also at play in modern bailouts, merger movements, and regulatory reforms.

Unsettled Account is a fascinating and informative must-read for anyone who wants to understand how the modern commercial banking system came to be, where it is headed, and how its development will affect global economic growth.

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Complete and Incomplete Econometric Models

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Econometric models are widely used in the creation and evaluation of economic policy in the public and private sectors. But these models are useful only if they adequately account for the phenomena in question, and they can be quite misleading if they do not. In response, econometricians have developed tests and other checks for model adequacy. All of these methods, however, take as given the specification of the model to be tested. In this book, John Geweke addresses the critical earlier stage of model development, the point at which potential models are inherently incomplete.

Summarizing and extending recent advances in Bayesian econometrics, Geweke shows how simple modern simulation methods can complement the creative process of model formulation. These methods, which are accessible to economics PhD students as well as to practicing applied econometricians, streamline the processes of model development and specification checking. Complete with illustrations from a wide variety of applications, this is an important contribution to econometrics that will interest economists and PhD students alike.

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Labor Markets and Business Cycles integrates search and matching theory with the neoclassical growth model to better understand labor market outcomes. Robert Shimer shows analytically and quantitatively that rigid wages are important for explaining the volatile behavior of the unemployment rate in business cycles.

The book focuses on the labor wedge that arises when the marginal rate of substitution between consumption and leisure does not equal the marginal product of labor. According to competitive models of the labor market, the labor wedge should be constant and equal to the labor income tax rate. But in U.S. data, the wedge is strongly countercyclical, making it seem as if recessions are periods when workers are dissuaded from working and firms are dissuaded from hiring because of an increase in the labor income tax rate. When job searches are time consuming and wages are flexible, search frictions--the cost of a job search--act like labor adjustment costs, further exacerbating inconsistencies between the competitive model and data. The book shows that wage rigidities can reconcile the search model with the data, providing a quantitatively more accurate depiction of labor markets, consumption, and investment dynamics.

Developing detailed search and matching models, Labor Markets and Business Cycles will be the main reference for those interested in the intersection of labor market dynamics and business cycle research.

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The Microtheory of Innovative Entrepreneurship

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An authoritative look at the microeconomics of entrepreneurship

Entrepreneurs are widely recognized for the vital contributions they make to economic growth and general welfare, yet until fairly recently entrepreneurship was not considered worthy of serious economic study. Today, progress has been made to integrate entrepreneurship into macroeconomics, but until now the entrepreneur has been almost completely excluded from microeconomics and standard theoretical models of the firm. The Microtheory of Innovative Entrepreneurship provides the framework for introducing entrepreneurship into mainstream microtheory and incorporating the activities of entrepreneurs, inventors, and managers into standard models of the firm.

William Baumol distinguishes between the innovative entrepreneur, who comes up with new ideas and puts them into practice, and the replicative entrepreneur, which can be anyone who launches a new business venture, regardless of whether similar ventures already exist. Baumol puts forward a quasi-formal theoretical analysis of the innovative entrepreneur's influential role in economic life. In doing so, he opens the way to bringing innovative entrepreneurship into the accepted body of mainstream microeconomics, and offers valuable insights that can be used to design more effective policies. The Microtheory of Innovative Entrepreneurship lays the foundation for a new kind of microtheory that reflects the innovative entrepreneur's importance to economic growth and prosperity.

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Social Identities, Relations, and Collective Action

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Recent surveys show that more than half of American entrepreneurs share ownership in their business startups rather than going it alone. Yet the media and many scholars continue to perpetuate the myth of the lone visionary who single-handedly revolutionizes the marketplace. In The Entrepreneurial Group, Martin Ruef shatters this myth, demonstrating that teams, not individuals, are the leading force behind entrepreneurial startups. This is the first book to provide an in-depth sociological analysis of entrepreneurial groups, and to put forward a theoretical framework for understanding activities and outcomes within them.

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Imitation and Innovation at a Global Bank

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In business, as in other aspects of life, we learn and grow from the examples set by others. Imitation can lead to innovation. But in order to grow innovatively, how do businesses decide what firms to imitate? And how do they choose what practices to follow? Learning by Example takes an unprecedented look at the benchmarking initiative of a major financial institution. David Strang closely follows twenty-one teams of managers sent out to observe the practices of other companies in order to develop recommendations for change in their own organization.

Through extensive interviews, surveys, and archival materials, Strang reveals that benchmarking promotes a distinctive managerial regime with potential benefits and pitfalls. He explores the organizations treated as models of best practice, the networks that surround a bank and form its reference group, the ways managers craft calls for change, and the programs implemented in the wake of vicarious learning. Strang finds that imitation does not occur through mindless conformity. Instead, managers act creatively, combining what they see in external site visits with their bank's strategic objectives, interpreted in light of their understanding of rational and progressive management.

Learning by Example opens the black box of interorganizational diffusion to show how managers interpret, advocate, and implement innovations.