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Complexity is emerging as a post-Newtonian paradigm for approaching a large body of phenomena of concern at the crossroads of physical, engineering, environmental, life and human sciences from a unifying point of view. This book outlines the foundations of modern complexity research as it arose from the cross-fertilization of ideas and tools from nonlinear science, statistical physics and numerical simulation. It is shown how these developments lead to an understanding, both qualitative and quantitative, of the complex systems encountered in nature and in everyday experience and, conversely, how natural complexity acts as a source of inspiration for progress at the fundamental level. ... Read more

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This book provides an in-depth analysis of selected methods in signal and system theory with applications to problems in communications, stochastic processes and optimal filter theory. The authors take a consistent functional analysis and operator theoretic approach to linear system theory, using Banach algebra and Hardy space techniques. The themes connecting all the chapters are questions concerning the consequences of the causality constraint, which is necessary in all realizable systems, and the question of robustness of linear systems with respect to errors in the data.

The first part of the book contains basic background on the necessary mathematical tools and provides a basic foundation of signal and system theory. Emphasis is given to the close relation between properties of linear systems such as causality, time-invariance, and robustness on the one hand and the algebraic structures and analytic properties of the mathematical objects, such as Banach algebras or Hardy spaces, on the other hand. The requirement of causality in system theory is inevitably accompanied by the appearance of certain mathematical operations, namely the Riesz projection and the Hilbert transform. These operations are studied in detail in part two. Part three relates the mathematical techniques that are developed in the first two parts to the behaviour of linear systems that are of interest from an engineering perspective, such as expansions of transfer functions in orthonormal bases, the approximation from measured data and the numerical calculation of the Hilbert transform, as well as spectral factorization.

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Complex behavior can occur in any system made up of large numbers of interacting constituents, be they atoms in a solid, cells in a living organism, or consumers in a national economy. Analysis of this behavior often involves making important assumptions and approximations, the exact nature of which vary from subject to subject. Foundations of Complex-system Theoriesbegins with a description of the general features of complexity and then examines a range of important concepts, such as theories of composite systems, collective phenomena, emergent properties, and stochastic processes. Each topic is discussed with reference to the fields of statistical physics, evolutionary biology, and economics, thereby highlighting recurrent themes in the study of complex systems. This detailed yet nontechnical book will appeal to anyone who wants to know more about complex systems and their behavior. It will also be of great interest to specialists studying complexity in the physical, biological, and social sciences. ... Read more

Customer Reviews (3)

4.5 Stars-The whole is not the sum of the parts;Excellent and scholarly
This is a very interesting book.The author demonstrates that she has command over a number of different fields.She exhibits awide ranging scholarship in this book.In a nutshell,one can categorize the major conclusions she arrives at as the whole is not the sum of the parts alone.Neither a strictly micro or macro approach to the different fields she investigates,using a complex systems framework, yields the idealized types of scientific discoveryand knowledge one finds postulatedin some philosophy of science discourses that emphasize deductive closure laws.I have one slight criticism of the book,which is why I have subtracted one half a star.The author has a deep general understanding of the Keynes-Knight distinction between risk and uncertainty in economics(and in social sciences).However,she lacks an understanding of the specifics of Keynes's approach in the A Treatise on Probability(1921;TP).She is unaware of Keynes's interval estimate approach to probability,his index,w,used to measure the completeness of the evidence ,ranging from ignorance through partial knowledge to a complete information set,and Keynes's conventional coefficient of weight and risk,which treats risk, based on the purely deductive laws of probability, as a special case.This would be a very minor criticism if she had integrated the work of D.Ellsberg(Ellsberg's 2001 book,Risk,Ambiguity,and Decision gives a modern,improved and updated version of the TP) and B.Mandelbrot into her discussions involving economics,risk,and uncertainty(Ellsberg's Ambiguity with his rho and alpha indexes and the wild versus mild risk of the cauchy distribution versus normal distribution as discussed by Mandelbrot).Unfortunately,Ellsberg's contributions are not discussed at all while Mandelbrot receives a single footnote that completely ignores his contributions to economics.She can certainly obtain a 5-star rating by bringing out a revised edition in which the original,technical, pioneering work of Keynes is covered followed by the modern and updated contributions of Ellsberg and Mandelbrot.

a fascinating book -- recommended to philosophers
Philosophers of science need to read this book:the hands-on
account of how three sciences work is a healthy
corrective to the usual practice of writing philosophy of science
without actually knowing how the science is done.

A Professional work
This is an amazing work. Sunny Auyang has written an easily comprehenedible book on applications of complexity theories to economics, biology and physics.It is a professional writing to professionals indifferent fields.One needs college level maths and some physics to fullygrasp it but she has made minimum use of mathematical symbols. Her writingflows, the examples are clear, some illuminate important issues in theapplied fields, some are just homey bits that convey an idea insightfully.A lot of depth in her philosophical explorations of the complexity ideas. I consider this to be a must for any person studying or instructing insystem thinking. ... Read more

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Customer Reviews (1)

Great Book
Sorry that my review is so small.This is a great book about the dichotomy of genes and environment and how there is no real line dividing the 2.It speaks of some of the misconceptions that way of thinking produces.It also discusses some of the common metaphors that have been used in the past relating genes to "blue prints" and the such and how these metaphors should be gotton rid of.The ingredients that go into an oransismand inheritance are many which includes genes, atmosphere, culture, and many more that she discuses.All are important in the construction of an organism and none are more important then any other.She also discuses the silliness of the nature nurture debate.I think this book and way of thinking is very important for science, social sciences and just the everyday [mis]conceptions most people in the western world have of the dualism of genetics and environment. ... Read more

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Customer Reviews (12)

The relevance of complexity theory
The book starts with a traditional approach to the game theory, in particular about the work of Morgenstern-von Neumann. This model must be related to the chaos theory for the possibility of an application to the social dynamics. The simulation of a structure based by agent can be seen also in an informatic context. The auctors adfirm that it exists different parts of human thinking able to influence the behaviour of people.

A much needed book
This is an excellent book that introduces the reader to the concept of computational models of complex adaptive systems. The language used is both simple and engaging. The authors discuss why modeling is used, and more importantly, what are its limitations. This book will not teach you to model complex adaptive systems. Instead, it will give you the knowledge necessary to appreciate the intuition behind modeling complex systems. Many of the ideas introduced are complex but the authors' writing style makes them easy to understand. The best thing about the book was the choice of examples. Although simple, each example was able to convey certain ideas that greatly enhance the reader's understanding. Anyone interested in modeling complex systems should read this book before any other.

This book is a great way to be introduced to the field
This textbook aims at introducing a relatively new and emerging scientific approach, complex adaptive systems. Simply stated, we're talking about complex systems in the sense that their dynamic is far too complex or chaotic to be modeled using analytical equations. Examples of such systems are social phenomena including immigration patterns and segregation, biological patterns such as bees behavior and others.The underlying assumption is that the system under review is too complex to be modeled using mathematical tools, and/or are too complex to conduct laboratory experiments with. The new method introduced in this book talks about modeling a very simple system of interacting entities (agents), with very simple micro behavior rules, letting the system run and observing the emerging macro-behavior of the system as a whole.

The book is a great textbook. Its flow of topics is in the correct order to taking the reader from the problem of why this approach is needed, through talking openly about the widespread criticism of this approach and tries answering it in a logical and intelligent way. It then continues to explaining what is a model and how to construct one and off to some examples that show other important corner stones of the field. I couldn't ask for a better arrangement of such book. The book is relatively easy to follow and can be used as an undergraduate textbook or for researchers who look for a good introduction to the field.

Some minor problems that I stumbled upon while reading are as follow: (1) chapter 5 is extremely important as it tries to discuss the approach's criticism, however the arguments wasn't always convincing. Specifically, I would like to see some examples of problems X that are given to the neoclassical theorists, and see some discussions on their inability to deal with them and how this approach can cope with them. (2) The research problems that are introduced are very simple (as also stated by the authors themselves), I think that another chapter with two or three examples of real problems would make this book more valuable for the more knowledgeable readers (e.g. some of Epstein works). (3) After doing a lot of reading on that topic I am still amazed to find new terminology to similar ideas I think the field will mature and be more comprehensive to newcomers if the terminology will be standardize.

Overall, this book provides a great introduction to the field, easy to follow, great arrangement of topics. Highly recommended.

Well written but could be better organized
This book is about computational models of adaptive complex systems that primarily emerge through social organization, for example voter dynamics, population clustering, bank runs...It starts with more elementary less adaptive models and builds on them to show how emergent properties can be seen and adaptive behaviour can be superior to deducible deterministic optimal points.The book is quite dense and cant be rushed through, but is readible andessentially an invitation to people not currently using the techniques of recursive system techniques in multi-agent based models.

I found this book very readable and the writing style very engaging.The authors ability to keep the subject both intuitive as well as rigorous is quite unique and I rarely read book that are as well balanced.The approach is generally to force people to look at repurcussions and then think about the dynamics that brings them about, which is a lot more sensible than working through from initial conditions the evolution of nonlinear dynamical systems.This approach is contained to examples where one builds the examples and interactive dynamics of the agents themselves rather than for arbitrary chaotic systems.

This book though is not 5 stars to me as I dont like the way it was organized.The beginning of the book was hard for me to figure out what they were talking about or who they were trying to convince.The writing was good, but I was unable to gain insight into the systems they eventually were leading the reader to consider.I finally understood what they were talking about when they mentioned sugarworld which I was familiar with.At that point, in hindsight the beginning of the book made more sense.All in all my only criticism is the conclusion type arguments about the utility of the methods before discussing an elementary example was probably unecessary.I think it would have been better start to finish by starting with examples, building up the difficulty (which they did, but just a fair way into the book) and really reinforcing the merit of the approach (which i found self revealing) at the end rather than the beginning.

Conceptually rich but unnecessarily complicated
Complexity is a hot subject. Unfortunately, the language of dynamical systems theory is advanced mathematics, which means that most of the available literature is not readily accessible to lay readers. Educated nonspecialists are left with few options aside from the occasional overview which, typically, does not delve too deeply into the subject matter. Given this state of affairs, Miller and Page's book would seem to be a godsend.

A stated aim of the book is that of providing a "clear, comprehensive, and accessible account of complex adaptive social systems" for "both academics and the sophisticated lay reader." Insofar as comprehensiveness, the authors deliver. Readers are first offered preliminary discussions on complexity in social worlds, modeling, and emergence, followed by a more detailed treatment of computational modeling as a tool for theory development and of agent-based objects as the recommended means to explore complex adaptive social systems. Then a basic framework of agent-based systems is presented, followed by discussions of unidimensional complexity models and the edge of chaos, social dynamics, evolving automata, and organizational decision making. These topics are largely illustrated with the authors' previously published models. Finally, conclusions are derived regarding the book's central theme: the "interest in between" as it pertains to complex social systems (which tend to fall in between the usual scientific boundaries). Two appendices bring up the rear: an agenda for future research in complex systems and an outline of best practices for computational modeling. The thematic coverage is ample and varied, excellent for a general introductory work on social complexity.

Insofar as clarity and accessibility are concerned, however, I find myself in disagreement with the book's blurbs. Much of the mathematical formalism has been expunged from the discussions, yes, but that by itself does not guarantee enhanced communicability. The logic of the arguments, which in this field is considerable, must now be conveyed by other means, either verbal or visual. The authors do make an effort to explain in words the basic concepts when they begin a new topic. But when they proceed to discuss an actual model, they shift gears. Instead of explaining or illustrating in detail the model's functional intricacies, they switch to summarizing their findings and present a table or figure that encapsulates the model's results. Repeated readings of the text are almost always required, but understanding does not necessarily ensue. This approach does not appear to contribute to the goal of making the models "as simple and accessible as possible."

This situation is not due to writer's oversight but to a deliberate choice. Prior to discussing their first example model (a computational version of Tiebout's model), the authors state: "Rather than fully pursuing the detailed version of the model we just outlined ... here we provide just an overview." Fateful words which amount to an announcement of their modus operandi, as the subsequent instances demonstrate. Caveat lector. The reader is also assumed to possess a working knowledge of such things as game theory, elementary combinatorics, and statistics, among others. So brush up on the basics and stay close to a search engine.

Reading this book takes time and some effort; it is not a breezy read. One never gets to see an actual piece of code or even pseudocode, which one would normally expect in an introductory book on computational modeling. The reader is left in a vacuum as to the mechanics of implementation. Still, it is a good book in terms of its conceptual content. However, the inconsistency between the stated aim of providing clarity of exposition at an introductory level and the actual product the reader interacts with detracts from the book's overall quality. It seems like we are still waiting for the canonical text on complex adaptive social systems.

Note: If you are looking for a general overview of complexity theory intended for a lay audience, I would suggest Melanie Mitchell's Complexity: A Guided Tour. It is excellent. At the other end of the spectrum, if you're heavily into power math, consider Complex and Adaptive Dynamical Systems: A Primer (Springer Complexity) by Claudius Gros. It is rigorous. ... Read more

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(Haworth Clinical Practice Press)Delivers insights on the emotional cutoff of Bowen's Family Systems Theory. With case examples, text illustrates the possibilities for bridging emotional cutoff for those trying to modify unresolved attachment in family relationships. Hardcover, softcover available and listed in approval week 2003-40. ... Read more

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Highly recommended
For anyone desiring a more in depth study of Bowen's concept of Emotional Cutoff, this book, edited by Peter Titelman, is most worthwhile.A quick glance over the table of contents, available online, shows the book to include a comprehensive survey of various areas cutoff occurs,i.e. divorce, migration, trauma survivors, and the possible long term effects. This book, as well as Titleman's Triangles, provide a greater depth of understanding and application of Bowen Theory as well as cutoff and triangles in everyday families. A very readable book.Highly recommended. ... Read more

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Steadily growing applications of game theory in modern science (including psychology, biology and economics) require sources to provide rapid access in both classical tools and recent developments to readers with diverse backgrounds. This book on game theory, its applications and mathematical methods, is written with this objective in mind.

The book gives a concise but wide-ranging introduction to games including older (pre-game theory) party games and more recent topics like elections and evolutionary games and is generously spiced with excursions into philosophy, history, literature and politics. A distinguished feature is the clear separation of the text into two parts: elementary and advanced, which makes the book ideal for study at various levels.

Part I displays basic ideas using no more than four arithmetic operations and requiring from the reader only some inclination to logical thinking. It can be used in a university degree course without any (or minimal) prerequisite in mathematics (say, in economics, business, systems biology), as well as for self-study by school teachers, social and natural scientists, businessmen or laymen.

Part II is a rapid introduction to the mathematical methods of game theory, suitable for a mathematics degree course of various levels. It includes an advanced material not yet reflected in standard textbooks, providing links with the exciting modern developments in financial mathematics (rainbow option pricing), tropical mathematics, statistical physics (interacting particles) and discusses structural stability, multi-criteria differential games and turnpikes.

To stimulate the mathematical and scientific imagination, graphics by a world-renowned mathematician and mathematics imaging artist, A T Fomenko, are used. The carefully selected works of this artist fit remarkably into the many ideas expressed in the book. ... Read more

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What do traffic jams, stock market crashes, and wars have in common?They are all explained using complexity, an unsolved puzzle that researchers believe is the key to predicting - and solving-everything from terrorist attacks and pandemic viruses right down to rush hour traffic congestion. Scientists can predict shopping habits, patterns in modern jazz, and the growth of cancer tumors. Considered by many to be the single most important scientific development since general relativity. ... Read more

Customer Reviews (7)

An interesting approach to the complexity
There is a proposition in this book that is really important for the evolution of the mathematical economy: "The system as a whole manages to self-organize itself in such a way that the fluctuations are smaller than for the case where everyone tosses a coin".(pag. 84) This means that an economy founded on the rules of Black-Scholes is less apted to understand than a theory of complexity integrated with the game theory. This fact allows to the researchers to have a better preview of the phoenomena.

An interesting walk down a single narrow path
Complexity science is a broad field with vague boundaries, so no single book can cover the whole field in depth.In this book, Neil Johnson focuses on a definition of complexity associated with a particular class of computational models, and he describes these models and their resulting behaviors at a level suitable for the general reader (somewhat detailed descriptions, but essentially no formal math).He has a PhD in physics and has himself done considerable research on these types of models (see the references at the end of the book), so his knowledge in this area is fairly authoritative.

For Johnson, a complex system has the following characteristics:

(1) A population of multiple (at least three) interacting objects or "agents" which typically form a network.These objects may be very simple, but they don't have to be.

(2) Competition among the objects for limited resources.As part of this overall competition, there can also be local cooperation within the system.

(3) Feedback processes, which give the system memory and history.

(4) Ability of the objects to adapt their strategies in response to their history.

(5) Ability of the system to interact with its environment.

(6) Self-organization of system behavior, without the need for a central controller.

(7) Emergence of non-trivial patterns of behavior, including a complicated mixture of ordered and disordered behavior.This can include chaotic behavior, as well as extreme ordered behavior (eg, traffic jams, market crashes, human diseases and epidemics, wars, etc.).

Johnson gives many examples of complex systems, and a jazz band is among the most interesting of these examples (the jazz performance is the behavior of the system).

Here are some of the key results from the models he describes:

(1) Even if the objects comprising the population of the system are complicated and heterogeneous (eg, people), this variability tends to "average out" in a way that allows the objects to be modeled as being fairly simple and homogeneous (at least as a first approximation).

(2) Due to competition, the population of objects will often become polarized into two opposing groups (eg, bears and bulls in financial markets, opposing political parties, etc.).This competition tends to reduce fluctuations in the behavior of the system.

(3) It's sometimes possible to steer the behavior of a system by manipulating a subset of the system's objects.

(4) Network structure tends to make complex systems more robust.

(5) The overall behavior of a system, and the ability of individual objects in the system obtain resources, depends on both the amount of available resources and the level of connectivity (network structure) between objects.When resources are only moderate, adding a small amount of connectivity widens the disparity between successful and unsuccessful objects, whereas adding a high level of connectivity reduces this disparity.By contrast, when resources are plentiful, adding a small amount of connectivity is sufficient to increase the average success rate and enable most objects to be successful.These patterns are consistent with what I've observed in the competition among engineering firms over the years (including during the current recession, a time of reduced resources).

(6) The behavioral outcomes of complex systems often follow a power law distribution, with smaller events being most common, but with extreme events also occurring more often than one might expect.

One of my main motivations to read this book was to get insight into how malignant tumors might be modeled as complex systems, with the hope that such models might provide clues regarding more effective ways to treat cancer.I was pleased to see that Johnson does discuss cancer at several points in the book, but I was disappointed to find that his discussion of cancer modeling is relatively superficial.Nevertheless, I'm firmly convinced that cancer is best modeled as a complex system, so I believe that much more research along these lines is (urgently) needed.

Overall, I do recommend this book.Johnson is qualified to write it, and it works well as an easily understood introduction at a level of detail suitable for general readers.However, again, keep in mind that the scope of the book is fairly narrow, so many important topics aren't mentioned at all.As a result, the book provides a good understanding of some of the trees in the forest of complexity science, but not much sense of the overall forest.For a broader introduction to complexity science, I recommend Complexity: A Guided Tour by Melanie Mitchell.

A good intro
I found this book interesting and engaging for the intelligent person who is a novice with complexity theory. It helps you appreciate the world from yet another perspective.Entertaining & thought provoking. I didn't feel floored, but I did keep with it.

A fine introduction to what Complexity is all about.
If you are unfamiliar with Complexity Theory ("The Science of Sciences") then this is a great book to start with. Neil Johnson has done an impeccable job of keeping the intricacies of Complexity within a very manageable framework that any layman can understand. Take this quote for example: "Complexity can be summed up by the phrase "Two's company, three is a crowd." In other words, Complexity Science can be seen as the study of the phenomena which emerge from a collection of interacting objects - and a crowd is a perfect example of such an emergent phenomenon, since it is a phenomenon which emerges from a collection of interacting people." The real strength of this book lies in Johnson's unsophisticated and plain approach towards Complexity Science which he couples with many real world examples. But neither does Johnson leave anything out; Self-Similarity, Fractals, Power-Laws, Networks, etc. - it's all here.

My only complaint about this book comes on page 100. Here, Johnson explains how the "six degrees of separation" network was conceived by Stanly Milgram in 1967. I am sure that Johnson knows that this was debunked by later research, but Johnson fails to mention this in the book (one only has to look to Wikipedia, Complexity: A Guided Tour by Melanie Mitchell or The Numbers Game: The Commonsense Guide to Understanding Numbers in the News, in Politics, and inLife for confirmation. I do not fault Johnson here because given the 'basic' level at which this book was written, he probably didn't feel like complicating the issue - the point he was trying to make was satisfied - and he therefore surely didn't feeling like going into the whole mess by upending the urban legend. So, with that aside, I do recommend this book as a great introduction to Complexity and recommend Complexity: A Guided Tour by Melanie Mitchell for the interested reader as a great book to continue learning about Complexity Science.

Ok, but I suspect there are better books on the subject
I enjoyed this book well enough.The subject matter was interesting and the author genuinely seems to have a way of making complex (no pun intended) subject matter very easy to understand.This is readily apparent upon reading his simple explanation of quantum physics for the lay person, which is among the best I have read (rivaling Stephen Hawking).

Where this author really has trouble is with his writing style.I'm not sure if he edited his own book, but I can't imagine this manuscript made it past a decent editor.The author uses the expression "In other words" with felonious frequency.He also uses other pet phrases, like "In particular", "It turns out", and "In short" way too often, though not as often as his all-time favorite "In other words."After a while this grated on my brain like fingernails on a chalkboard.I began finding myself mentally rewriting his sentences to make them less annoying, rather than enjoying the subject matter.

Just for kicks, I did a search for his pet phrases using the Amazon preview tool (which I am sure didn't give me all the occurrences - only the ones in the preview).The results were 111 "In other words", 120 "In particular", 66 for "It turns out", and 36 for "In short".I'd say there are easily twice this many instances of each of these.I counted "In other words" three times on one page.

Bottom line:There was nothing so compelling or unique in this book that would cause me to recommend it in spite of its shortcomings.In particular (ha!) the writing style keeps the book from being enjoyable.In short (ha ha!), I'd recommend finding a different book on Complexity Theory that gives the same information in a much less annoying way.In other words (ha ha ha!), don't buy it unless you find repetitive, useless phrases entertaining.

... Read more

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(Jessica Kingsley)Friends Hospital, Philadelphia, PA. Account of the author's professional life documenting major developments in group analysis and showing how a theory is formulated from intellectual and personal contexts and how a theory-based practice is generated. Softcover. ... Read more

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Confidently predict receiver system noise temperature using the techniques developed for NASA-JPL's Deep Space Network techniques presented, for the first time, in this groundbreaking resource. The book shows you how to analyze, design, measure and accurately evaluate the many detailed elements comprising noise temperature. After a thorough introductory overview, you delve into reflector performance issues, including material conductivity, perforations, protective coatings, the effects of terrestrial weather, and the influence of the Earth's Sun.

This in-depth reference covers mismatch error equations, in terms of both reflection coefficient magnitudes and VSWRs. Moreover, you find expert guidance in calibrating system noise temperature and antenna efficiency. The book includes easy-to-use formulas that enable you to calculate noise temperature of solid metallic reflector surfaces and of leaks in perforated plates or wire grids. What's more, you get an invaluable tutorial on using S- parameters to predict noise temperature of multiports. ... Read more

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Helping us understand our complex world, this book presents key findings in quantitative complex system science. Its approach is modular and phenomenology driven. Examples of phenomena treated in the book include the small world phenomenon in social and scale-free networks; life at the edge of chaos; the concept of living dynamical systems; and emotional diffusive control within cognitive system theory. Each chapter includes exercises to test your grasp of new material. Written at an introductory level, the author provides an accessible entry for graduate students in physics, mathematics, and theoretical computer science.

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The definitive guide to control system design

Modern Control System Theory and Design, Second Edition offers the most comprehensive treatment of control systems available today. Its unique text/software combination integrates classical and modern control system theories, while promoting an interactive, computer-based approach to design solutions. The sheer volume of practical examples, as well as the hundreds of illustrations of control systems from all engineering fields, make this volume accessible to students and indispensable for professional engineers.

This fully updated Second Edition features a new chapter on modern control system design, including state-space design techniques, Ackermann's formula for pole placement, estimation, robust control, and the H method for control system design. Other notable additions to this edition are:

• Free MATLAB software containing problem solutions, which can be retrieved from The Mathworks, Inc., anonymous FTP server at ftp://ftp.mathworks.com/pub/books/shinners
• Programs and tutorials on the use of MATLAB incorporated directly into the text
• A complete set of working digital computer programs
• Reviews of commercial software packages for control system analysis
• An extensive set of new, worked-out, illustrative solutions added in dedicated sections at the end of chapters
• Expanded end-of-chapter problems—one-third with answers to facilitate self-study
• An updated solutions manual containing solutions to the remaining two-thirds of the problems

Superbly organized and easy-to-use, Modern Control System Theory and Design, Second Edition is an ideal textbook for introductory courses in control systems and an excellent professional reference. Its interdisciplinary approach makes it invaluable for practicing engineers in electrical, mechanical, aeronautical, chemical, and nuclear engineering and related areas. ... Read more

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Complexity theory illuminates the many interactions between natural and social systems, providing a better understanding of the general principles that can help solve some of today's most pressing environmental issues. Complexity theory was developed from key ideas in economics, physics, biology, and the social sciences and contributes to important new concepts for approaching issues of environmental sustainability such as resilience, scaling, and networks.

Complexity Theory for a Sustainable Future is a hands-on treatment of this exciting new body of work and its applications, bridging the gap between theoretical and applied perspectives in the management of complex adaptive systems. Focusing primarily on natural resource management and community-based conservation, the book features contributions by leading scholars in the field, many of whom are among the leaders of the Resilience Alliance. Theoreticians will find a valuable synthesis of new ideas on resilience, sustainability, asymmetries, information processing, scaling, and networks. Managers and policymakers will benefit from the application of these ideas to practical approaches and empirical studies linked to social-ecological systems. Chapters present new twists on such existing approaches as scenario planning, scaling analyses, and adaptive management, and the book concludes with recommendations on how to manage natural resources, how to involve stakeholders in the dynamics of a system, and how to explain the difficult topic of scale. A vital reference for an emerging discipline, this volume provides a clearer understanding of the conditions required for systems self-organization, since the capacity of any system to self-organize is crucial for its sustainability over time.

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Social Change and Development is a text designed to introduce undergraduates to the study of social theory, social change and Third World development. The author compares the strengths and weaknesses of the modernization, the dependency and the world system schools of research which have dominated development studies for four decades.

The book is divided into three parts, which examine: classical and contemporary theories of social change; dependency theory; the world-system perspective and Third World industrialization. A number of books on Third World development have been published, but this book will be the only study to address the research implications of the three development theories in a comprehensive fashion and should be an essential course book for any student of development studies.

Customer Reviews (4)

Social Change and Development: Modernization, Dependency and World-System Theories (SAGE Library of Social Research)
It's an easy reference book for the understanding of development theory. It contains the three main currents of development theory including modernization theory, dependency theory and world-system theory. The book is well structured in ideas and eash to read. For those who are interested in the development theory, this book is a good choice.

Never Understood Theory So Well
Alvin So's book is the only time I ever read a book about theory and on the first time through the sentence I said "Oh! That's what that's all about!"It's sad but true that most theory books are so full of garbage-- unneeded words, grammatically convoluted sentences that go nowhere-- that you end up more confused than enlightened.

Twenty or so years of teaching at the University of Hawaii if I am not mistaken allowed So to practice again and again explaining theory to students until he'd figured out how to do it right, I only wish he'd written a book on all the other theories as well!

dry as dust but oh, so clear
This is clearly a textbook, as the publisher's writeup notes, so don't go looking for a ripping insider tell-all.That said, it's a good, solid textbook in true academic fashion: clearly laid out, systematic in structure and specific in definitions.Absolutely a dream to take notes from.
It's also a needed change that, instead of hopping around references to different theories based on politics or country, the author breaks the text into three blocks - one per major theoretical school - and lines them up chronologically by era of popularity.This of course gets a bit muddy by the end as the field in general starts to look like a free-for-all to find what works, but overall the text is blessedly clear after so much rhetoric.

An Articulate and thorough account of Development Studies
Dr. So's comparison of the three major schools of thought in Development Studies, namely Modernization, Dependency, and World Systems, is the best book of its kind currently available.While it lacks the breadth of _Society, State, and Market_ by John Martinussen, it makes up for it in the depth of its analysis.Using A limited numer of theorists, Dr. So presents a comprehensive picture of each of the schools of thought in a historical perspective.He outlines the historical and intellectual origins of each, then discusses the theory itself, follows with an examination of the classical studies in each school, and concludes with the modern studies from that intellectual tradition.If supplemented with another, broader work, this book is a perfect introduction into a daunting field that often defies understanding. ... Read more

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This book is a crystallization of the authors' work over the last twenty-five years. The book covers the latest advances in grey information and systems research, providing a state-of-the-art overview of this important field.

Covering the theoretical foundation, fundamental methods and main topics in grey information and systems research, this book includes all the elementary concepts: basic principles, grey numbers and their operations, grey equations and matrices, operators of sequences and generations of grey sequences, grey incidence analysis, grey clusters and grey statistical evaluations, grey systems modeling, grey combined models, grey prediction, grey decisions, grey programming, grey input and output and grey controls, etc.

The book will be of interest to advanced students and researchers in a wide range of fields including information and systems sciences and management sciences, and to those working in applied areas such as geo-science, engineering, agriculture, medicine, biosciences and others.

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Perfect resource for understanding grey system theory
Perfect resource for understanding grey system theory. It start from begginer level. If you want to learn grey system theory this book is certainly true adreses. Thank you authors for great contributions. ... Read more

Product Description

This book presents a "practical theory" of reactive systems, with formal foundations in Temporal Logic of Actions. The theory supports incremental development of operational, object-oriented models in steps that preserve already established properties. Models are given in an action-oriented language, and their modularity relates to aspects in aspect-oriented programming. The emphasis is on theoretical understanding of reactive behaviors, and on using "horizontal" modularity to manage their complexity.

Special chapters are devoted to the applicability of the theory to distributed and real-time systems. Incremental specification is illustrated in the book by a number of examples of varying size and complexity.

Customer Reviews (1)

Good content, written to support a course
I really bought this book because I agree with the author: reactive systems are the best way to capture the complexity of real-time sytems. The content of the book is decent, it has most of the important concepts of reactive systems. Nevertheless, the presentation is not what I wanted: it is not a top down categorization and presenation of concepts but more of a linear presentation adapted towards supporting a course on on the subject. Maybe as course supporting material the book deserves a better rating but I was not looking for course.
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