Product Description
Managing the Complex is an ambitious title - and it would be an audacious one if we were not to begin with a frank admission: to date few to none of us have a skill set which includes managing the complex. We try various things, we write about others, and we wonder about still others. When a tool, perspective, or technique comes along which seems to evoke success, we emulate it probe it and recoil at the all too often admission that it was situation and context which afforded success its opportunity, and not some quality intrinsic to the tool perspective or technique. Indeed, if the study of complexity has done anything for managers, and for those who espouse managerial theory, it is in providing a 'scientific foundation' for the notion that context matters. Those who preach abstract ideas have then to reconcile themselves to the notion that situation and embodiment matters. Those who believe in strong causality and determinism are left to wrestle with the role of chance, uncertainty, and chaos. Those who prefer to argue that men move history are confronted with the role of environment and affordances, while those who argue the reverse are left to contend with charisma, irrationality of crowds, and the strange qualities we know as emotions.A series on complex systems has less ambitious goals to contend with than this. Such a series can deal with classifications, and categories, and speak of 'noise' as if it were not the central focus of the problem. Managing the complex is about managing 'noise' or perhaps we should say it is about 'dealing with' 'accepting' 'making room for' and 'learning from' 'noise'. The articles in this volume and in volumes to come will each be considered as 'noise' by some and as 'gems' by others, but we hope that practicing managers and academics alike will find plenty of fuel to drive their personal explorations into understanding, and perhaps even managing, the complex. ... Read more

Product Description
The study of complex systems in a unified framework has become recognized in recent years as a new scientific discipline, the ultimate in the interdisciplinary fields. Breaking down the barriers between physics, chemistry, and biology and the so-called soft sciences of psychology, sociology, economics and anthropology, this text explores the universal physical and mathematical principles that govern the emergence of complex systems from simple components. Dynamics of Complex Systems is the first text describing the modern unified study of complex systems. It is designed for upper-undergraduate/beginning graduate level students, and covers a broad range of applications in a broad array of disciplines. A central goal of this text is to develop models and modeling techniques that are useful when applied to all complex systems. This is done by adopting both analytic tools, including statistical mechanics and stochastic dynamics, and computer simulation techniques, such as cellular automata and Monte Carlo. In four sets of paired, self-contained chapters, Yaneer Bar-Yam discusses complex systems in the context of neural networks, protein folding, living organisms, and finally, human civilization itself. He explores fundamental questions about the structure, dynamics, evolution, development and quantitative complexity that apply to all complex systems. In the first chapter, mathematical foundations such as iterative maps and chaos, probability theory and random walks, thermodynamics, information and computation theory, fractals and scaling, are reviewed to enable the text to be read by students and researchers with a variety of backgrounds. ... Read more

Customer Reviews (9)

beautifully written and highly useful
This is a beautifully written and thought-provoking work that presents the field of complex systems in a unified manner. The writing is highly engaging and stimulating with a broad range of topics. The material is pitched at just the right level, focusing on the concepts without getting buried in unnecessary details, while avoiding superficiality. I highly recommend this excellent book.

The worst side of normal science
The book is a tour around the paradigms used by scientists in
Complex Systems. While normal science is about using and re-using the paradigms without much creativity or true aportation to knowledge or understanding, the situation is worse in complex systems, since, as an emerging area it has multiple (competing?) paradigms, to the point that it is not possible to define a "complex system" in a form that encompases all the paradigms. The book certainly does not solve this problem, yet the author acknowledges the difficulty present in saying what a complex system is.
Complex systems is not an area of research but a community of researchers united by their interests.
The book is then a compilation of the "how to" and the believes for each paradigm, several of them carry very little science and have left the idea of "refutation" burried under piles of meaningless papers. Not surprissingly, some authors claim that complex systems is a postmodern scienceComplexity and Postmodernism: Understanding Complex Systems. And truly, the complex systems of Bar-Yam are only possible after we have buried reason and have accepted that science has nothing to do with truth.
Too much for me, not a book I recommend to my students.

Perpetuates the usual myths
that information is the opposite of entropy which is a measure of disorder or uncertainty. However because this book is about complexity and not information per se, I will only briefly refer to his mistakes with the latter as I have explained them further in other reviews that are specifically on that topic.

Shannon's information rate from communications theory, R, is an entropy like formula but most critically it is a state function difference of the uncertainty reduction to a recognizer after a measurement. Entropy is not a proper measure of disorder or uncertainty; the 2nd law of entropy increase of the universe applied long before there were any observers. It is a measure of the dispersal of energy. Going back in time is not going back to perfect order, but quite the opposite. I have not seen proper definitions in any book but there are PhD level articles available on the internet with proper definitions such as the Principia Cybernetica Web and molecular biologist Dr Thomas Schneider's website. Biologist Richard Dawkins also has an accurate short article on the internet. Most physicists have the definitions wrong unfortunately and believe information evolved before life, which is false. (A recognizer is required, whether a ribosome or mind etc.) Instead a better definition of complexity than the present author offers would indicate that the universe has increased in complexity through gravitational clumping (among other things). By making the mistake then the physicists and present author believe maximum information is randomness or equilibrium. This is the definition of algorithmic complexity.

As the author adapts algorithmic theory to his complexity profile he arrives at formulas that are observer dependant: "the complexity profile [is] the length of the description [of] the error allowed [as] the description increases." This is of little or no practical use. Again the universe has grown in complexity (or at least in pockets or we wouldn't be here) without relying on the degree of focus of any observer. A crystal is highly ordered relative to say a human cell whose complexity is a result of a multitude of interactions of chemical agents and macro molecules. This is where his analysis falls silent, in fact wrong. He says (page 741) "short-range correlations decrease the microstate complexity..." Well that's because he has a flawed method of using statistical mechanics. There is likely no universal complexity algorithm. Consider that a single gene can yield up to thousands of different proteins. One should be wary however of any formula that treats correlations as reduced complexity! Again the crystal vs the cell!

However there are ways of measuring the critical biological requirement of interactions that in fact increase complexity, the opposite of equilibrium statistical mechanics, a flawed tool. For instance in a recent article at lanl.arXiv.org, authors Edwin Wang et. al. apply Pearson's correlation coefficient to show that "genes with higher cis-regulation complexity are more coordinately regulated by transcription factors at the transcriptional level and by micro RNA's at the post-transcriptional level. This is a potentially novel discovery of a mechanism for coordinated regulation of gene expression...We found a positive correlation between these twogroups of transcriptional regulators... " Measures of correlations are key in studying biological complexity and are not based on an observer's focus ability.

For a layman's guide to the issue of correlations for life see Irun Cohen's book 'Tending Adam's Garden' (though it has no quantitative aspect).

Interesting but incomplete
That physical systems are complex has been acknowledged for centuries, but only in recent decades has the scientific community, especially physicists and biologists, directly confronted complexity. This book discusses complex systems from the dynamical systems perspective, and as such can be read by physicists, mathematicians, and mathematical biologists. Biologists in particular will find the discussion of `emergence' the most important one, especially systems biologists. Physicists and mathematicians who study dynamical systems tend to not be concerned with their origins, whether they are in biology or some other area. But physicists do concern themselves with the experimental relevance of dynamical systems, unlike mathematicians who are sorely concerned with their formal properties, and do not care at all if they can find expression in the real world. But it goes without saying that the theory of complex systems has found application in finance, genetic engineering, cryptography, network engineering, and many other areas. This book gives a good overview of the techniques used to study complex systems, and can be read by anyone with the necessary mathematical preparation, consisting of probability theory and elementary calculus.

Systems that are simple can become complex by only a slight alteration in their configuration. The gravitational three-body system in classical mechanics is a good example of this. The dynamics of two objects interacting gravitationally can be solved explicitly, but the system consisting of three bodies cannot. The complexity in these two cases is measured by the availability of solutions to the dynamics of the system. The author is very aware that more involved measures of complexity are needed and he gives examples of these in the book. Mathematical techniques from probability and statistics are of course used throughout the book to frame these measures more quantitatively. This reflects the author's stated strategy throughout the book, namely to describe the essential characteristics of a class of systems, and employ statistical techniques to find the properties and behaviors of these systems.

The concepts of emergence and complexity are fundamental to a study of complex systems, the author argues and early on in the book he clears up some of the confusions behind the use of these terms in the scientific literature. A `complex system' is one which is constructed from many components and whose behavior cannot be determined from the behavior of these components, i.e. the behavior of the system is `emergent.' The `complexity' of a system, on the other hand, is the amount of information needed to describe the system. This is a somewhat subtle definition, and quite a few proposals have been put forward in the literature for measuring complexity. The author settles on a familiar method, the `entropy' for measuring complexity, but with a warning to the reader that the calculation of the entropy is dependent on the particular length or time scale over which the system is observed. For extremely long time scales (of observation), one can get away with describing systems as always in equilibrium. In this case the entropy would be maximum but the system would not be viewed as being complex. For very short time scales (of observation) , the entropy of the system is very small but due to the ability to observe the microscopic dynamics of the system it would be viewed as highly complex.

These considerations lead the author to introduce the concept of a 'complexity profile' of a system, which he discusses at some length in the last pages of the book. The complexity profile is designed to study the the dependence of complexity on both length and time scales. The concept is dependent on the notion of a sequence of observers that are ordered according to their ability to distinguish microstates. The author calculates the complexity profile of the ideal gas and shows that the complexity of a microstate for this case is simply the entropy, but as the number of microstates with a given region increases, the complexity approaches zero. Other examples of the complexity profile are discussed, one being for observers that only measure the positions of particles and not the momentum. The author also studies the connection between the complexity profile and the predictability or chaotic behavior of the system, where chaotic systems are viewed as being ones where information from a particular scale can be transferred to a larger scale, as contrasted with dissipative systems where information on a large scale is transferred to a smaller scale. The author gives various arguments and calculations that illustrate the difference in complexity profiles between chaotic systems and those of conservative, nonchaotic systems. The discussion is fairly convincing but if the complexity profile is important in complex systems, its defintion and properties should have been included at the beginning of the book, and serve as a central theme behind the discussions throughout the entire book. As it stands the complexity profile comes across as a concept that is purely ancillary to the study of complex systems. It certainly does not appear to be indispensable in discussing irreversibility of physical systems, this problem still being the most pressing one in statistical mechanics and is still hotly debated at the present time.

How complicated are we?
This book is designed as a text to introduce graduate students in science to the concepts and methods in the ``science of complexity'' which comprises studies in mathematics, physics, chemistry, biology, computer science, sociology, psychology, economics, anthropology, and philosophy. Written from the perspectives of a physicist, definitions are informal; thus a concise definition of a complex system is not given. The concept of a complex system is introduced through examples, and informally described as having ``a large number of interacting parts'' although ``even a few interacting objects can behave in complex ways.'' More precisely, complexity is defined as ``the amount of information necessary to describe a system.'' Another key concept is the phenomenon of emergence which arises when ``the collective behavior [of a complex system] is not readily understood from the behavior of its parts.''

Dynamics of Complex Systems opens with a long chapter (278 pages) of ``introduction and preliminaries'' which surveys iterative maps; thermodynamics and statistical mechanics; activated processes (glasses); cellular automata; statistical fields; computer simulations; information theory; computation; and fractals, scaling and renormalization. It is suggested that this chapter can serve as the basis for a one-semester course. This introductory chapter is followed by eight chapters devoted two each to four different subjects: neural networks, protein folding, biological evolution, and human civilization. In each of these pairs of chapters, the first is more detailed and the second more general. Thus the first of the two chapters on neural networks describes neural network models (Hopfield's attactor models) whereas the second discusses the phenomenon of sleep and models of mind, with similar divisions of labor in the pairs of chapters on protein folding and on biological evolution. In the final chapter, it is noted that ``human civilization is more complex than we are as individuals.''

Alwyn Scott
http://personal.riverusers.com/~rover/ ... Read more

Product Description

Complex systems have become ubiquitous and are essential to today’s society. The design of reliable complex systems and the determination of their availability are therefore very important tasks for managers and engineers. These tasks, however, can be extremely difficult to achieve, due to the fact that current analytical methods are often too complicated, time-consuming, inefficient, or even inappropriate, when dealing with real-life systems.

Simulation Methods for Reliability and Availability of Complex Systems discusses the use of computer simulation-based techniques and algorithms to determine reliability and availability (R&A) levels in complex systems, and to support the improvement of these levels both at the design stage and during the system operating stage. It presents current best practice in the field, as well as:

• sharing theoretical or applied models and decision support systems that make use of simulation to estimate and to improve system R&A levels;

• forecasting emerging technologies and trends in the use of computer simulation for R&A; and

• proposing hybrid approaches to the development of efficient methodologies designed to solve R&A-related problems in real-life systems.

Dealing with practical issues, Simulation Methods for Reliability and Availability of Complex Systems is designed to support managers and system engineers in the improvement of R&A, as well as providing a thorough exploration of the techniques and algorithms available for researchers, and for advanced undergraduate and postgraduate students.

Product Description

With their ability to cross traditional boundaries and achieve a level of functionality greater than their component elements, mega-systems have helped corporations and government organizations around the world resolve complex challenges that they otherwise couldn’t address with stand-alone systems. Engineering Mega-Systems: The Challenge of Systems Engineering in the Information Age provides a clear understanding of the engineering of this class of systems—a process that demands consideration of increasing program scale and the rapid change of underlying technologies.

Written by Renee Stevens, a Senior Principal Engineer at The MITRE Corporation with decades of experience analyzing, engineering, and acquiring large-scale systems for the U.S. Department of Defense and other government agencies, this book explains how the engineering of mega-systems is inherently different from that of large-scale monolithic systems. It supplies the vocabulary and framework needed to explore the issues relevant to mega-systems. This framework then evolves into the Profiler diagnostic tool that helps　you understand the nature and context of the system at hand and, on that basis, select the most appropriate processes, tools, and techniques.

Stevens examines commercial and government applications of mega-systems to provide insight into the contemporary challenges of engineering these systems in three critical dimensions: engineering processes, management processes, and the larger context in which these systems are developed and deployed. Complete with two case studies in engineering mega-systems that illustrate valuable lessons learned and highlight emerging practices, this book supplies the understanding and the tools needed to begin engineering, characterizing, and acquiring mega-systems across multiple dimensions.

Product Description

Written for students and professionals in the fields of biomedical engineering, systems biology, biophysics, and physiology, this unique reference covers complexity issues within living systems. Topics explored include human responses to coping with complex systems, the Law of Unintended Consequences, the relation of complexity to evolution, the complexity inherent in invertebrate immune systems, and the complexity inherent in economic systems. A comprehensive glossary is included to help readers with acronyms and terms relating to complex, nonlinear biological systems. Also included are dynamic models and homework questions to further aid in understanding.

Product Description

Autonomy Oriented Computing is a comprehensive reference for scientists, engineers, and other professionals concerned with this promising development in computer science. It can also be used as a text in graduate/undergraduate programs in a broad range of computer-related disciplines, including Robotics and Automation, Amorphous Computing, Image Processing, Programming Paradigms, Computational Biology, etc.

Part One describes the basic concepts and characteristics of an AOC system and enumerates the critical design and engineering issues faced in AOC system development. Part Two gives detailed analyses of methodologies and case studies to evaluate AOC used in problem solving and complex system modeling. The final chapter outlines possibilities for future research and development.

Numerous illustrative examples, experimental case studies, and exercises at the end of each chapter of Autonomy Oriented Computing help particularize and consolidate the methodologies and theories presented.

Product Description
Deeply rooted in fundamental research in Mathematics and Computer Science, Cellular Automata (CA) are recognized as an intuitive modeling paradigm for Complex Systems. Already very basic CA, with extremely simple micro dynamics such as the Game of Life, show an almost endless display of complex emergent behavior.Conversely, CA can also be designed to produce a desired emergent behavior, using either theoretical methodologies orevolutionary techniques. Meanwhile, beyond the original realm of applications - Physics, Computer Science, and Mathematics – CAhave also become work horses in very different disciplines such as epidemiology, immunology, sociology, and finance. In this context of fast and impressive progress, spurred further by the enormous attraction these topics have on students,this book emerges as a welcome overview of the field for its practitioners, as well as a good starting point for detailed study on the graduate and post-graduate level. The book contains three parts, two major parts on theory and applications, and a smaller part on software. The theory part contains fundamental chapters on how to design and/or apply CA for many different areas. In the applications part a number of representative examples of really using CA in a broad range of disciplines is provided - this part will give the reader a good idea of the real strength of this kind of modeling as well as the incentive to apply CA in their own field of study. Finally, we included a smaller section on software, to highlight the important work that has been done to create high quality problem solving environments that allow to quickly and relatively easily implement a CA model and run simulations, both on the desktop and if needed, on High Performance Computing infrastructures. ... Read more

Product Description

Without standardized construction elements such as nuts, bolts, bearings, beams, resistors and the like, the design of physical equipment is hopelessly inefficient, and engineers are continually bogged down with re-designing these elements over and over again. The same can be said for the domain of ideas and performance requirements. Only through a process of standardization of the corresponding functional elements will systems engineering truly live up to its potential of increased efficiency and quality.

Designing Complex Systems: Foundations of Design in the Functional Domain introduces students and practitioners in the field of system design to a particular methodology that addresses design issues in a rigorous and consistent top-down fashion. It also reassesses the characteristics of engineering and its place within the field of intellectual activity, in particular, examining the creative aspects of design as reflected in the difference between engineers and technicians.

Erik W. Aslaksen brings forty years of experience to the table with this groundbreaking work. He examines how the concept of value can provide a quantitative measure of that wider interaction of the engineered object with its environment. With its forward-looking approach and holistic perspective, this volume is sure to advance the field of knowledge of systems engineering for years to come.

Product Description

In recent years, scientists have applied the principles of complex systems science to increasingly diverse fields. The results have been nothing short of remarkable: their novel approaches have provided answers to long-standing questions in biology, ecology, physics, engineering, computer science, economics, psychology and sociology. "Unifying Themes in Complex Systems" is a well established series of carefully edited conference proceedings that serve the purpose of documenting and archiving the progress of cross-fertilization in this field.

About NECSI: For over 10 years, The New England Complex Systems Institute (NECSI) has been instrumental in the development of complex systems science and its applications. NECSI conducts research, education, knowledge dissemination, and community development around the world for the promotion of the study of complex systems and its application for the betterment of society. NECSI hosts the International Conference on Complex Systems and publishes the NECSI Book Series in conjunction with Springer Publishers.

Product Description
Nine innovative methods to think outside the box and solve complex system problems

Managing Complex Systems provides specific tools and guidance needed to be a more creative and innovative thinker. Following the author's methodology, the reader will be better able to devise and implement nontraditional solutions to seemingly intractable complex problems. By challenging the reader to think in new and creative ways, the book offers a road map to success, whether measured in terms of competitive advantage, greater market share, improved productivity, or higher profits, all based upon better solutions to difficult problems.

The first four chapters set the foundation for creative thinking by exploring the nature of large-scale systems and complexity, thinking inside and outside the box, and examples of how an inventive mind solves problems in both management and scientific domains. Subsequent chapters address nine focused methods that the author has formulated to help the reader think outside the box:
* Broaden and generalize
* Crossover
* Question conventional wisdom
* Back of the envelope
* Expanding the dimensions
* Obversity
* Remove constraints
* Thinking with pictures
* Systems approach

Real-life examples are provided for each method that demonstrate how the approach enhances problem solving and decision making in system development and management. Following the discussion of the nine methods, the author examines group decision making as well as additional creative thinking procedures devised by other researchers, including references that assist in exploring these methods in greater detail. The author ends with a wrap-up chapter that includes a test to help readers practice their tendencies toward creative thinking skills and action with respect to solving real-world problems.

The nine methods discussed in this book have broad applicability and can be used successfully by managers with a wide range of responsibilities in business and technology. For anyone who is tired of the same old approach with the same old results, this book is essential reading. ... Read more

Customer Reviews (3)

Systems Engineering: Intermediate to advanced level
It is a great book, although I would not suggest as a first book on systems engineering and/or systems management (in this case I'd recommend the other book of the same author). Has some material on Complex and Systems of Systems, Software Reuse, and Off The Shelf Systems, and Managing its development.

The book has two rather interesting chapters:

i) 14 - "THINKING IN GROUPS": where it presents the differences of individual thinking as opposed to group thinking, as well as some commonly used methods. Unfortunately this chapter only scratches the surface of each topic (Dr. Eisner, please write a book on this subject!!); and
ii) 15 - "WIDENING THE CIRCLE": where it presents some approaches (as the author refers), such as: TRIZ, Thinking like Leonardo, The Art of Problem Solving, Einstein, Breakthrough Thinking, Creativity, among others.

It has no exercises at the end of each chapter.

I recommend it for students, managers and practitioners.

Hope this helps!

worse than unfortunate
As a student who had this as a textbook, I can tell you that this is the last book you want to read IF your goal is managing complex systems.In point of fact, this book is nothing less than an "in-the-box" approach to identifying that which is out of the box.Can you hackney the hackneyed?Eisner has proven it so...

Do not buy this book, even if it is in your syllabus.

Wise advices for dealing with complexity
Professor Eisner argues that dealing with complexity is a paramount for the modern technological organization. By having a huge academic and business experience Professor Eisner presents 9 ways of think out sides the box, which means a broad way to look at problems brought about by complexity. Written in a almost informal language this book is pleasant reading that will help a great deal those who must overcome complexity. ... Read more

Product Description
Have you ever wondered how birds flock or forest fires spread? For thousands of years people - from DaVinci to Einstein - have created models to help them better understand patterns and processes in the world around them. Computers make it easier for novices to build and explore their own models - and learn new scientific ideas in the process. Adventures in Modeling introduces you and your students to designing, creating, and investigating models in StarLogo. Computer modeling, the use of computer programs to simulate complex, dynamic systems or events (like population growth or environmental conservation), is a powerful learning tool that is finding a rapidly growing audience among teachers in middle and high school science and mathematics classes, especially since the NCTM Standards 2000 advocates its use in the curriculum. This valuable resource: Provides educators with a rich and accessible introduction to the use of computer modeling in the classroom using the popular StarLogo computer programming language; Takes readers step-by-step through the process of using computer models to simulate complex relationships; Shows how and why computer modeling can lead to powerful and enduring learning outcomes for all students. Provides explicit links between various state and national math and science content standards and the use of computer models, to enable educators to see how this work may enhance standards-based instruction; As computer use gains in currency and value in the middle and high school classroom, Adventures in Modeling will give teachers and students a very effective way to build curiosity and boost learning outcomes in a standards-based curriculum. ... Read more

Customer Reviews (5)

Good Intro to Topic...but Doesn't Extend Well to NetLogo
I am intigued with and have been trying to explore 'emergent behavior' for several months.I am especially enjoying trying to learn and explore with NetLogo. It is the upgraded and much more capable big brother to StarLogo (which this book is about).The main proble that I'm having is that are no printed books that either provide a good reference to the NetLogo lanuage nor any good printed tutorials. I find the electronic versions good but too hard to use...especially while trying to program in NetLogo on the computer.

So I was thinking that this beek looked like a pretty good tutorial on applying StarLogo and, after all, StarLogo is the little brother to NetLogo...so I decided to give it a try.The organization and approach to developing skills with StarLogo are superb and I've enjoyed it a lot.Unfortunately, NetLogo is such an advancement over StarLogo that the StarLogo examples and exercises do not translate well (or at all) to NetLogo.So, in that regard, it was a bust for me.

But if you use (or are interested in getting and using StarLogo) then I highly recommend this book.However, if you're interested in NetLogo,I think you'll likely be disappointed.

Turtles for all
This book is a great guide to taking the somewhat difficult ideas explored in Mitchel Resnick's book "Turtles, Termites, and Traffic Jams" and implementing them with students.Adventures in modeling can be used alone but, for any teacher who wants to use this book in a computer class, it is helpful to read the other book first.The activities and challenges here are reasonable for students from college down though middle school.I know of one teacher who has even successfully used these activites with pre-teens.

Good book but not perfect...
The book is good overall but I felt they need to use more carefully thought out examples and not try to push an 'agenda'.
It is as if the author(s) are trying to make an issue over creation vs evolution. In the very beginning chapter, they make an invalid example by comparing evolution vs creation to central control vs decentralized systems. This is a quote from the book, "This tendency to assume centralized control, which we call the centralized mindset, makes it difficult for people to understand the workings of many phenomena in the world. The recurrent questioning of evolutionary theories is another example: When people see complex living systems in the world, they assume that someone or something must have explicitly designed them; instead, these livings systems are the products of millions of incremental changes over time."

Great guide to modeling systems!
This is a great book for anyone interested in modeling dynamic systems. The authors provide wonderful background theory as a basis for building computer simulations. The simple step-by-step instructions guide you through the process of creating your own simulations using StarLogo. This book is an interesting, easily understandable beginner's manual and comes with all the software you need. It's a great way to teach yourself or other people how to program a simulation. I love the turtles!

Excellent guide to modeling systems!
This is a great book for people intereted in modeling systems behavior. The authors give an excellent background summary of the theory involved in StarLogo. The program given with the CD is easy to install and use. The book takes you step by step through thinking about and creating your own computer simulation in an easy to understand manner. There's lots of support for any technical difficulties you might have and good examples of what you can do with the program. I highly recommend it to everyone. ... Read more

Product Description

The main challenge faced by designers of self-organizing systems is how to validate and control non-deterministic dynamics. Over-engineering the system may completely suppress self-organization with an outside influence, eliminating emergent patterns and decreasing robustness, adaptability and scalability. Whilst leaving too much non-determinism in the system’s behaviour may make its verification and validation almost impossible. This book presents the state-of-the-practice in successfully engineered self-organizing systems, and examines ways to balance design and self organization in the context of applications.

As demonstrated throughout, finding this balance helps to deal with diverse practical challenges. The book begins with the more established fields of traffic management and structural health monitoring, building up towards robotic teams, solving challenging tasks deployed in tough environments. The second half of the book follows with a deeper look into the micro-level, and considers local interactions between agents. These interactions lead towards self-modifying digital circuitry and self-managing grids, self-organizing data visualization and intrusion detection in computer networks, immunocomputing and nature-inspired computation, and eventually to artificial life. The case studies described illustrate the richness of the topic and provide guidance to its intricate areas.

Many algorithms proposed and discussed in this volume are biologically inspired and readers will also gain an insight into cellular automata, genetic algorithms, artificial immune systems, snake-like locomotion, ant foraging, birds flocking and mutualistic biological ecosystems, amongst others. Demonstrating the practical relevance and applicability of self-organization, this book will be of interest to advanced students and researchers in a wide range of fields.

Product Description

This book presents the concepts needed to deal with self-organizing complex systems from a unifying point of view that uses macroscopic data. The various meanings of the concept "information" are discussed and a general formulation of the maximum information (entropy) principle is used. With the aid of results from synergetics, adequate objective constraints for a large class of self-organizing systems are formulated and examples are given from physics, life and computer science. The relationship to chaos theory is examined and it is further shown that, based on possibly scarce and noisy data, unbiased guesses about processes of complex systems can be made and the underlying deterministic and random forces determined. This allows for probabilistic predictions of processes, with applications to numerous fields in science, technology, medicine and economics. The extensions of the third edition are essentially devoted to an introduction to the meaning of information in the quantum context. Indeed, quantum information science and technology is presently one of the most active fields of research at the interface of physics, technology and information sciences and has already established itself as one of the major future technologies for processing and communicating information on any scale.

This book addresses graduate students and nonspecialist researchers wishing to get acquainted with the concept of information from a scientific perspective in more depth. It is suitable as a textbook for advanced courses or for self-study.

Customer Reviews (1)

physics approach
Self-Organization is not the function given to a neural net (although theyhave taken it) used for pattern recognition, nor is it a cult somewhere inGermany. After following Haken's work for 6-8 years it is good to see asummary of sorts. Haken was working with self-organizing similarities inthe 80's when unification ideas were rampant. Haken uses this same analogyby equating the basic form to stochastic differential equations. It issomewhat easier to approach the differential equation as a dynamical systemdriven by random vector fields of which the Ito form (stuff Kalman filtersare made of) is a special case. Without going into martingales Brownianmotion ergodic theorems of Markovian processes Haken does give a convincingargument for what he terms MIP (max. information principle) and informationgain in the system.Linguistically converted this means that the processmay be likened to a diffusion process with thermodynamic stuff. This pavesthe way for the transfer of information from one organization structurediffusion (in the wave) front to another. It seems to me, however, that amuch simpler proof would be; show the parallel between Haken's basic formand the Lax form of an evolution equation. Establish relationship toHirota's derivatives. Usually represented and manifested as theKorteweg-deVrie equations the polynomials groups describing the equationeasily convert to Hiroto derivatives. Show fundamental relationship ton-solitons and vertex operators, establish relationship to Heisenberg andClifford algebras, show Fock representation of Bosons using Maya diagrams,show Boson-Fermion correspondence. Complex variables, infinite dimensionalalgebras, Fermions, and Bosons; The principle of superposition does notapply to non-linear waves, despite that there exists exact solutionscontaining an arbitrary number of parameters suggesting an infinitedimensional transformation group acting on spaces of solutions ofintegrable systems (Reaction-diffusion as one type shock waves as another).Because of this self-symmetry in scales of complex polynomials,transformational methods work well. If waves are information densities andan increase in entropy is an increase of information Hiroto's derivativeswould give the mathematical link showing the degrees of informationtransfer between types of diffusion front (waves) and another. Thesimilarity of scales, the repeating nature, then transfer of one wave front(diffusion) through another without annihilation. ... Read more

Product Description
There is a need for more inclusive holistic approaches to identify and analyze safety-related system risks. Systems are becoming increasingly more complex, diverse, and vastly distributed. Conventional approaches of conducting hazard analyses and risk assessment do have limitations. This book addresses some of these limitations and a number of inclusive approaches are discussed, which can be applied against the limitations. The book emphasizes scenario-driven hazard analysis as a means to conduct more holistic analysis.

It discusses safety analyses of large complex systems; which are comprised of software, firmware, hardware, the human and the environment.  “System thinking” in problem solving is emphasized throughout the book. The book is comprised of three parts. The first part Risk identification covers topics including understanding risk, evaluating safety, and scenario-driven hazard analysis. The second part Risk elimination and control addresses eliminating risk and provides hazard control methods, techniques, and applications. Finally managing safety-related risks covers key concepts and observations associated with a safety management and other topics including making safety-related decisions.

At the end of each chapter there are “Questions and Topics for Further Discussion”, which enables the book to be used for graduate and undergraduate education, and specialized courses or instructional development.    ... Read more

Product Description

In Risk Analysis of Complex and Uncertain Systems acknowledged risk authority Tony Cox shows all risk practitioners how Quantitative Risk Assessment (QRA) can be used to improve risk management decisions and policies. It develops and illustrates QRA methods for complex and uncertain biological, engineering, and social systems – systems that have behaviors that are just too complex to be modeled accurately in detail with high confidence – and shows how they can be applied to applications including assessing and managing risks from chemical carcinogens, antibiotic resistance, mad cow disease, terrorist attacks, and accidental or deliberate failures in telecommunications network infrastructure.  This book was written for a broad range of practitioners, including decision risk analysts, operations researchers and management scientists, quantitative policy analysts, economists, health and safety risk assessors, engineers, and modelers.

Customer Reviews (2)

Comprehensive and example-laden - Every issue is touched
I have used Cox's research in my own recent book, .He is a colleague who has written numerous articles on this topic and has combined those along with his practical experience to write this critical book.It touches on every major issue in the area of risk assessment - which includes many issues that other risk assessment authors either dare not touch or are simply unaware of.

The most impressive feature of this book is the litany of examples in literally every chapter.He draws on a wide spectrum of different fields including public health, airline safety, engineering risks and terrorism.It is an extremely comprehensive treatment of quantitative risk assessment methods and each method is backed up with practical applications.

For me, the most important part of this book is the large section Cox dedicates to "Avoiding Bad Risk Analysis".He systematically debunks what I think are the most popular methods in business today.I even used his phase "Worse than Useless" to describe such methods in my book (properly attributed, of course) because nothing else says it better.

But Cox doesn't just endorse every method used in quantitative risk assessment.He is careful to point out the potential flaws and proposes specific solution.Debunking these popular methods is the first step.The second step is adopting an improved quantitative approach to risk assessment.This book covers all of it.

Highly recommended.

real risk analysis
This is an excellent, approachable read for any risk manager; understanding its examples requires only elementary probability, statistics and calculus, though the foundations are much deeper.The author uses direct language, and does not hesitate to declare a fashionable risk analysis technique "worse than useless."The author shows how not to do risk analysis, using simple but devastating examples to illustrate the weaknesses of prioritized investments, subject matter expert opinion, risk matrices and qualitative risk assessments, and the independence assumption.Then, case studies present constructive examples of good practice.Refreshingly, this text clearly distinguishes between threats from Mother Nature, and those posed by an intelligent adversary.There is unevenness, because this is an edited ensemble of papers originally published in a variety of technical journals; however, this is also a strength, because the appeal and scholarship underlying biological, engineering, and social science examples is broad.This is not a how-to guide, and won't help fill in a blank page risk analysis; however, this is an excellent source for the skeptical consumer of contemporary risk management advice and products, and hopefully will have some influence with policy makers who are the source of simplistic and dangerous guidance.

Gerald G. Brown
Distinguished Professor of Operations Research
Naval Postgraduate School
National Academy of Engineering
INFORMS Fellow
... Read more

Product Description

"Control of Complex Systems: Structural Constraints and Uncertainty" focuses on control design under information structure constraints, with a particular emphasis on large-scale systems. The complexity of such systems poses serious computational challenges and severely restricts the types of feedback laws that can be used in practice. This book systematically addresses the main issues, and provides a number of applications that illustrate potential design methods, most which use Linear Matrix Inequalities (LMIs), which have become a popular design tool over the past two decades. Authors Aleksandar I. Zecevic and Dragoslav D. Siljak use their years of experience in the control field to also:

• Address the issues of large-scale systems as they relate to robust control and linear matrix inequalities
• Discuss a new approach to applying standard LMI techniques to large-scale systems, combining graphic-theoretic decomposition techniques with appropriate low-rank numerical approximations and dramatically reducing the computational effort
• Providing numerous examples and a wide variety of applications, ranging from electric power systems and nonlinear circuits to mechanical problems and dynamic Boolean networks

"Control of Complex Systems: Structural Constraints and Uncertainty" will appeal to practicing engineers, researchers and students working in control design and other related areas.

Product Description
The systems movement is made up of many systems societies aswell as of disciplinary researchers and researches, explicitly orimplicitly focusing on the subject of systemics, officially introducedin the scientific community fifty years ago. Many researches indifferent fields have been and continue to be sources of new ideas andchallenges for the systems community. To this regard, a very importanttopic is the one of EMERGENCE. Between the goals for the actual andfuture systems scientists there is certainly the definition of ageneral theory of emergence and the building of a general model ofit.The goal of this book, is to recall to the systems community animportant challenge to be dealt with in the immediate future: thestudy and characterization of general features of what is commonlyqualified as `emergence', chiefly in complex systems such asbiological and cognitive ones. Such a topic was a fundamental one atthe very beginning of the systemic movement, and to it the foundingfathers, such as Von Bertalanffy, Ashby and Von Foerster, devoted mostefforts. In more recent times, however, the interests shifted towardsan empirical study of systemic properties characterizing humanorganizations, and the subject of emergence was partly abandoned.Notwithstanding, the understanding of what is emergence, and of thecircumstances which allow for its occurrence within a complex system,is of crucial importance for systemics. Namely all systemic properties-- the ones which allow a system to behave as a whole and not asan aggregate of constituents -- are just emergent properties. ... Read more

Product Description
Derived from the 2001 Santa Fe Institute Conference, "The Economy as an Evolving Complex System III," represents scholarship from the leading figures in th area of economics and complexity.The subject, a perennial centerpiece of the SFI program of studies has gained a wide range of followers for its methods of employing empirical evidence in the development of analytical economic theories.Accordingly, the chapters in this volume addresses a wide variety of issues in the fields of economics and complexity, accessing eclectic techniques from many disciplines, provided that they shed light on the economic problem.Dedicated to Kenneth Arrow on his 80th birthday, this volume honors his many contributions to the Institute.SFI-style economics is regarded as having had an important impact in introducing a new approach to economic analysis. ... Read more

Product Description
THE PROJECT MANAGEMENT CLASSIC-REVISED AND EXPANDED

Now Includes Downloadable Forms and Worksheets

Projects are becoming the heart of business. This comprehensive revision of the bestselling guide to project management explains the processes, practices, and management techniques you need to implement a successful project culture within your team and enterprise. Visualizing Project Management simplifies the challenge of managing complex projects with powerful, visual models that have been adopted by more than 100 leading government and private organizations.

In this new Third Edition, the authors-leading thinkers and practitioners in the field-keep you on the cutting edge with a sophisticated approach that integrates project management, systems engineering, and process improvement. This advanced content can help take your career and your organization well beyond the fundamentals.

New, downloadable forms, templates, and worksheets make it easy to implement powerful project techniques and tools.

Includes references to the Project Management Institute Body of Knowledge and the INCOSE Handbook to help you pass:

• The Project Management Professional Certification Exam
• The INCOSE Systems Engineer Certification Exam (CSEP)

"I recommend this book to all those who aspire to project management [and] those who must supervise it."
—Norman R. Augustine, former chairman and CEO Lockheed Martin Corporation

"The importance of this excellent book, able to encompass these two key disciplines [systems engineering and project management], cannot be overemphasized."
—Heinz Stoewer, President, INCOSE ... Read more

Customer Reviews (7)

Nice to have
In my opinion the title does not cover the contents. The contents is by far more textual than visual. I was expecting a collection of models, process flows, graphs, templates, forms and pics with a how to... Something like 50/50 text and visuals. So it didn't meet my expectations, not by a long shot.
However, it is a little more richly illustrated than the usual textbooks on the matter and the authors use clear language to explain complex systems. Further it covers some ground not covered in PMBOK or PRINCE2. Therefor I decided to keep it.

Looking for a cheaper book
Good options for new or used, good service, easy to use site, = I got what I wanted at a super price.

Pretty Good PM Resource
I am fairly new to the PM role where I am responsible for other's work, so I purchased this book as a reference tool and so far it has helped in terms of having examples that I can start with instead of starting from scratch.
Other than that, I have relied on my leadership and team building skills to meet deadlines which proves to be more important that having the pretty models, charts, etc.

Good Textbook
This book was assigned as THE textbook for my graduate Level Project Management class.It is a good read, great at presenting its ideas, and easy to understand.It unfortunately talks only of a couple of project management techniques vaguely and what examples are included are very short with little or no good background.I'd sell this book as a good starter for those looking to gain understanding in PM, but with the understanding that other books would be needed for true enlightenment in particular areas.

On-time delivery
product came in good condition and on-time.
that was all that I wanted. ... Read more