Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity) Review

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(More customer reviews)At the time of writing this review, this book isn't searchable through Amazon, that's too bad because if you're reading the reviews wondering if it's worth buying, just browsing through any page from the intro or appendix B would clearly resolve any remnant hesitation. This book is a must have for anyone even remotely interested in complex adaptive systems. Scott Page and John Miller dress the landscape and state of the art of computational social science, the issues are motivated from the ground up and the existing approaches to resolve them explicitly detailed, yet using clear and jargon free language. For example, descriptions of the many concepts repeatedly used in the scientific method (of CAS et al) such as ergodicity or optimization theory are refreshing and insightful, simply stuff you don't get from textbooks, but rather that one would learn over years of experience doing.
In summary, the authors are handing us an expert summary of literature and developments of a complex field in a concise, fun and delightful read, it would be a shame to miss it.

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Military Operations Research: Quantitative Decision Making (International Series in Operations Research & Management Science) Review

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(More customer reviews)Jaiswal provides the most recent land power-focused military operations research volume. He provides a basic survey of the field, beginning with a very brief discussion of the origins of OR in the military. His topics include search and detection, military simulation, cost effectiveness analysis, optimization, the Analytic Hierarchy Process, Lanchester equations, and a quantified approach to intelligence analysis. The reader should be aware that his coverage of various specific military simulation models is a bit dated, as one should expect in a book, and limited in scope. Beyond that topic, his treatment is broad and therefore less sensitive to the passage of time. The book is a survey, so depth of treatment is not present. But it fills the intended role of pulling together disparate topics of land-based military OR. It also provides some perspective on non NATO defense issues. It must be challenging to decide what to exclude, but surprisingly there is no coverage of network flows, queuing theory, decision analysis, or game theory which have clear military applications. The focus is also on operations rather than the logistics of military analysis.

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The field of Operations Research (OR) grew out of World War IIoperations to improve the effectiveness of newly introduced weaponsand equipment, and to solve logistical problems for the war effort.Since its beginnings, OR has rapidly become a robust set ofdecision-making methodologies widely used in business, engineering,and governmental sectors. Nevertheless, many of OR's military anddefense contributions have remained confined to classified reports.This book is a systematic, state-of-the-art treatment of militaryoperations research (MOR). It has been written for those interested inlearning about the applications of OR techniques to military problems,and within these discussions theoretical concepts needed for analysisof military issues are presented. The book examines issues that relateto both tactical and strategic levels. Several examples have beensolved in each chapter to illustrate the application of the techniquesof MOR to military systems. The data used in these examples arehypothetical. They do not correspond to any existing weapon ormilitary situations. They are used strictly to illustrate anapplication of MOR in defense decision-making.

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Understanding Agent Systems (Springer Series on Agent Technology) Review

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(More customer reviews)There are several books on intelligent agents and multi-agents systems that I've come across, but most are either too broad-ranging and shallow so that they don't actually get to important core issues, or they're too narrow and mathematical for my liking (and for many others). This excellent book somehow manages to pull off the feat of providing a good introduction to agents, while also drilling down to some fascinating and deep issues in multi-agent systems. What's particularly good is that it does two things - it analyses and explains the issues with really clear textual description, and then provides a more formal description (using the Z specification language) that is surprisingly readable.
After providing an introductory chapter, the book presents a "framework" for understanding agent systems (hence the title) in which it brings together various different notions of agents. The chapters cover the framework itself, the different kinds of inter-agent
relationships that arise within it (to get to multi-agent systems), and more complex agents with greater sophistication. There are also a couple of case-study chapters that show how the model can be used to give descriptions of BDI systems and the contract net.
Throughout, the authors provide really good explanations, and then also formal descriptions using Z. Whether or not you buy the claim that Z is the most used industrial formal method, it turns out that despite the mathematical nature of the Z specification, the book as a whole is really very readable. It is worth noting that the level of mathematical description in the book for describing the framework and the systems is pretty close to abstract code descriptions (which is perhaps not surprising given that Z is intended for use for specifying software). With the appendix intro to Z, the book should also be a useful resource for developers wanting to understand exactly what would be involved in building systems.
One of the difficulties I've found when reading about agents is trying to make sense of some very different ideas and systems, and trying to understand how they fit together. This book provides some of the answers. In summary, the book covers some basic agent concepts, and builds them up to describe quite complex multi-agent systems, moving from abstract ideas to descriptions of specific implemented systems, and showing how they come together. It provides an excellent
introduction to agents, and keeps going to address some much deeper issues.

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Mark d'Inverno and Michael Luck presenta formal approach to dealing with agents and agent systems in this second edition of Understanding Agent Systems. The Z specification language is used to establish an accessible and unified formal account of agent systems and inter-agent relationships. In particular, the framework provides precise and unambiguous meanings for common concepts and terms for agent systems, allows for the description of alternative agent models and architectures, and serves as a foundation for subsequent development of increasingly refined agent concepts. The practicability of this approach is verified by applying the formal framework to three detailed case studies. The book will appeal equally to researchers, students, and professionals in industry.

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Random Fields on a Network: Modeling, Statistics, and Applications (Probability and Its Applications) Review

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(More customer reviews)Guyon has done research in the theory of random fields. This text was first published in French in 1992 and then translated to English and published by Springer-Verlag in 1995. This theory is rapidly developing and there have been many new advances over the nine years since the publication of this work. Nevertheless it contains a good theoretical development and treatment of the theory and provides applications to image processing.
The important results on stochastic algorithms are covered in Chapter Six which includes the results on Gibbs sampling that first had a big impact on spatial modeling and image processing through the work of the Gemans. Later it was recognized to be a special case of Markov Chain Monte Carlo modeling that is now so crucial to the practical implementation of Bayesian statistical methods.
The book contains an excellent list of over 175 references.


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The theory of spatial models over lattices, or random fields as they are known, has developed significantly over recent years. This book provides a graduate-level introduction to the subject which assumes only a basic knowledge of probability and statistics, finite Markov chains, and the spectral theory of second-order processes. A particular strength of this book is its emphasis on examples - both to motivate the theory which is being developed, and to demonstrate the applications which range from statistical mechanics to image analysis and from statistics to stochastic algorithms.

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Modeling Dynamic Climate Systems (With CD-ROM) Review

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(More customer reviews)This book aims to teach about climate modeling while presenting some fundamentals of atmospheric physics by providing numerous STELLA models ranging from a simple stability model of a leaky bucket to much more complex (and relevant) models for Rossby waves and El Nino. Though the models are not "rigorous", they are intended to show how simplifications can enhance understanding and how some simplifications meet the goals of the model while other times simplifications miss important aspects for accurate models.
For those who are looking for sophisticated programing and modeling approaches, they are sure to be disappointed. However, for those who are either trying to learn or teach basics of climate modeling to those with limited mathematical expertise or teaching students with such limited experience, this book will prove quite useful. The approximately 40 STELLA models included with the book guide the reader to an intuitive understanding of an Earth system approach of atmospheric science. I plan to use a number of examples with a group of students who have only a simple calculus background. Though the text has a 2001 copywrite and the CD-ROM was intended for an earlier version of STELLA, I found that the models could be translated to the newest versions of STELLA on a Macintosh through a fairly simple manipulations and help from software updates provided by High Performance Systems. The text would be useful for junior level classes in atmospheric science aimed at students in environmental science programs. It would be less useful for those with strong math skills majoring in a rigorous atmospheric science sequence, though it could provide such students with a much better conceptual understanding than they might receive in a more mathematically sophisticated class.

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In the process of building and using models to comprehend the dynamics of the atmosphere, ocean and climate, the reader will learn how the different components of climate systems function, interact with each other, and vary over time. Topics include the stability of climate, Earths energy balance, parcel dynamics in the atmosphere, the mechanisms of heat transport in the climate system, and mechanisms of climate variability. Special attention is given to the effects of climate change. The book is accompanied by a cross-platform CD-ROM containing models and a run-time version of STELLA modeling software.

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Modeling for Learning Organizations (System Dynamics Series) Review

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(More customer reviews)"Modeling for Learning Organizations" builds off of the extensive experience of top professors and consultants using the SD tools to test strategies and build an understanding of firm and industry dynamics.
"Modeling" also includes a section overviewing the various simulation software packages available to modelers. Though developers like High-Performance Systems, Vensim, Pugh-Roberts, and PowerSim have made product enhancements to date, the sections from each company provide a great introduction to what is out there how each package can be applied.
The most valuable aspect of the book is probably in the case studies and methodological explorations of several authors. A number of key insights are offered as authors reflect upon the successes and shortcoming of the methods each chose to use to explore and develop models in a variety of business and public environments.
This is definitely a must have for any SD library.

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Conventional wisdom says that we can learn from our errors, but errors in the business world can be prohibitively costly. To truly understand how complex business organizations function requires different tools than most managers have been given. Yet managers need methods to understand how their organization works in order to test policies, discover flaws in thinking, and find the hidden leveragepoints within the complex systems they manage. Through a system simulation, the dynamics of the whole system, not just the individual parts, becomes apparent. The outcome of current and future situations becomes possible to predict and with this information, managers can focus on the changes that need to be made.The distinguished contributors to Modeling for Learning Organizations include Jay W. Forrester, Peter Senge, and Arie De Geus. You will learn about leading applications such as:
Shell's work on modeling the oil producers.
The Management Flight Simulator, a computer-based case learning environment pioneered by John Sterman and others at MIT
The landmark Claims Learning Laboratory at Hanover Insurancecompanies.
For managers, professionals, academicians, and everyone who recognizes the profound implications of modeling, this book is an excellent resource. It offers a broad understanding of the modeling process, discusses a multitude of case studies, and provides a review of the most recent simulation software.

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Computational Modeling of Genetic and Biochemical Networks (Computational Molecular Biology) Review

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(More customer reviews)Regulatory networks are central to every aspect of computational biology. Determining what they are, and what genes, proteins, and post-translational modifications interact is a major and exciting field of study.
I just didn't come away from this book with that excitement. I was hoping for more about the large-scale regulation networks, but these papers go down to the quantum mechanics of interactions between pairs of molecules. I appreciate that the exact interactions matter, and that computation is probably the only way to examine some kinds of interactions (e.g. the ones in lethal mutations). It's just not what I think of as a "network."
I was also hoping for some more specifics about the computation techniques. There were some interesting insights here. For example, I never thought about the similarities between steady state chemical equilibrium and steady state Markov model behavior before, but the formalisms have striking similarities. I was also interested in some of the information-based measures for determining how well a model represents a system. I learned that the statistical assumptions behind normal chemical "equilibrium" break down at the scale of bacteria - instead, presence or absence of individual molecules matters more. Still, those were isolated kinds of facts and never came together into a whole for me.
The range of views was worthwhile. On the whole, though, the models all seemed very low-level to me, probably not well suited to handling more than a few dozen interactions, and the computation specifics were not always explicit. I'm still looking for a book with more information that I can apply directly.

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The advent of ever more sophisticated molecular manipulation techniqueshas made it clear that cellular systems are far more complex and dynamic thanpreviously thought. At the same time, experimental techniques are providing analmost overwhelming amount of new data. It is increasingly apparent that linkingmolecular and cellular structure to function will require the use of newcomputational tools.This book provides specific examples, across a wide range ofmolecular and cellular systems, of how modeling techniques can be used to explorefunctionally relevant molecular and cellular relationships. The modeling techniquescovered are applicable to cell, developmental, structural, and mathematical biology;genetics; and computational neuroscience. The book, intended as a primer for boththeoretical and experimental biologists, is organized in two parts: models of geneactivity and models of interactions among gene products. Modeling examples areprovided at several scales for each subject. Each chapter includes an overview ofthe biological system in question and extensive references to important work in thearea.

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Modeling the Environment, Second Edition Review

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(More customer reviews)A highly readable introduction to environmental modeling. What distinguishes the book from other environmental science and environmental modeling works is its interdisciplinary treatment. In particular, the models integrate the physical world and the world of human behavior. Far too many environmental models fail to close the feedbacks between human behavior and the state of the environment, instead taking waste inputs or resource use as exogenous. This book helps students learn to model human behavior (social and economic) as an integral part of the ecological system. The models and software mean the book encourages active learning, and enable students to explore important issues on their own if they choose.

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Modeling the Environment was the first textbook in an emerging field-the modeling techniques that allow managers and researchers to see in advance the consequences of actions and policies in environmental management. This new edition brings the book thoroughly up to date and reaffirms its status as the leading introductory text on the subject. System dynamics is one of the most widely known and widely used methods of modeling. The fundamental principles of this approach are demonstrated here with a wide range of examples, including geo-hydrology, population biology, epidemiology and economics. The applications demonstrate the transferability of the systems approach across disciplines, across spatial scales, and across time scales. All of the models are implemented with stock and flow software programs such as Stella and Vensim. These programs are easy and fun to learn, and they allow students to develop realistic models within the first few weeks of a college course. System dynamics has emerged as the most common approach in collaborative projects to address environmental problems. The stock and flow structures and the emphasis on feedback control provide a common language that is understood by scientists from many disciplines. Although the interdisciplinary approach described here is widely used in practice, there are few books to aid instruction. Modeling the Environment meets the urgent need for instructional materials in interdisciplinary modeling of environmental systems.

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Mathematics for Dynamic Modeling, Second Edition Review

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(More customer reviews)This is not a new cover on an older book. Having enjoyed Beltrami's first book I was glad to see a second. The new continues the subject of modeling not math. Well written, the author's book ties the conceptual difficulites of the subjects with the necessary math to get the point accross and guide the reader to new frontiers of insight again in the sense of the physical model not the math. This is a very important point! One does not lose sight of the over-all objective as with some math intensive proof types. The beauty of the work is getting the necessary across with the least. One disappointment though. The book was to short. I hope the author continues another work. Perhaps some more indepth of previous covered material. All examples and problems are easily solved in Mathcad, which already has the depth but sometimes not the explanation.

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The Art of Modeling Dynamic Systems: Forecasting for Chaos, Randomness and Determinism (Dover Books on Mathematics) Review

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I find myself agreeing with all the comments made so far.
It's not too common to find a book that is able to describe in simple terms, such a large and diverse range of mathematical tools.
The author uses a framework - to tie together tools used in describing and handling deterministic, semi deterministic, and stochastic systems. For an example of Deterministic, try ODE's (ordinary differential equations), for semi deterministic - try Periodic but noisy wave-forms (some stock prices), and finally Stochastic - Random looking waveforms that have underlying patterns that can be described using either using Chaotic indicators (Hurst, Liapunov ) or probability type descriptors.
This book is the kind of thing you needed to help steer you through those dry mathematical books that are divorced from reality - A sort of classification system for deciphering what kind of gunpowder was used in those display's of intellectual fireworks from the tops of ivory towers. Kinda "So thats what all that maths means, but in plain english".
A depth of understanding, for practical application, without intellectual egotism and opaqueness. (But then maybe I'm just a bit thick ... :)
I'd tend to call this book as an equivalent to the Rosetta Stone for the maths of dynamical systems.
You may not use it directly - but you will benefit and grow in understanding from its' plain and simple sign posts along your journey.
It has its place on my book shelf.

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This text demonstrates the roles of statistical methods, coordinate transformations, and mathematical analysis in mapping complex, unpredictable dynamical systems. Written by a well-known authority in the field, it employs practical examples and analogies, rather than theorems and proofs, to characterize the benefits and limitations of modeling tools. 1991 edition.

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