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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Agent-Based Models (Quantitative Applications in the Social Sciences) Review

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(More customer reviews)This book is fine as far as it goes. But ABM can only be done with software and it fails to mention one of the key players in this area. The author points out that NetLogo is easiest to learn but too simple for large models. Then he points you to the programmers-only solutions of Repast, Swarm, and Mason -- all academic development environments that require you to program in Java. He bemoans the gap between these two extremes yet somehow he skips AnyLogic which is a true high-level application with drag-and-drop model building, sophisticated libraries, model wizards to help beginners, and many advanced features.
It's hard to believe someone would write a book on ABM without first doing at least a Google search on the available tools.
At any rate, the book is a solid theoretical treatment. If you are an expert Java programmer with the time to code models from scratch this will be an important book.

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Agent-based modeling (ABM) is a technique increasingly used in a broad range of social sciences. It involves building a computational model consisting of 'agents," each of which represents an actor in the social world, and an "environment" in which the agents act. Agents are able to interact with each other and are programmed to be pro-active, autonomous and able to perceive their virtual world. The techniques of ABM are derived from artificial intelligence and computer science, but are now being developed independently in research centers throughout the world.In Agent-Based Models, Nigel Gilbert reviews a range of examples of agent-based modeling, describes how to design and build your own models, and considers practical issues such as verification, validation, planning a modeling project, and how to structure a scholarly article reporting the results of agent-based modeling. It includes a glossary, an annotated list of resources, advice on which programming environment to use when creating agent-based models, and a worked, step-by-step example of the development of an ABM.This latest volume in the SAGE Quantitative Applications in the Social Sciences series will have wide appeal in the social sciences, including the disciplines of sociology, economics, social psychology, geography, economic history, science studies, and environmental studies. It is appropriate for graduate students, researchers and academics in these fields, for both those wanting to keep up with new developments in their fields and those who are considering using ABM for their research.Key Features

Aimed at readers who are new to ABM

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Artificial Life Models in Software Review

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(More customer reviews)Remember Conway's Game of Life? Surely you must, if you are interested in this book. The Game has been around since the 70s. The editors have cultivated recent research papers that demonstrate how far the field has advanced. Reinforced by some pretty colour plates that depict artificial entities [dare we call them living?] in some surroundings. These include the modelling of bee flights through a garden, and simulated trajectories of a group of bacteria.
Nor is the Game of Life ignored. One plate shows it in three dimensions. The Game is played in 2 dimensions, with time as the third dimension. An obvious choice that gives interesting trajectories of the cells.
The narrative adds to the illustrations. By describing a variety of computer simulations [worlds?]. Where the experimenter can tweak many parameters, and watch her world unfold. Some worlds are impressively rich in complexity of observed behaviours.
The only drawback in the book is its skimpy index. A mere two pages. It should have been more detailed.

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The advent of powerful processing technologies and the advances in software development tools have drastically changed the approach and implementation of computational research in fundamental properties of living systems through simulating and synthesizing biological entities and processes in artificial media. Nowadays realistic physical and physiological simulation of natural and would-be creatures, worlds and societies becomes a low-cost task for ordinary home computers. The progress in technology has dramatically reshaped the structure of the software, the execution of a code, and visualization fundamentals. This has led to the emergence of novel breeds of artificial life software models, including three-dimensional programmable simulation environment, distributed discrete events platforms and multi-agent systems. This second edition reflects the technological and research advancements, and presents the best examples of artificial life software models developed in the World and available for users.

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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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Simulating Society: A Mathematica Toolkit for Modeling Socioeconomic Behavior Review

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(More customer reviews)This book will help you design simulations. It doesn't take you trough the design on the simulation, but rather help you apply certain algorithms to your simulations. If you know simulations and require help in coding Mathematica, this book is for you.

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An exploration of the basis for social and economic behaviour. Using cellular automata in particular, the authors model various factors that are involved in a system of individuals who interact socially and economically with one another. Computer simulations in the social sciences provide a laboratory in which qualitative ideas about social and economic interactions can be tested. This brings a new dimension to the science, where 'explanations' abound, but are rarely subject to much experimental testing. The authors have chosen Mathematica because it has a number of features which make it uniquely qualified for use by social scientists, especially those without expertise in computer programming. Further, users can easily access and readily interact with the various 3.0 Mathematica notebooks, plus other data to be found at www.telospub.com.

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Adventures in Modeling: Exploring Complex, Dynamic Systems with StarLogo Review

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(More customer reviews)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!

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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.

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Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation Review

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(More customer reviews)'Managing Business Complexity' is a great start at bridging the significant academic work in complexity science over recent years to business applications. It provides an introduction to agent-based simulations and an overview of the characteristics and advantages of agents, and walks the reader through two illustrative examples. Such examples are especially helpful to readers with little or no previous experience using agent-based models.
Applications of complexity science to business are still in their infancy. As such, the discussion in the book leans towards the academic, and more pointedly towards programmers rather than business practitioners with scant scientific background. Future editions of this book might benefit from including further business applications, and including the impact to bottom line.
This book is highly recommended as an overview of this exciting subject and its applicability to business situations.

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Agent-based modeling and simulation (ABMS), a way to simulate a large number of choices by individual actors, is one of the most exciting practical developments in business modeling since the invention of relational databases. It represents a new way to understand data and generate information that has never been available before--a way for businesses to view the future and to understand and anticipate the likely effects of their decisions on their markets and industries. It thus promises to have far-reaching effects on the way that businesses in many areas use computers to support practical decision-making.Managing Business Complexity is the first complete business-oriented agent-based modeling and simulation resource. It has three purposes: first, to teach readers how to think about ABMS, that is, about agents and their interactions; second, to teach readers how to explain the features and advantages of ABMS to other people and third, to teach readers how to actually implement ABMS by building agent-based simulations. It is intended to be a complete ABMS resource, accessible to readers who haven't had any previous experience in building agent-based simulations, or any other kinds of models, for that matter. It is also a collection of ABMS business applications resources, all assembled in one place for the first time. In short, Managing Business Complexity addresses who needs ABMS and why, where and when ABMS can be applied to the everyday business problems that surround us, and how specifically to build these powerful agent-based models.

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