Showing posts with label social science. Show all posts
Showing posts with label social science. Show all posts

7/11/2012

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

Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity)
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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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4/08/2012

Artificial Life Models in Software Review

Artificial Life Models in Software
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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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3/19/2012

Understanding Agent Systems (Springer Series on Agent Technology) Review

Understanding Agent Systems (Springer Series on Agent Technology)
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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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2/07/2012

Simulating Society: A Mathematica Toolkit for Modeling Socioeconomic Behavior Review

Simulating Society: A Mathematica Toolkit for Modeling Socioeconomic Behavior
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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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8/24/2011

Generative Social Science: Studies in Agent-Based Computational Modeling (Princeton Studies in Complexity) Review

Generative Social Science: Studies in Agent-Based Computational Modeling (Princeton Studies in Complexity)
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Josh Epstein's new Opus is a landmark publication in the emerging field of multiagent-based simulation of dynamic social systems. Since Josh is not only one of this still nascent (though burgeoning) field's ablest and most creative practitioners, but also among its most thoughtful critics, the reader of has two treats in store: (1) a generous, and wide-ranging, sampling of case studies (including social networks and evolution, population growth, emergence of economic classes, civil unrest, timing of retirement, the dynamics of adaptive organizations and the spread of infectious disease), and (2) a cogent "meta" discussion of what multiagent models ARE, ARE NOT and how (when their properties and limitations are *not* properly taken account of) they can easily be MISAPPLIED.
Far from suggesting that multiagent-based models are a panacea solution to all (or most) social dynamical systems, Josh's book carefully articulates the conditions for which such an approach IS (and is NOT) appropriate; an approach rarely taken by other, similar, overviews of the field. Indeed, the cogent philosophical discussion in Chapter One - alone! - in which the generativist's position is defined and put into a broader modeling/simulation context, is worth the price of admission; I have not seen a better "manifesto" of multiagent-based modeling elsewhere.
Finally, without taking away any of the inherent "beauty" (in the technical sense) of the often exaggerated concept of "emergence," Josh succeeds admirably in both defining the term, and de-mystifying it, stripping it of some of its unnecessary "quasi-mystical" baggage (at least as it is often portrayed in lay publications).
Anyone who is interested in understanding how agent models may be used to help explore the dynamics of social dynamical systems, should have this book firmly on top of their "must read" list! Josh has generously provided future generations of agent explorers their go-to source of both inspiration and ideas. Well done Josh!

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Agent-based computational modeling is changing the face of social science. In Generative Social Science, Joshua Epstein argues that this powerful, novel technique permits the social sciences to meet a fundamentally new standard of explanation, in which one "grows" the phenomenon of interest in an artificial society of interacting agents: heterogeneous, boundedly rational actors, represented as mathematical or software objects. After elaborating this notion of generative explanation in a pair of overarching foundational chapters, Epstein illustrates it with examples chosen from such far-flung fields as archaeology, civil conflict, the evolution of norms, epidemiology, retirement economics, spatial games, and organizational adaptation. In elegant chapter preludes, he explains how these widely diverse modeling studies support his sweeping case for generative explanation.

This book represents a powerful consolidation of Epstein's interdisciplinary research activities in the decade since the publication of his and Robert Axtell's landmark volume, Growing Artificial Societies. Beautifully illustrated, Generative Social Science includes a CD that contains animated movies of core model runs, and programs allowing users to easily change assumptions and explore models, making it an invaluable text for courses in modeling at all levels.


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