Showing posts with label theory. Show all posts
Showing posts with label theory. Show all posts

Database Management: An Organizational Perspective Review

Database Management: An Organizational Perspective
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A birdseye view on the overall perspective of the Database Management System. I find the SQL Playbook section a great help in applying immediately whatever I've learned about the SQL in the earlier chapters.An excellent guide book.

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Complete coverage of database management with the correct balance of business and technical material for the MIS professional. This book covers the technical aspects of database design and implementation, with an equal emphasis on the "why" and "how" of the management of databases, and the managerial uses and philosophy behind databases.

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Two-Sided Matching: A Study in Game-Theoretic Modeling and Analysis (Econometric Society Monographs) Review

Two-Sided Matching: A Study in Game-Theoretic Modeling and Analysis (Econometric Society Monographs)
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This book is totally dedicated to matching theory. The book in itself is rather general, it doesn't focus on any particular application, and discusses matching as a general abstract theory. Therefore the book can be used by both micro- and macro people equally. It basically covers the problem of one-to-one and one-to-many matchings and tries to explain when equilibriums exist and if matches are unique or non-unique and comes with algorithms or constructive methods to actually do the matching. The structure of the book is mostly like math books and at each step presents an algorithm or a theorem or lemma that states a result. In most cases the proof comes afterwards. However this doesn't undermine the practicality of the book as you can easily locate the algorithm or theorem that embodies your required result and just use it. In my opinion this is one of those books you want to keep on your shelf and refer to every now and then when need be.

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Two-sided matching provides a model of search processes such as those between firms and workers in labor markets or between buyers and sellers in auctions. This book gives a comprehensive account of recent results concerning the game-theoretic analysis of two-sided matching. The focus of the book is on the stability of outcomes, on the incentives that different rules of organization give to agents, and on the constraints that these incentives impose on the ways such markets can be organized. The results for this wide range of related models and matching situations help clarify which conclusions depend on particular modeling assumptions and market conditions, and which are robust over a wide range of conditions.

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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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