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Complexity And Artificial Markets

Author: Klaus Schredelseker
Publisher: Springer Science & Business Media
ISBN: 3540705562
Size: 78.42 MB
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In recent years, agent-based simulation has become a widely accepted tool when dealing with complexity in economics and other social sciences. The contributions presented in this book apply agent-based methods to derive results from complex models related to market mechanisms, evolution, decision making, and information economics. In addition, the applicability of agent-based methods to complex problems in economics is discussed from a methodological perspective. The papers presented in this collection combine approaches from economics, finance, computer science, natural sciences, philosophy, and cognitive sciences.

Complex Systems In Finance And Econometrics

Author: Robert A. Meyers
Publisher: Springer Science & Business Media
ISBN: 1441977007
Size: 14.56 MB
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"This book consists of selections from the Encyclopedia of complexity and systems science edited by Robert A. Myers"--T.p. verso.

Advanced Geo Simulation Models

Author: Danielle J. Marceau
Publisher: Bentham Science Publishers
ISBN: 1608052222
Size: 39.52 MB
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Geosimulation has recently emerged at the intersection of Geographic Information Science, Complex Systems Theory and Computer Science. Geosimulation aims at understanding the dynamics of complex human-driven spatial systems through the use of spatially explicit computer simulation. the approaches and tools for validating Geosimulation models are especially important for understanding their complex and spatially heterogeneous outcomes. the Ebook presents the recent conceptual and methodological advances achieved in the field. It should be very useful for scientists and graduate students working in the fields of Complex Systems Modelling, Geocomputation, Science, Geography, Regional Science, Computer Science, Artificial Intelligence, Environment Simulation and Modeling, and Environmental Engineering.

Agent Based Approaches In Economic And Social Complex Systems V

Author: Takao Terano
Publisher: Springer Science & Business Media
ISBN: 4431874356
Size: 39.41 MB
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Agent-based modeling/simulation is an emergent approach to the analysis of social and economic systems. It provides a bottom-up experimental method to be applied to social sciences such as economics, management, sociology, and politics as well as some engineering fields dealing with social activities. This book includes selected papers presented at the Fifth International Workshop on Agent-Based Approaches in Economic and Social Complex Systems held in Tokyo in 2007. It contains two invited papers given as the plenary and invited talks in the workshop and 21 papers presented in the six regular sessions: Organization and Management; Fundamentals of Agent-Based and Evolutionary Approaches; Production, Services and Urban Systems; Agent-Based Approaches to Social Systems; and Market and Economics I and II. The research presented here shows the state of the art in this rapidly growing field.

Agent Based Modeling And Network Dynamics

Author: Akira Namatame
Publisher: Oxford University Press
ISBN: 0191017981
Size: 63.37 MB
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While the significance of networks in various human behavior and activities has a history as long as human's existence, network awareness is a recent scientific phenomenon. The neologism network science is just one or two decades old. Nevertheless, with this limited time, network thinking has substantially reshaped the recent development in economics, and almost all solutions to real-world problems involve the network element. This book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The authors begin with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling's segregation model and Axelrod's spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The text also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. It reviews a number of pioneering and representative models in this family. Upon the given foundation, the second part reviews three primary forms of network dynamics, such as diffusions, cascades, and influences. These primary dynamics are further extended and enriched by practical networks in goods-and-service markets, labor markets, and international trade. At the end, the book considers two challenging issues using agent-based models of networks: network risks and economic growth.

Complexity And Evolution

Author: David S. Wilson
Publisher: MIT Press
ISBN: 0262035383
Size: 45.56 MB
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An exploration of how approaches that draw on evolutionary theory and complexity science can advance our understanding of economics.

Managing Market Complexity

Author: Andrea Teglio
Publisher: Springer Science & Business Media
ISBN: 3642313019
Size: 76.99 MB
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The field of artificial economics (AE) embraces a broad range of methodologies relying on computer simulations in order to model and study the complexity of economic and social phenomena. The overarching principle of AE is the analysis of aggregate properties of artificial economies populated by adaptive agents that are equipped with behavioural rules and specific individual targets. These aggregate properties are neither foreseen nor intended by the artificial agents; conversely they are emerging characteristics of such artificially simulated systems. The book presents a peer-reviewed collection of papers addressing a variety of issues related to macroeconomics, industrial organization, networks, management and finance, as well as purely methodological issues.

Generative Social Science Studies In Agent Based Computational Modeling

Author: Joshua M. Epstein
Publisher: Princeton University Press
ISBN: 1400842875
Size: 58.26 MB
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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.

Foundations Of Prediction Markets

Author: Shu-Heng Chen
Publisher: Springer
ISBN: 9784431552291
Size: 64.17 MB
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A prediction market is designed to trade and predict future events. This book provides a comprehensive and multidisciplinary treatment of the prediction market, explaining what it is, how it works, and why it may fail, from the theoretical, computational, and statistical (or machine learning) perspectives. The book begins with the theoretical aspect by reviewing Friedrich Hayek’s work on markets, which he viewed as discovery processes, and proceeds to experimental economics to examine the Hayek hypothesis by using human-subject experiments, finally moving to the modeling work. In addition to the conventional analytical models based on neoclassical economics, agent-based models of prediction markets are introduced. The use of agent-based models makes it possible to address the following four elements, which are difficult to tackle with analytical models: space, networks, traders’ behavior, and market designs. Agent-based simulation of the prediction market augmented with these four elements enables an examination of the effects of these elements on the prediction market from the computational aspect and hence tests the Hayek hypothesis on the basis of diverse institutional and individual characteristics. The empirical part of the book is based mainly on data from xFuture, currently the largest prediction market in Asia. This dataset includes 5.9 million trades from 170,000 members distributed over 128 countries. Forty variables are abstracted from the dataset and categorized into five groups to build empirical models to help evaluate or predict the performance of prediction markets. In addition to the linear models, complex thinking prompts the use of artificial intelligence or machine learning tools to develop nonlinear models. The system thus created allows an examination of how the performance of prediction markets can be affected by the complexity of events, the heterogeneity of agents’ intelligence and beliefs, and the degrees of manipulation.