Computational Models of Complex Systems

Computational Models of Complex Systems
Author: Vijay Kumar Mago
Publisher: Springer Science & Business Media
Total Pages: 199
Release: 2013-10-31
Genre: Technology & Engineering
ISBN: 3319012851

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Computational and mathematical models provide us with the opportunities to investigate the complexities of real world problems. They allow us to apply our best analytical methods to define problems in a clearly mathematical manner and exhaustively test our solutions before committing expensive resources. This is made possible by assuming parameter(s) in a bounded environment, allowing for controllable experimentation, not always possible in live scenarios. For example, simulation of computational models allows the testing of theories in a manner that is both fundamentally deductive and experimental in nature. The main ingredients for such research ideas come from multiple disciplines and the importance of interdisciplinary research is well recognized by the scientific community. This book provides a window to the novel endeavours of the research communities to present their works by highlighting the value of computational modelling as a research tool when investigating complex systems. We hope that the readers will have stimulating experiences to pursue research in these directions.

Complex Adaptive Systems

Complex Adaptive Systems
Author: John H. Miller
Publisher: Princeton University Press
Total Pages: 285
Release: 2009-11-28
Genre: Social Science
ISBN: 1400835526

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This book provides the first clear, comprehensive, and accessible account of complex adaptive social systems, by two of the field's leading authorities. Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.

Computational Social Science and Complex Systems

Computational Social Science and Complex Systems
Author: János Kertész
Publisher:
Total Pages: 0
Release: 2019
Genre: Quantum systems
ISBN: 9781643680361

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For many years, the development of large-scale quantitative social science was hindered by a lack of data. Traditional methods of data collection like surveys were very useful, but were limited. The situation has of course changed with the development of computing and information communication technology, and we now live in a world of data deluge, where the question has become how to extract important information from the plethora of data that can be accessed. Big Data has made it possible to study societal questions which were once impossible to deal with, but new tools and new multidisciplinary approaches are required. Physicists, together with economists, sociologists, computer scientists, etc. have played an important role in their development.This book presents the 9 lectures delivered at the CCIII Summer Course Computational Social Science and Complex Systems, held as part of the International School of Physics Enrico Fermi in Varenna, Italy, from 16-21 July 2018. The course had the aim of presenting some of the recent developments in the interdisciplinary fields of computational social science and econophysics to PhD students and young researchers, with lectures focused on recent problems investigated in computational social science.Addressing some of the basic questions and many of the subtleties of the emerging field of computational social science, the book will be of interest to students, researchers and advanced research professionals alike.

Think Complexity

Think Complexity
Author: Allen Downey
Publisher: "O'Reilly Media, Inc."
Total Pages: 159
Release: 2012-03-02
Genre: Computers
ISBN: 1449314635

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Dive into Python's advanced possibilities, including algorithm analysis, graphs, scale-free networks, and cellular automata with this in-depth, hands-on guide.

Modeling Complex Systems

Modeling Complex Systems
Author: Nino Boccara
Publisher: Springer Science & Business Media
Total Pages: 490
Release: 2010-09-09
Genre: Computers
ISBN: 1441965629

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This book illustrates how models of complex systems are built up and provides indispensable mathematical tools for studying their dynamics. This second edition includes more recent research results and many new and improved worked out examples and exercises.

Modeling of Complex Systems

Modeling of Complex Systems
Author: V. Vemuri
Publisher: Academic Press
Total Pages: 465
Release: 2014-05-10
Genre: Technology & Engineering
ISBN: 1483267520

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Modeling of Complex Systems: An Introduction describes the framework of complex systems. This book discusses the language of system theory, taxonomy of system concepts, steps in model building, and establishing relations using physical laws. The statistical attributes of data, generation of random numbers fundamental problems of recognition, and input-output type models are also elaborated. This text likewise covers the optimization with equality constraints, transfer function models, and competition among species. This publication is written primarily for senior undergraduate students and beginning graduate students who are interested in an interdisciplinary or multidisciplinary approach to large-scale or complex problems of contemporary societal interest.

Understanding Complex Systems Through Computational Modeling and Simulation

Understanding Complex Systems Through Computational Modeling and Simulation
Author: Xuan Tuan Le
Publisher:
Total Pages: 0
Release: 2017
Genre:
ISBN:

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Traditional approaches are not sufficient, and sometimes impossible in dealing with complexity issues such as emergence, self-organization, evolution and adaptation of complex systems. As illustrated in this thesis by the practical work of the author in a real-life project, the spreading of infectious disease as well as interventions could be considered as difusion processes on complex networks of heterogeneous individuals in a society which is considered as a reactive system. Modeling of this system requires explicitly specifying of each individual's behaviors and (re)actions, and transforming them into computational model which has to be flexible, reusable, and ease of coding. Statechart, typical for model-based programming, is a good solution that the thesis proposes. Bottom-up agent based simulation finds emergence episodes in what-if scenarios that change rules governing agent's behaviors that requires agents to learn to adapt with these changes. Decision tree learning is proposed to bring more flexibility and legibility in modeling of agent's autonomous decision making during simulation runtime. Our proposition for computational models such as agent based models are complementary to traditional ones, and in some case they are unique solutions due to legal, ethical issues.

Computational Modeling And Simulations Of Biomolecular Systems

Computational Modeling And Simulations Of Biomolecular Systems
Author: Benoit Roux
Publisher: World Scientific
Total Pages: 209
Release: 2021-08-23
Genre: Computers
ISBN: 9811232776

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This textbook originated from the course 'Simulation, Modeling, and Computations in Biophysics' that I have taught at the University of Chicago since 2011. The students typically came from a wide range of backgrounds, including biology, physics, chemistry, biochemistry, and mathematics, and the course was intentionally adapted for senior undergraduate students and graduate students. This is not a highly technical book dedicated to specialists. The objective is to provide a broad survey from the physical description of a complex molecular system at the most fundamental level, to the type of phenomenological models commonly used to represent the function of large biological macromolecular machines.The key conceptual elements serving as building blocks in the formulation of different levels of approximations are introduced along the way, aiming to clarify as much as possible how they are interrelated. The only assumption is a basic familiarity with simple mathematics (calculus and integrals, ordinary differential equations, matrix linear algebra, and Fourier-Laplace transforms).

Complex Models and Computational Methods in Statistics

Complex Models and Computational Methods in Statistics
Author: Matteo Grigoletto
Publisher: Springer Science & Business Media
Total Pages: 228
Release: 2013-01-26
Genre: Mathematics
ISBN: 884702871X

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The use of computational methods in statistics to face complex problems and highly dimensional data, as well as the widespread availability of computer technology, is no news. The range of applications, instead, is unprecedented. As often occurs, new and complex data types require new strategies, demanding for the development of novel statistical methods and suggesting stimulating mathematical problems. This book is addressed to researchers working at the forefront of the statistical analysis of complex systems and using computationally intensive statistical methods.