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Navigating the Landscape of Conflict: Applications of Dynamical Systems Theory to Addressing Protracted Conflict
Dynamics of Intractable Conflict Peter T. Coleman, PhD Robin Vallacher, PhD Andrzej Nowak, PhD International Center for Cooperation and Conflict Resolution Teachers College, Columbia University New York, NY, USA Why are some intergroup conflicts impossible to solve and what can we do to address them? “…one of the things that frustrates me about this conflict, thinking about this conflict, is that people don’t realize the complexity… how many stakeholders there are in there…I think there is a whole element to this particular conflict to where you start the story, to where you begin the narrative, and clearly it’s whose perspective you tell it from…One of the things that’s always struck me is that there are very compelling narratives to this conflict and all are true, in as much as anything is true… I think the complexity is on so many levels…It’s a complexity of geographic realities…the complexities are in the relationships…it has many different ethnic pockets… and I think it’s fighting against a place, where particularly in the United States, in American culture, we want to simplify, we want easy answers…We want to synthesize it down to something that people can wrap themselves around and take a side on…And maybe sometimes I feel overwhelmed…” (Anonymous Palestinian, 2002) Four Basic Themes An increasing degree of complexity and interdependence of elements. An underlying proclivity for change, development, and evolution within people and social-physical systems. Extraordinary cognitive, emotional, and behavioral demands…anxiety, hopelessness. Oversimplification of problems. Intractable Conflicts: The 5% Problem Three inter-related dimensions (Kriesberg, 2005): Enduring Destructive Resistant Uncommon but significant (5%; Diehl & Goertz, 2000) 5% of 11,000 interstate rivalries between 1816-1992. -
Chaos Theory
By Nadha CHAOS THEORY What is Chaos Theory? . It is a field of study within applied mathematics . It studies the behavior of dynamical systems that are highly sensitive to initial conditions . It deals with nonlinear systems . It is commonly referred to as the Butterfly Effect What is a nonlinear system? . In mathematics, a nonlinear system is a system which is not linear . It is a system which does not satisfy the superposition principle, or whose output is not directly proportional to its input. Less technically, a nonlinear system is any problem where the variable(s) to be solved for cannot be written as a linear combination of independent components. the SUPERPOSITION PRINCIPLE states that, for all linear systems, the net response at a given place and time caused by two or more stimuli is the sum of the responses which would have been caused by each stimulus individually. So that if input A produces response X and input B produces response Y then input (A + B) produces response (X + Y). So a nonlinear system does not satisfy this principal. There are 3 criteria that a chaotic system satisfies 1) sensitive dependence on initial conditions 2) topological mixing 3) periodic orbits are dense 1) Sensitive dependence on initial conditions . This is popularly known as the "butterfly effect” . It got its name because of the title of a paper given by Edward Lorenz titled Predictability: Does the Flap of a Butterfly’s Wings in Brazil set off a Tornado in Texas? . The flapping wing represents a small change in the initial condition of the system, which causes a chain of events leading to large-scale phenomena. -
Introductory Course on Dynamical Systems Theory and Intractable Conflict DST Course Objectives
Introductory Course on Dynamical Systems Theory and Intractable Conflict Peter T. Coleman Columbia University December 2012 This self-guided 4-part course will introduce the relevance of dynamical systems theory for understanding, investigating, and resolving protracted social conflict at different levels of social reality (interpersonal, inter-group, international). It views conflicts as dynamic processes whose evolution reflects a complex interplay of factors operating at different levels and timescales. The goal for the course is to help develop a basic understanding of the dynamics underlying the development and transformation of intractable conflict. DST Course Objectives Participants in this class will: Learn the basic ideas and methods associated with dynamical systems. Learn the relevance of dynamical systems for personal and interpersonal processes. Learn the implications of dynamical models for understanding and investigating conflict of different types and at different levels of social reality. Learn to think about conflict in a manner that allows for new and testable means of conflict resolution. Foundational Texts Nowak, A. & Vallacher, R. R. (1998). Dynamical social psychology. New York: Guilford Publications. Vallacher, R., Nowak, A., Coleman, P. C., Bui-Wrzosinska, L., Leibovitch, L., Kugler, K. & Bartoli, A. (Forthcoming in 2013). Attracted to Conflict: The Emergence, Maintenance and Transformation of Malignant Social Relations. Springer. Coleman (2011). The Five Percent: Finding Solutions to Seemingly Impossible Conflicts. Perseus Books. Coleman, P. T. & Vallacher, R. R. (Eds.) (2010). Peace and Conflict: Journal of Peace Psychology, Vol. 16, No. 2, 2010. (Special issue devoted to dynamical models of intractable conflict). Ricigliano, R. (2012).Making Peace Last. Paradigm. Burns, D. (2007). Systemic Action Research: A Strategy for Whole System Change. -
Synchronization in Nonlinear Systems and Networks
Synchronization in Nonlinear Systems and Networks Yuri Maistrenko E-mail: [email protected] you can find me in the room EW 632, Wednesday 13:00-14:00 Lecture 4 - 23.11.2011 1 Chaos actually … is everywhere Web Book CHAOS = BUTTERFLY EFFECT Henri Poincaré (1880) “ It so happens that small differences in the initial state of the system can lead to very large differences in its final state. A small error in the former could then produce an enormous one in the latter. Prediction becomes impossible, and the system appears to behave randomly.” Ray Bradbury “A Sound of Thunder “ (1952) THE ESSENCE OF CHAOS • processes deterministic fully determined by initial state • long-term behavior unpredictable butterfly effect PHYSICAL “DEFINITION “ OF CHAOS “To say that a certain system exhibits chaos means that the system obeys deterministic law of evolution but that the outcome is highly sensitive to small uncertainties in the specification of the initial state. In chaotic system any open ball of initial conditions, no matter how small, will in finite time spread over the extent of the entire asymptotically admissible phase space” Predrag Cvitanovich . Appl.Chaos 1992 EXAMPLES OF CHAOTIC SYSTEMS • the solar system (Poincare) • the weather (Lorenz) • turbulence in fluids • population growth • lots and lots of other systems… “HOT” APPLICATIONS • neuronal networks of the brain • genetic networks UNPREDICTIBILITY OF THE WEATHER Edward Lorenz (1963) Difficulties in predicting the weather are not related to the complexity of the Earths’ climate but to CHAOS in the climate equations! Dynamical systems Dynamical system: a system of one or more variables which evolve in time according to a given rule Two types of dynamical systems: • Differential equations: time is continuous (called flow) dx N f (x), t R dt • Difference equations (iterated maps): time is discrete (called cascade) xn1 f (xn ), n 0, 1, 2,.. -
Writing the History of Dynamical Systems and Chaos
Historia Mathematica 29 (2002), 273–339 doi:10.1006/hmat.2002.2351 Writing the History of Dynamical Systems and Chaos: View metadata, citation and similar papersLongue at core.ac.uk Dur´ee and Revolution, Disciplines and Cultures1 brought to you by CORE provided by Elsevier - Publisher Connector David Aubin Max-Planck Institut fur¨ Wissenschaftsgeschichte, Berlin, Germany E-mail: [email protected] and Amy Dahan Dalmedico Centre national de la recherche scientifique and Centre Alexandre-Koyre,´ Paris, France E-mail: [email protected] Between the late 1960s and the beginning of the 1980s, the wide recognition that simple dynamical laws could give rise to complex behaviors was sometimes hailed as a true scientific revolution impacting several disciplines, for which a striking label was coined—“chaos.” Mathematicians quickly pointed out that the purported revolution was relying on the abstract theory of dynamical systems founded in the late 19th century by Henri Poincar´e who had already reached a similar conclusion. In this paper, we flesh out the historiographical tensions arising from these confrontations: longue-duree´ history and revolution; abstract mathematics and the use of mathematical techniques in various other domains. After reviewing the historiography of dynamical systems theory from Poincar´e to the 1960s, we highlight the pioneering work of a few individuals (Steve Smale, Edward Lorenz, David Ruelle). We then go on to discuss the nature of the chaos phenomenon, which, we argue, was a conceptual reconfiguration as -
Tom W B Kibble Frank H Ber
Classical Mechanics 5th Edition Classical Mechanics 5th Edition Tom W.B. Kibble Frank H. Berkshire Imperial College London Imperial College Press ICP Published by Imperial College Press 57 Shelton Street Covent Garden London WC2H 9HE Distributed by World Scientific Publishing Co. Pte. Ltd. 5 Toh Tuck Link, Singapore 596224 USA office: Suite 202, 1060 Main Street, River Edge, NJ 07661 UK office: 57 Shelton Street, Covent Garden, London WC2H 9HE Library of Congress Cataloging-in-Publication Data Kibble, T. W. B. Classical mechanics / Tom W. B. Kibble, Frank H. Berkshire, -- 5th ed. p. cm. Includes bibliographical references and index. ISBN 1860944248 -- ISBN 1860944353 (pbk). 1. Mechanics, Analytic. I. Berkshire, F. H. (Frank H.). II. Title QA805 .K5 2004 531'.01'515--dc 22 2004044010 British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library. Copyright © 2004 by Imperial College Press All rights reserved. This book, or parts thereof, may not be reproduced in any form or by any means, electronic or mechanical, including photocopying, recording or any information storage and retrieval system now known or to be invented, without written permission from the Publisher. For photocopying of material in this volume, please pay a copying fee through the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA. In this case permission to photocopy is not required from the publisher. Printed in Singapore. To Anne and Rosie vi Preface This book, based on courses given to physics and applied mathematics stu- dents at Imperial College, deals with the mechanics of particles and rigid bodies. -
Annotated List of References Tobias Keip, I7801986 Presentation Method: Poster
Personal Inquiry – Annotated list of references Tobias Keip, i7801986 Presentation Method: Poster Poster Section 1: What is Chaos? In this section I am introducing the topic. I am describing different types of chaos and how individual perception affects our sense for chaos or chaotic systems. I am also going to define the terminology. I support my ideas with a lot of examples, like chaos in our daily life, then I am going to do a transition to simple mathematical chaotic systems. Larry Bradley. (2010). Chaos and Fractals. Available: www.stsci.edu/~lbradley/seminar/. Last accessed 13 May 2010. This website delivered me with a very good introduction into the topic as there are a lot of books and interesting web-pages in the “References”-Sektion. Gleick, James. Chaos: Making a New Science. Penguin Books, 1987. The book gave me a very general introduction into the topic. Harald Lesch. (2003-2007). alpha-Centauri . Available: www.br-online.de/br- alpha/alpha-centauri/alpha-centauri-harald-lesch-videothek-ID1207836664586.xml. Last accessed 13. May 2010. A web-page with German video-documentations delivered a lot of vivid examples about chaos for my poster. Poster Section 2: Laplace's Demon and the Butterfly Effect In this part I describe the idea of the so called Laplace's Demon and the theory of cause-and-effect chains. I work with a lot of examples, especially the famous weather forecast example. Also too I introduce the mathematical concept of a dynamic system. Jeremy S. Heyl (August 11, 2008). The Double Pendulum Fractal. British Columbia, Canada. -
Instructional Experiments on Nonlinear Dynamics & Chaos (And
Bibliography of instructional experiments on nonlinear dynamics and chaos Page 1 of 20 Colorado Virtual Campus of Physics Mechanics & Nonlinear Dynamics Cluster Nonlinear Dynamics & Chaos Lab Instructional Experiments on Nonlinear Dynamics & Chaos (and some related theory papers) overviews of nonlinear & chaotic dynamics prototypical nonlinear equations and their simulation analysis of data from chaotic systems control of chaos fractals solitons chaos in Hamiltonian/nondissipative systems & Lagrangian chaos in fluid flow quantum chaos nonlinear oscillators, vibrations & strings chaotic electronic circuits coupled systems, mode interaction & synchronization bouncing ball, dripping faucet, kicked rotor & other discrete interval dynamics nonlinear dynamics of the pendulum inverted pendulum swinging Atwood's machine pumping a swing parametric instability instabilities, bifurcations & catastrophes chemical and biological oscillators & reaction/diffusions systems other pattern forming systems & self-organized criticality miscellaneous nonlinear & chaotic systems -overviews of nonlinear & chaotic dynamics To top? Briggs, K. (1987), "Simple experiments in chaotic dynamics," Am. J. Phys. 55 (12), 1083-9. Hilborn, R. C. (2004), "Sea gulls, butterflies, and grasshoppers: a brief history of the butterfly effect in nonlinear dynamics," Am. J. Phys. 72 (4), 425-7. Hilborn, R. C. and N. B. Tufillaro (1997), "Resource Letter: ND-1: nonlinear dynamics," Am. J. Phys. 65 (9), 822-34. Laws, P. W. (2004), "A unit on oscillations, determinism and chaos for introductory physics students," Am. J. Phys. 72 (4), 446-52. Sungar, N., J. P. Sharpe, M. J. Moelter, N. Fleishon, K. Morrison, J. McDill, and R. Schoonover (2001), "A laboratory-based nonlinear dynamics course for science and engineering students," Am. J. Phys. 69 (5), 591-7. http://carbon.cudenver.edu/~rtagg/CVCP/Ctr_dynamics/Lab_nonlinear_dyn/Bibex_nonline.. -
Summary of Unit 3 Chaos and the Butterfly Effect
Summary of Unit 3 Chaos and the Butterfly Effect Introduction to Dynamical Systems and Chaos http://www.complexityexplorer.org The Logistic Equation ● A very simple model of a population where there is some limit to growth ● f(x) = rx(1-x) ● r is a growth parameter ● x is measured as a fraction of the “annihilation” parameter. ● f(x) gives the population next year given x, the population this year. David P. Feldman Introduction to Dynamical Systems http://www.complexityexplorer.org and Chaos Iterating the Logistic Equation ● We used an online program to iterate the logistic equation for different r values and make time series plots ● We found attracting periodic behavior of different periods and... David P. Feldman Introduction to Dynamical Systems http://www.complexityexplorer.org and Chaos Aperiodic Orbits ● For r=4 (and other values), the orbit is aperiodic. It never repeats. ● Applying the same function over and over again does not result in periodic behavior. David P. Feldman Introduction to Dynamical Systems http://www.complexityexplorer.org and Chaos Comparing Initial Conditions ● We used a different online program to compare time series for two different initial conditions. ● The bottom plot is the difference between the two time series in the top plot. David P. Feldman Introduction to Dynamical Systems http://www.complexityexplorer.org and Chaos Sensitive Dependence on Initial Conditions ● When r=4.0, two orbits that start very close together eventually end up far apart ● This is known as sensitive dependence on initial conditions, or the butterfly effect. David P. Feldman Introduction to Dynamical Systems http://www.complexityexplorer.org and Chaos Sensitive Dependence on Initial Conditions ● For any initial condition x there is another initial condition very near to it that eventually ends up far away ● To predict the behavior of a system with SDIC requires knowing the initial condition with impossible accuracy. -
Towards a Theory of Sustainable Prevention of Chagas Disease: an Ethnographic
Towards a Theory of Sustainable Prevention of Chagas Disease: An Ethnographic Grounded Theory Study A dissertation presented to the faculty of Ohio University In partial fulfillment of the requirements for the degree Doctor of Philosophy Claudia Nieto-Sanchez December 2017 © 2017 Claudia Nieto-Sanchez. All Rights Reserved. 2 This dissertation titled Towards a Theory of Sustainable Prevention of Chagas Disease: An Ethnographic Grounded Theory Study by CLAUDIA NIETO-SANCHEZ has been approved for the School of Communication Studies, the Scripps College of Communication, and the Graduate College by Benjamin Bates Professor of Communication Studies Mario J. Grijalva Professor of Biomedical Sciences Joseph Shields Dean, Graduate College 3 Abstract NIETO-SANCHEZ, CLAUDIA, Ph.D., December 2017, Individual Interdisciplinary Program, Health Communication and Public Health Towards a Theory of Sustainable Prevention of Chagas Disease: An Ethnographic Grounded Theory Study Directors of Dissertation: Benjamin Bates and Mario J. Grijalva Chagas disease (CD) is caused by a protozoan parasite called Trypanosoma cruzi found in the hindgut of triatomine bugs. The most common route of human transmission of CD occurs in poorly constructed homes where triatomines can remain hidden in cracks and crevices during the day and become active at night to search for blood sources. As a neglected tropical disease (NTD), it has been demonstrated that sustainable control of Chagas disease requires attention to structural conditions of life of populations exposed to the vector. This research aimed to explore the conditions under which health promotion interventions based on systemic approaches to disease prevention can lead to sustainable control of Chagas disease in southern Ecuador. -
Chaos: the Mathematics Behind the Butterfly Effect
Chaos: The Mathematics Behind the Butterfly E↵ect James Manning Advisor: Jan Holly Colby College Mathematics Spring, 2017 1 1. Introduction A butterfly flaps its wings, and a hurricane hits somewhere many miles away. Can these two events possibly be related? This is an adage known to many but understood by few. That fact is based on the difficulty of the mathematics behind the adage. Now, it must be stated that, in fact, the flapping of a butterfly’s wings is not actually known to be the reason for any natural disasters, but the idea of it does get at the driving force of Chaos Theory. The common theme among the two is sensitive dependence on initial conditions. This is an idea that will be revisited later in the paper, because we must first cover the concepts necessary to frame chaos. This paper will explore one, two, and three dimensional systems, maps, bifurcations, limit cycles, attractors, and strange attractors before looking into the mechanics of chaos. Once chaos is introduced, we will look in depth at the Lorenz Equations. 2. One Dimensional Systems We begin our study by looking at nonlinear systems in one dimen- sion. One of the important features of these is the nonlinearity. Non- linearity in an equation evokes behavior that is not easily predicted due to the disproportionate nature of inputs and outputs. Also, the term “system”isoftenamisnomerbecauseitoftenevokestheideaof asystemofequations.Thiswillbethecaseaswemoveourfocuso↵ of one dimension, but for now we do not want to think of a system of equations. In this case, the type of system we want to consider is a first-order system of a single equation. -
A Look Into the Nature of Complex Systems and Beyond “Stonehenge” Economics: Coping with Complexity Or Ignoring It in Applied Economics?
AGRICULTURAL ECONOMICS Agricultural Economics 37 (2007) 219–235 A look into the nature of complex systems and beyond “Stonehenge” economics: coping with complexity or ignoring it in applied economics? Chris Noell∗ Department of Agricultural Economics, University of Kiel, Germany Received 27 October 2006; received in revised form 23 July 2007; accepted 27 July 2007 Abstract Real-world economic systems are complex in general but can be approximated by the “open systems” approach. Economic systems are very likely to possess the basic and advanced emergent properties (e.g., self-organized criticality, fractals, attractors) of general complex systems.The theory of “self-organized criticality” is proposed as a major source of dynamic equilibria and complexity in economic systems. This is exemplified in an analysis for self-organized criticality of Danish agricultural subsectors, indicated by power law distributions of the monetary production value for the time period from 1963 to 1999. Major conclusions from the empirical part are: (1) The sectors under investigation are obviously self-organizing and thus very likely to show a range of complex properties. (2) The characteristics of the power law distributions that were measured might contain further information about the state or graduation of self-organization in the sector. Varying empirical results for different agricultural sectors turned out to be consistent with the theory of self-organized criticality. (3) Fully self-organizing sectors might be economically the most efficient. Finally,