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Complex Systems

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  • Harald Atmanspacher, A Semiotic Approach to Complex Systems.
    A key topic in the work of Burghard Rieger is the notion of meaning. To explore this notion, he and his collaborators developed a most sophisticated approach combining theoretical ideas and concepts of semiotics with empirical and numerical tools of computational linguistics (see [31] for a most recent comprehensive account). In the present contribution, relations of Rieger’s achievements to some issues of interest in the physics and philosophy of complex systems will be addressed.
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  • William P. Bechtel (2001). The Compatibility of Complex Systems and Reduction: A Case Analysis of Memory Research. Minds And Machines 11 (4):483-502.
    Some theorists who emphasize the complexity of biological and cognitive systems and who advocate the employment of the tools of dynamical systems theory in explaining them construe complexity and reduction as exclusive alternatives. This paper argues that reduction, an approach to explanation that decomposes complex activities and localizes the components within the complex system, is not only compatible with an emphasis on complexity, but provides the foundation for dynamical analysis. Explanation via decomposition and localization is nonetheless extremely challenging, and an (...)
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  • Michael J. Behe (2000). Self-Organization and Irreducibly Complex Systems: A Reply to Shanks and Joplin. Philosophy of Science 67 (1):155-162.
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  • Tom R. Burns (2006). The Sociology of Complex Systems: An Overview of Actor-System-Dynamics Theory. World Futures 62 (6):411 – 440.
    This article illustrates the important scientific role that a systems approach might play within the social sciences and humanities, above all through its contribution to a common language, shared conceptualizations, and theoretical integration in the face of the extreme (and growing) fragmentation among the social sciences (and between the social sciences and the natural sciences). The article outlines a systems theoretic approach, actor-system-dynamics (ASD), whose authors have strived to re-establish systems theorizing in the social sciences (after a period of marginalization (...)
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  • Paul Cilliers (1998). Complexity and Postmodernism: Understanding Complex Systems. Routledge.
    Complexity and Postmodernism explores the notion of complexity in the light of contemporary perspectives from philosophy and science. The book integrates insights from complexity and computational theory with the philosophical position of thinkers including Derrida and Lyotard. Paul Cilliers takes a critical stance towards the use of the analytical method as a tool to cope with complexity, and he rejects Searle's superficial contribution to the debate.
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  • John Collier, A Dynamical Approach to Identity and Diversity in Complex Systems.
    The subject of this chapter is the identity of individual dynamical objects and properties. Two problems have dominated the literature: transtemporal identity and the relation between composition and identity. Most traditional approaches to identity rely on some version of classification via essential or typical properties, whether nominal or real. Nominal properties have the disadvantage of producing unnatural classifications, and have several other problems. Real properties, however, are often inaccessible or hard to define (strict definition would make them nominal). I suggest (...)
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  • John Collier, Change and Identity in Complex Systems.
    Complex systems are dynamic and may show high levels of variability in both space and time. It is often difficult to decide on what constitutes a given complex system, i.e., where system boundaries should be set, and what amounts to substantial change within the system. We discuss two central themes: the nature of system definitions and their ability to cope with change, and the importance of system definitions for the mental metamodels that we use to describe and order ideas about (...)
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  • Bruce Edmonds, Understanding Observed Complex Systems – the Hard Complexity Problem.
    bruce@edmonds.name http://bruce.edmonds.name Abstract. Two kinds of problem are distinguished: the first of finding processes which produce complex outcomes from the interaction of simple parts, and the second of finding which process resulted in an observed complex outcome. The former I call the easy complexity problem and the later the hard complexity problem. It is often assumed that progress with the easy problem will aid process with the hard problem. However this assumes that the “reverse engineering” problem, of determining the process (...)
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  • Helena Knyazeva (2005). Figures of Time in Evolution of Complex Systems. Journal for General Philosophy of Science 36 (2).
    Owing to intensive development of the theory of self-organization of complex systems called also synergetics, profound changes in our notions of time occur. Whereas at the beginning of the 20th century, natural sciences, by picking up the general spirit of Einstein's theory of relativity, consider a geometrization as an ideal, i.e. try to represent time and force interactions through space and the changes of its properties, nowadays, at the beginning of the 21st century, time turns to be in the focus (...)
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  • Wayne Nahu Lanham (2008). The Spiral Template: The Revolution in the Evolution From Simple to Complex Systems. World Futures 64 (1):60 – 71.
    Change is an inborn trait of all organisms at every level of existence. This article proposes that the evolution of all life follows a course as if bound by a guiding principle or template. Overcoming disorder and entropy through diversity, this template has the properties of a spiral force, which acts to maintain continuity during change and transitions, and operates at all levels, from the simplest of forms to the most complex. Drawing from Chaos Theory, biology, depth psychology, and Buddhism, (...)
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  • Jay L. Lemke & Nora H. Sabelli (2008). Complex Systems and Educational Change: Towards a New Research Agenda. Educational Philosophy and Theory 40 (1):118–129.
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  • Kara Vander Linden (2006). A Grounded Approach to the Study of Complex Systems. World Futures 62 (7):491 – 497.
    The complex and dynamic nature of systems pose a particular challenge to researchers and require the use of a research methodology designed to deal with such systems. The properties of fit, relevance, understandability, generality, control, workability, generalizability, and modifiability make Glaserian grounded theory and grounded action particularly well suited for studying systems. These methods are innovative, systemic, and sophisticated enough to reveal the underlying complexities of systems and plan actions that address their complex, dynamic nature while remaining grounded in what (...)
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  • F. Mallamace & H. Eugene Stanley (eds.) (2004). The Physics of Complex Systems: New Advances and Perspectives. Ios Press.
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  • Jay Odenbaugh (2003). Complex Systems, Trade‐Offs, and Theoretical Population Biology: Richard Levin's “Strategy of Model Building in Population Biology” Revisited. Philosophy of Science 70 (5).
    Ecologist Richard Levins argues population biologists must trade‐off the generality, realism, and precision of their models since biological systems are complex and our limitations are severe. Steven Orzack and Elliott Sober argue that there are cases where these model properties cannot be varied independently of one another. If this is correct, then Levins's thesis that there is a necessary trade‐off between generality, precision, and realism in mathematical models in biology is false. I argue that Orzack and Sober's arguments fail since (...)
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  • Jay Odenbaugh, Complex Systems, Trade-Offs and Theoretical Population Biology: Richard Levin`S 'Strategy of Model Building in Population Biology' Revisited.
    Ecologist Richard Levins (1966, 1968) argues population biologists must trade-off the generality, realism and precision of their models since biological systems are complex and our limitations are severe. Elliott Sober and Steven Orzack (1993) argue that there are cases where these model properties cannot be varied independently of one another. If this is correct, then Levins` thesis that there is a necessary trade-off between generality, precision, and realism in mathematical models in biology is false. I argue that Sober and Orzack`s (...)
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  • S. Schweber, Wachter &unknown & M. (2000). Complex Systems, Modelling and Simulation. Studies in History and Philosophy of Science Part B 31 (4):583-609.
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  • David Jon Spurrett, Review Article Of: Cilliers, P. (1998) Complexity and Postmodernism: Understanding Complex Systems, London: Routledge.
    This is a review article of Paul Cillier's 1999 book _Complexity and Postmodernism_. The review article is generally encouraging and constructive, although isolates a number of areas in need of clarification or development in Cillier's work. The volume of the _South African Journal of Philosophy_ in which the review article appeared also printed a response by Cilliers.
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  • Andreas Wagner (1999). Causality in Complex Systems. Biology and Philosophy 14 (1).
    Systems involving many interacting variables are at the heart of the natural and social sciences. Causal language is pervasive in the analysis of such systems, especially when insight into their behavior is translated into policy decisions. This is exemplified by economics, but to an increasing extent also by biology, due to the advent of sophisticated tools to identify the genetic basis of many diseases. It is argued here that a regularity notion of causality can only be meaningfully defined for systems (...)
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  • William C. Wimsatt, The Ontology of Complex Systems: Levels of Organization, Perspectives, and Causal Thickets.
    Willard van Orman Quine once said that he had a preference for a desert ontology. This was in an earlier day when concerns with logical structure and ontological simplicity reigned supreme. Ontological genocide was practiced upon whole classes of upper-level or "derivative" entities in the name of elegance, and we were secure in the belief that one strayed irremediably into the realm of conceptual confusion and possible error the further one got from ontic fundamentalism. In those days, one paid more (...)
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  • Kazuko Yamasaki, Kaushik Matia, Fabio Pammolli, Sergey Buldyrev, Massimo Riccaboni, H. Eugene Stanley & Dongfeng Fu, Preferential Attachment and Growth Dynamics in Complex Systems.
    Complex systems can be characterized by classes of equivalency of their elements defined according to system specific rules. We propose a generalized preferential attachment model to describe the class size distribution. The model postulates preferential growth of the existing classes and the steady influx of new classes. According to the model, the distribution changes from a pure exponential form for zero influx of new classes to a power law with an exponential cut-off form when the influx of new classes is (...)
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Chaos
  • Peter Coles (2006). From Cosmos to Chaos: The Science of Unpredictability. Oxford University Press.
    Cosmology has undergone a revolution in recent years. The exciting interplay between astronomy and fundamental physics has led to dramatic revelations, including the existence of the dark matter and the dark energy that appear to dominate our cosmos. But these discoveries only reveal themselves through small effects in noisy experimental data. Dealing with such observations requires the careful application of probability and statistics. But it is not only in the arcane world of fundamental physics that probability theory plays such an (...)
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Nonlinear Dynamics
Systems Theory
  • Evandro Agazzi (1978). Systems Theory and the Problem of Reductionism. Erkenntnis 12 (3).
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  • Kenneth D. Bailey (2005). Emergence, Drop-Back and Reductionism in Living Systems Theory. Axiomathes 15 (1).
    Millers Living Systems Theory (LST) is known to be very comprehensive. It comprises eight nested hierarchical levels. It also includes twenty critical subsystems. While Millers approach has been analyzed and applied in great detail, some problematic features remain, requiring further explication. One of these is the relationship between reduction and emergence in LST. There are at least four relevant possibilities. One is that LST exhibits neither clear reductionism nor emergence, but is essentially neutral in this regard. Another is that the (...)
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  • Philip Barnard & Tim Dalgleish (2005). Psychological-Level Systems Theory: The Missing Link in Bridging Emotion Theory and Neurobiology Through Dynamic Systems Modeling. Behavioral and Brain Sciences 28 (2):196-197.
    Bridging between psychological and neurobiological systems requires that the system components are closely specified at both the psychological and brain levels of analysis. We argue that in developing his dynamic systems theory framework, Lewis has sidestepped the notion of a psychological level systems model altogether, and has taken a partisan approach to his exposition of a brain-level systems model.
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  • James A. Blachowicz (1971). Systems Theory and Evolutionary Models of the Development of Science. Philosophy of Science 38 (2):178-199.
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  • Wayne Christensen (1996). A Complex Systems Theory of Teleology. Biology and Philosophy 11 (3).
    Part I [sections 2–4] draws out the conceptual links between modern conceptions of teleology and their Aristotelian predecessor, briefly outlines the mode of functional analysis employed to explicate teleology, and develops the notion of cybernetic organisation in order to distinguish teleonomic and teleomatic systems. Part II is concerned with arriving at a coherent notion of intentional control. Section 5 argues that intentionality is to be understood in terms of the representational properties of cybernetic systems. Following from this, section 6 argues (...)
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  • Daniel Dennett, Intentional Systems Theory.
    Intentional systems theory is in the first place an analysis of the meanings of such everyday ‘mentalistic’ terms as ‘believe,’ ‘desire,’ ‘expect,’ ‘decide,’ and ‘intend,’ the terms of ‘folk psychology’ (Dennett 1971) that we use to interpret, explain, and predict the behavior of other human beings, animals, some artifacts such as robots and computers, and indeed ourselves. In traditional parlance, we seem to be attributing minds to the things we thus interpret, and this raises a host of questions about the (...)
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  • Dave Elder-Vass (2007). Luhmann and Emergentism: Competing Paradigms for Social Systems Theory? Philosophy of the Social Sciences 37 (4).
    Social systems theory has been dominated in recent years by the work of Niklas Luhmann, but there is another strand of systems thinking, which is receiving increasing attention in sociology: emergentism. For emergentism, the core problems of systems thinking are concerned with causation and reductionism; for Luhmann, they are questions of meaning and self-reference. Arguing from an emergentist perspective, the article finds that emergentism addresses its own core problem successfully, while Luhmann's approach is incapable of resolving questions of causation and (...)
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  • Alan Fogel, Ilse de Koeyer, Cory Secrist & Ryan Nagy (2002). Dynamic Systems Theory Places the Scientist in the System. Behavioral and Brain Sciences 25 (5):623-624.
    Dynamic systems theory is a way of describing the patterns that emerge from relationships in the universe. In the study of interpersonal relationships, within and between species, the scientist is an active and engaged participant in those relationships. Separation between self and other, scientist and subject, runs counter to systems thinking and creates an unnecessary divide between humans and animals.
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  • Roman Frigg (2004). In What Sense is the Kolmogorov-Sinai Entropy a Measure for Chaotic Behaviour?—Bridging the Gap Between Dynamical Systems Theory and Communication Theory. British Journal for the Philosophy of Science 55 (3).
    On an influential account, chaos is explained in terms of random behaviour; and random behaviour in turn is explained in terms of having positive Kolmogorov-Sinai entropy (KSE). Though intuitively plausible, the association of the KSE with random behaviour needs justification since the definition of the KSE does not make reference to any notion that is connected to randomness. I provide this justification for the case of Hamiltonian systems by proving that the KSE is equivalent to a generalized version of Shannon's (...)
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  • Peter Godfrey-Smith (2000). Explanatory Symmetries, Preformation, and Developmental Systems Theory. Philosophy of Science 67 (3):331.
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  • Paul E. Griffiths & Russell D. Gray (2005). Discussion: Three Ways to Misunderstand Developmental Systems Theory. Biology and Philosophy 20 (2-3).
    Developmental systems theory (DST) is a general theoretical perspective on development, heredity and evolution. It is intended to facilitate the study of interactions between the many factors that influence development without reviving `dichotomous' debates over nature or nurture, gene or environment, biology or culture. Several recent papers have addressed the relationship between DST and the thriving new discipline of evolutionary developmental biology (EDB). The contributions to this literature by evolutionary developmental biologists contain three important misunderstandings of DST.
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  • Ian I. Mitroff & Francisco Sagasti (1973). Epistemology as General Systems Theory: An Approach to the Design of Complex Decision-Making Experiments. Philosophy of the Social Sciences 3 (1).
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  • David Morris (2004). The Sense of Space. State University of New York Press.
    The Sense of Space brings together space and body to show that space is a plastic environment, charged with meaning, that reflects the distinctive character of human embodiment in the full range of its moving, perceptual, emotional, expressive, developmental, and social capacities. Drawing on the philosophies of Merleau-Ponty and Bergson, as well as contemporary psychology to develop a renewed account of the moving, perceiving body, the book suggests that our sense of space ultimately reflects our ethical relations to other people (...)
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  • David Morris (2002). Thinking the Body, From Hegel's Speculative Logic of Measure to Dynamic Systems Theory. Journal of Speculative Philosophy 16 (3):182-197.
    A study of shifts in scientific strategies for measuring the living body, especially in dynamic systems theory: (1) sheds light on Hegel's concept of measure in The Science of Logic, and the dialectical transition from categories of being to categories of essence; (2) shows how Hegel's speculative logic anticipates and analyzes key tensions in scientific attempts to measure and conceive the dynamic agency of the body. The study's analysis of the body as having an essentially dynamic identity irreducible to measurement (...)
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  • Erik Myin & Sonja Smets (2002). Could Dancing Be Coupled Oscillation? – The Interactive Approach to Linguistic Communication and Dynamical Systems Theory. Behavioral and Brain Sciences 25 (5):634-635.
    Although we applaud the interactivist approach to language and communication taken in the target article, we notice that Shanker & King (S&K) give little attention to the theoretical frameworks developed by dynamical system theorists. We point out how the dynamical idea of causality, viewed as multidirectional across multiple scales of organization, could further strengthen the position taken in the target article.
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  • Susan Oyama (2000). Causal Democracy and Causal Contributions in Developmental Systems Theory. Philosophy of Science 67 (3):347.
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  • Andreas Pickel (2007). Rethinking Systems Theory: A Programmatic Introduction. Philosophy of the Social Sciences 37 (4).
    Does systems theory need rethinking? Most social scientists would probably say no. It had its run, was debated critically, and found wanting. If at all, it should be treated historically. Why then might systems theory need rethinking, as the title of this symposium claims? The reason is that, unlike in the natural and biosocial sciences, any conception of system in the social sciences has remained suspect in the wake of problematic Parsonian and cybernetic systems theories. The premise of this special (...)
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  • Teed Rockwell (2005). Attractor Spaces as Modules: A Semi-Eliminative Reduction of Symbolic AI to Dynamic Systems Theory. Minds and Machines 15 (1):23-55.
    I propose a semi-eliminative reduction of Fodors concept of module to the concept of attractor basin which is used in Cognitive Dynamic Systems Theory (DST). I show how attractor basins perform the same explanatory function as modules in several DST based research program. Attractor basins in some organic dynamic systems have even been able to perform cognitive functions which are equivalent to the If/Then/Else loop in the computer language LISP. I suggest directions for future research programs which could find similar (...)
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  • Odis E. Simmons (2006). Some Professional and Personal Notes on Research Methods, Systems Theory, and Grounded Action. World Futures 62 (7):481 – 490.
    Academic social scientists and professional practitioners could increase the effectiveness of their undertakings to advance positive change toward solving social and organizational problems by more effectively combining their efforts. Historically, both realms have used reductionist techniques and methodologies that are unsuited for understanding and solving problems in social and organizational systems. Their efforts could be significantly enhanced by using a grounded theory/grounded action approach. Grounded theory/grounded action is designed to generate explanations directly from data that provide a theoretical foothold for (...)
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  • Susan Stillman (2006). Grounded Theory and Grounded Action: Rooted in Systems Theory. World Futures 62 (7):498 – 504.
    The research methodologies of grounded theory and grounded action are framed by a systems perspective, from which they contribute their own unique properties and processes to the evolution of systems thinking. The author provides definitions for systems, theory, grounded theory, grounded action, and systems thinking, and explores the relationships between theory, grounded theory/grounded action, and systems thinking with regard to purpose, context, and usefulness for the resolution of social concerns and systemic change.
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  • Marco Van Leeuwen (2005). Questions for the Dynamicist: The Use of Dynamical Systems Theory in the Philosophy of Cognition. Minds and Machines 15 (3-4):271-333.
    The concepts and powerful mathematical tools of Dynamical Systems Theory (DST) yield illuminating methods of studying cognitive processes, and are even claimed by some to enable us to bridge the notorious explanatory gap separating mind and matter. This article includes an analysis of some of the conceptual and empirical progress Dynamical Systems Theory is claimed to accomodate. While sympathetic to the dynamicist program in principle, this article will attempt to formulate a series of problems the proponents of the approach in (...)
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  • G. P. Wagner (1983). On the Necessity of a Systems Theory of Evolution and its Population Biologic Foundation: Comments on Dr. Regelmann's Article. Acta Biotheoretica 32 (3).
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  • Gerhard Wagner (1997). The End of Luhmann's Social Systems Theory. Philosophy of the Social Sciences 27 (4).
    By advocating an enlightened method of theorizing committed to thinking in terms of a system of differences, Luhmann has contributed to the development of sociology in a manner that cannot be praised enough. Nonetheless, he does not succeed in giving an account of his own position that satisfies the very logical preconditions that he himself has formulated for it. Instead, his systems theory paradigm of sociology is based on metaphysical premises characteristic of the identity-logical thought of "Old Europe." In fact, (...)
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