Bookmark and Share

Complex Systems

Edited by Jon Lawhead (University of Southern California)
About this topic
Summary The study of complex systems is an interdisciplinary field that examines how the interaction of many parts can give rise to holistic collective behavior at the system level.  Contemporary complex systems science is a synthesis of many different areas of inquiry, including non-linear dynamical systems theory, chaos theory, cybernetics, control theory, information theory, multiscale modeling, and non-equilibrium statistical mechanics.  There is as-yet no widely accepted general definition of "complex system," but a few common themes or properties can be observed.  Complex systems frequently tend to display self-organization, autopoiesis, non-linearity in their dynamics, chaotic behavior, emergent properties, adaptation or some combination of these traits.  In the natural sciences, the global climate, the economy, neural networks, and living organisms are among the systems generally regarded as "complex," and the methods or tools of complex systems theory are frequently applied to their study.  A holistic understanding of complex systems frequently involves contributions from many areas, including both the social and physical sciences as well as the humanities.  Given the challenges associated with coordinating this kind of vast interdisciplinary collaboration, philosophy--with its emphasis on what Wilfrid Sellars famously called "bridge-building" between disparate disciplines--has a clear and obvious role to play.  The study of complex systems also overlaps with a number of traditional problems in the philosophy of science and metaphysics, including mereology, the nature of laws and explanations, supervenience, emergence and reduction, the scale-relativity of ontology, and functionalism.  Applied philosophical issues raised by complex systems include: how do we understand causation and explanation in systems that require analysis from multiple perspectives, and which resist hierarchical organizational schemes?  Can computer simulations and multi-scale modeling provide a new way to explore strong emergence and self-organization?  How can we design organizational systems to most effectively engage in collaborative decision making while still mitigating the risks associated with large-scale collective action problems?  These questions are of extremely general importance as we move forward into the 21st century, and how we choose to address them will have implications for a diverse set of topics: challenges like how to meet the problems posed by anthropogenic climate change, how the digital revolution stands to impact our social organizations, how human society will cope with increasingly autonomous artificially intelligent agents, and how to design or manage the behavior of novel complex adaptive organisms all involve coming to grips with complexity theoretic concepts to some degree.
Key works Work in the fields from which modern complexity theory emerged, including information theory (Weaver 1948), chaos theory (Lorenz 1963; Prigogine 1984), statistical physics (Anderson 1994), and cybernetics (Simon 1962) are important for a foundational understanding of the relevant concepts.  Important early works in complexity theory include Lloyd & Pagels 1988 and Gell-Mann 1995.  More contemporary contributions have been made by Bar‐Yam 2004 (which explores the mathematical foundations of strong emergence), Ladyman et al 2013 (which offers a taxonomy of definitions of 'complexity'), and Hooker 2013 (which explores the physical underpinnings of complex dynamics).
Introductions Mitchell 2009Auyang 1999Hooker msMitchell 2012Dennett 1991
  Show all references
Related categories
Subcategories:
606 found
Search inside:
(import / add options)   Order:
1 — 50 / 606
Chaos
  1. H. D. I. Abarbanel (1992). Local Lyapunov Exponents Computed From Observed Data. Journal of Nonlinear Science 2 (3):343-365.
    We develop methods for determining local Lyapunov exponents from observations of a scalar data set. Using average mutual information and the method of false neighbors, we reconstruct a multivariate time series, and then use local polynomial neighborhood-to-neighborhood maps to determine the phase space partial derivatives required to compute Lyapunov exponents. In several examples we demonstrate that the methods allow one to accurately reproduce results determined when the dynamics is known beforehand. We present a new recursive QR decomposition method for finding (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
  2. A. Abbasi, S. H. Fathi, G. B. Gharehpatian, A. Gholami & H. R. Abbasi (2013). Voltage Transformer Ferroresonance Analysis Using Multiple Scales Method and Chaos Theory. Complexity 18 (6):34-45.
    Remove from this list   Direct download (5 more)  
     
    Export citation  
     
    My bibliography   7 citations  
  3. Ralph Abraham (1994). Chaos, Gaia, Eros a Chaos Pioneer Uncovers the Three Great Streams of History.
    Remove from this list  
     
    Export citation  
     
    My bibliography   1 citation  
  4. Philip Anderson & Jack Cohen (1999). Reviews: Coping with Uncertainty, Insights From the New Sciences of Chaos, Self-Organization, and Complexity, Uri Merry. [REVIEW] Emergence: Complexity and Organization 1 (2):106-108.
    (1999). Reviews: Coping with Uncertainty, Insights from the New Sciences of Chaos, Self-Organization, and Complexity, Uri Merry. Emergence: Vol. 1, No. 2, pp. 106-108.
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    My bibliography  
  5. S. M. Anlage (2000). Book Review: Quantum Chaos-An Introduction. [REVIEW] Foundations of Physics 30 (7):1135-1138.
  6. I. Antoniou & Z. Suchanecki (1997). The Fuzzy Logic of Chaos and Probabilistic Inference. Foundations of Physics 27 (3):333-362.
    The logic of a physical system consists of the elementary observables of the system. We show that for chaotic systems the logic is not any more the classical Boolean lattice but a kind of fuzzy logic which we characterize for a class of chaotic maps. Among other interesting properties the fuzzy logic of chaos does not allow for infinite combinations of propositions. This fact reflects the instability of dynamics and it is shared also by quantum systems with diagonal singularity. We (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    My bibliography  
  7. Fatihcan M. Atay, Sarika Jalan & Jürgen Jost (2009). Randomness, Chaos, and Structure. Complexity 15 (1):29-35.
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    My bibliography   2 citations  
  8. Harald Atmanspacher, Characterizing Spontaneous Irregular Behavior in Coupled Map Lattices.
    Two-dimensional coupled map lattices display, in a specific parameter range, a stable phase (quasi-) periodic in both space and time. With small changes to the model parameters, this stable phase develops spontaneous eruptions of nonperiodic behavior. Although this behavior itself appears irregular, it can be characterized in a systematic fashion. In particular, parameter-independent features of the spontaneous eruptions may allow useful empirical characterizations of other phenomena that are intrinsically hard to predict and reproduce. Specific features of the distributions of lifetimes (...)
    Remove from this list  
     
    Export citation  
     
    My bibliography  
  9. Harald Atmanspacher, Ontic and Epistemic Descriptions of Chaotic Systems.
    Traditional philosophical discourse draws a distinction between ontology and epistemology and generally enforces this distinction by keeping the two subject areas separated and unrelated. In addition, the relationship between the two areas is of central importance to physics and philosophy of physics. For instance, all kinds of measurement-related problems force us to consider both our knowledge of the states and observables of a system (epistemic perspective) and its states and observables independent of such knowledge (ontic perspective). This applies to quantum (...)
    Remove from this list  
     
    Export citation  
     
    My bibliography  
  10. David Aubin (1998). A Cultural History of Catastrophes and Chaos: Around the Institut des Hautes Études Scientifiques. Princeton.
    Remove from this list  
     
    Export citation  
     
    My bibliography  
  11. David Aubin & Amy Dalmedico (2002). Writing the History of Dynamics Systems and Chaos: Longue Durée and Revolution, Disciplines and Cultures. Historia Mathematica 29:1–67.
    Remove from this list  
     
    Export citation  
     
    My bibliography  
  12. Sunny Auyang, How Science Comprehends Chaos.
    Behaviors of chaotic systems are unpredictable. Chaotic systems are deterministic, their evolutions being governed by dynamical equations. Are the two statements contradictory? They are not, because the theory of chaos encompasses two levels of description. On a higher level, unpredictability appears as an emergent property of systems that are predictable on a lower level. In this talk, we examine the structure of dynamical theories to see how they employ multiple descriptive levels to explain chaos, bifurcation, and other complexities of nonlinear (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
  13. R. Badii (1997). Complexity: Hierarchical Structures and Scaling in Physics. Cambridge University Press.
    This is a comprehensive discussion of complexity as it arises in physical, chemical, and biological systems, as well as in mathematical models of nature. Common features of these apparently unrelated fields are emphasised and incorporated into a uniform mathematical description, with the support of a large number of detailed examples and illustrations. The quantitative study of complexity is a rapidly developing subject with special impact in the fields of physics, mathematics, information science, and biology. Because of the variety of the (...)
    Remove from this list  
     
    Export citation  
     
    My bibliography   9 citations  
  14. Arek Bagiânski & Agnieszka Wierzchucka (1999). Chaos.
    Remove from this list  
     
    Export citation  
     
    My bibliography  
  15. Gerold Baier (1995). A Strategy for Higher Chaos. In R. J. Russell, N. Murphy & A. R. Peacocke (eds.), Chaos and Complexity. Vatican Observatory Publications 189.
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
  16. Riccardo Baldissone (2013). Chaos Beyond Order: Overcoming the Quest for Certainty and Conservation in Modern Western Sciences. Cosmos and History: The Journal of Natural and Social Philosophy 9 (1):35-49.
    Chaos theory not only stretched the concept of chaos well beyond its traditional semantic boundaries, but it also challenged fundamental tenets of physics and science in general. Hence, its present and potential impact on the Western worldview cannot be underestimated. I will illustrate the relevance of chaos theory in regard to modern Western thought by tracing the concept of order, which modern thinkers emphasised as chaos’ dichotomic counterpart. In particular, I will underline how the concern of seventeenth-century natural philosophers with (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    My bibliography  
  17. Robert W. Batterman (1993). Defining Chaos. Philosophy of Science 60 (1):43-66.
    This paper considers definitions of classical dynamical chaos that focus primarily on notions of predictability and computability, sometimes called algorithmic complexity definitions of chaos. I argue that accounts of this type are seriously flawed. They focus on a likely consequence of chaos, namely, randomness in behavior which gets characterized in terms of the unpredictability or uncomputability of final given initial states. In doing so, however, they can overlook the definitive feature of dynamical chaos--the fact that the underlying motion generating the (...)
    Remove from this list   Direct download (6 more)  
     
    Export citation  
     
    My bibliography   8 citations  
  18. Robert W. Batterman (1991). Chaos, Quantization, and the Correspondence Principle. Synthese 89 (2):189 - 227.
  19. Robert W. Batterman & Homer White (1996). Chaos and Algorithmic Complexity. Foundations of Physics 26 (3):307-336.
    Our aim is to discover whether the notion of algorithmic orbit-complexity can serve to define “chaos” in a dynamical system. We begin with a mostly expository discussion of algorithmic complexity and certain results of Brudno, Pesin, and Ruelle (BRP theorems) which relate the degree of exponential instability of a dynamical system to the average algorithmic complexity of its orbits. When one speaks of predicting the behavior of a dynamical system, one usually has in mind one or more variables in the (...)
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    My bibliography   3 citations  
  20. Roger A. Beaumont (1994). War, Chaos, and History. Monograph Collection (Matt - Pseudo).
    Remove from this list  
     
    Export citation  
     
    My bibliography   1 citation  
  21. Christopher Belanger (2013). On Two Mathematical Definitions of Observational Equivalence: Manifest Isomorphism and Epsilon-Congruence Reconsidered. Studies in History and Philosophy of Science Part B 44 (2):69-76.
    In this article I examine two mathematical definitions of observational equivalence, one proposed by Charlotte Werndl and based on manifest isomorphism, and the other based on Ornstein and Weiss’s ε-congruence. I argue, for two related reasons, that neither can function as a purely mathematical definition of observational equivalence. First, each definition permits of counterexamples; second, overcoming these counterexamples will introduce non-mathematical premises about the systems in question. Accordingly, the prospects for a broadly applicable and purely mathematical definition of observational equivalence (...)
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    My bibliography  
  22. Gordon Belot & John Earman (1997). Chaos Out of Order: Quantum Mechanics, the Correspondence Principle and Chaos. Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 28 (2):147-182.
    A vast amount of ink has been spilled in both the physics and the philosophy literature on the measurement problem in quantum mechanics. Important as it is, this problem is but one aspect of the more general issue of how, if at all, classical properties can emerge from the quantum descriptions of physical systems. In this paper we will study another aspect of the more general issue-the emergence of classical chaos-which has been receiving increasing attention from physicists but which has (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    My bibliography  
  23. Gordon Belot & Lina Jansson (2010). Alisa Bokulich, Reexamining the Quantum-Classical Relation: Beyond Reductionism and Pluralism , Cambridge University Press, Cambridge (2008) ISBN 978-0-521-85720-8 Pp. X+195. [REVIEW] Studies in History and Philosophy of Science Part B 41 (1):81-83.
  24. Andrew Belsey (1994). Chaos and Order, Environment and Anarchy. Royal Institute of Philosophy Supplement 36:157-167.
    The distinction between chaos and order has been central to western philosophy, both in metaphysics and politics. At the beginning, it was intrinsic to presocratic natural philosophy, and shortly after that to the cosmology and social philosophy of Plato. Even in the pre-presocratic period there were important intimations of it. Thus Hesiod tells us that ‘first of all did Chaos come into being’ —although exactly what is meant by ‘chaos’ in this context is not clear. between earth and sky . (...)
    Remove from this list   Direct download (5 more)  
     
    Export citation  
     
    My bibliography  
  25. Melvyn S. Berger (1995). Order Beyond Periodicity: Fighting Chaos for Quasiperiodic Motion of Nonlinear Hamiltonian Systems. In R. J. Russell, N. Murphy & A. R. Peacocke (eds.), Chaos and Complexity. Vatican Observatory Publications 185.
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
  26. K.-F. Berggren & T. Ouchterlony (2001). Chaos in a Quantum Dot with Spin-Orbit Coupling. Foundations of Physics 31 (2):233-242.
    Level statistics and nodal point distribution in a rectangular semiconductor quantum dot are studied for different degrees of spin-orbit coupling. The chaotic features occurring from the spin-orbit coupling have no classical counterpart. Using experimental values for GaSb/InAs/GaSb semiconductor quantum wells we find that level repulsion can lead to the semi-Poisson distribution for nearest level separations. Nodal lines and nodal points are also investigated. Comparison is made with nodal point distributions for fully chaotic states.
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    My bibliography  
  27. Robert C. Bishop & Frederick M. Kronz (1999). Is Chaos Indeterministic? In Maria Luisa Dalla Chiara (ed.), Language, Quantum, Music. 129--141.
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography   2 citations  
  28. Marcel Bodea (2005). Chaos and Determinism: Prediction and Anticipation – a Conceptual Distinction. Studia Philosophica 1.
    Today, it is difficult to find much unanimity in what is “the prediction”. New mathematical theories offer the support for an epistemological investigation of predictability. Chaos breaks across the lines that separate the scientific predictions. Chaos poses new conceptual problems in philosophy. Prediction and Anticipation is a conceptual distinction between numerical predictions and geometrical `predictions`. Anticipation means to see what kind of theoretical picture one could develop. Conceptual analysis on a philosophical level is an operational way to clarify the so (...)
    Remove from this list  
     
    Export citation  
     
    My bibliography  
  29. Marcel Bodea (2002). Chaos and Determinism From the Standpoint of the Sensibility to Initial Conditions: An Epistemological Approach. Studia Philosophica 2.
    The classical determinism is the view for which the only barrier to prediction is our lack of knowledge, due to a lack of observational data or to the lack of knowledge of the relevant laws of nature. A new mathematical theory, called CHAOS, offers a way of understanding order, order masquerading as randomness. My purpose here is an epistemological investigation: to examine a new area of scientific and philosophic inquiry, called ‘deterministic chaos’; to analyse the determinism in relation to unpredictability (...)
    Remove from this list  
     
    Export citation  
     
    My bibliography  
  30. O. Bohigas, P. Lebœuf & M. J. Sánchez (2001). Spectral Spacing Correlations for Chaotic and Disordered Systems. Foundations of Physics 31 (3):489-517.
    New aspects of spectral fluctuations of (quantum) chaotic and diffusive systems are considered, namely autocorrelations of the spacing between consecutive levels or spacing autocovariances. They can be viewed as a discretized two point correlation function. Their behavior results from two different contributions. One corresponds to (universal) random matrix eigenvalue fluctuations, the other to diffusive or chaotic characteristics of the corresponding classical motion. A closed formula expressing spacing autocovariances in terms of classical dynamical zeta functions, including the Perron–Frobenius operator, is derived. (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    My bibliography  
  31. Oriol Bohigas, Patricio Leboeuf & M. J. Sanchez (2001). Spectral Spacing Correlations for Chaotic and Disordered Systems. Foundations of Physics 31 (3):489-517.
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    My bibliography  
  32. Norbert W. Bolz (1992). Chaos Und Simulation. Monograph Collection (Matt - Pseudo).
    Remove from this list  
     
    Export citation  
     
    My bibliography  
  33. D. M. Borchert (ed.) (2006). Encyclopedia of Philosophy, Second Edition.
    Remove from this list  
    Translate
     
     
    Export citation  
     
    My bibliography  
  34. Moses Boudourides (1996). Chaos and Critical Theory. Neusis 5:115-121.
    Remove from this list  
     
    Export citation  
     
    My bibliography   1 citation  
  35. Alain Boutot (1991). La philosophie du chaos. Revue Philosophique de la France Et de l'Etranger 181 (2):145 - 178.
    Remove from this list  
    Translate
      Direct download  
     
    Export citation  
     
    My bibliography  
  36. Seamus Bradley, Scientific Uncertainty: A User's Guide. Grantham Institute on Climate Change Discussion Paper.
    There are different kinds of uncertainty. I outline some of the various ways that uncertainty enters science, focusing on uncertainty in climate science and weather prediction. I then show how we cope with some of these sources of error through sophisticated modelling techniques. I show how we maintain confidence in the face of error.
    Remove from this list  
    Translate
      Direct download  
     
    Export citation  
     
    My bibliography  
  37. Robert E. Brooks (1998). Creativity and the Cathartic Moment: Chaos Theory and the Art of Theatre. Dissertation, Louisiana State University and Agricultural & Mechanical College
    This dissertation investigates the potential applications of the scientific paradigm known as "chaos theory" in the examination of dramatic theory. By illuminating the limitations of traditional Newtonian physics and Euclidean geometry, chaos theory conveys philosophical implications that transcend the scientific and provide suitable tools for describing cultural and artistic phenomena. These implications include emphasis on unpredictability, interaction and feedback, qualitative rather that quantitative analyses, and a nonlinear, continuous, even holistic perspective of systems traditionally viewed as dischotomous . ;This study examines (...)
    Remove from this list  
     
    Export citation  
     
    My bibliography  
  38. L. Brown & J. Brown, Out of Chaos and Into a New Identity.
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
  39. Stephen Brush (1986). Order Out of Chaos: Man's New Dialogue with Nature. [REVIEW] British Journal for the History of Science 19 (3):371-372.
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
  40. Jean E. Burns (2007). Vacuum Radiation, Entropy, and Molecular Chaos. Foundations of Physics 37 (12):1727-1737.
    Vacuum radiation causes a particle to make a random walk about its dynamical trajectory. In this random walk the root mean square change in spatial coordinate is proportional to t 1/2, and the fractional changes in momentum and energy are proportional to t −1/2, where t is time. Thus the exchange of energy and momentum between a particle and the vacuum tends to zero over time. At the end of a mean free path the fractional change in momentum of a (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    My bibliography  
  41. John L. Casti (1996). Chaos Data Analyzer. Complexity 2 (2):46-47.
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    My bibliography  
  42. C. M. Caves (1994). Quantum Theory: Concepts and Methods. Foundations of Physics 24:1583-1583.
  43. Carlton M. Caves & R.�Diger Schack (1997). Unpredictability, Information, and Chaos. Complexity 3 (1):46-57.
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    My bibliography  
  44. Hugues Chat (1995). Towards a Thermodynamic Approach of Spatiotemporal Chaos. In R. J. Russell, N. Murphy & A. R. Peacocke (eds.), Chaos and Complexity. Vatican Observatory Publications 31.
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
  45. Boris V. Chirikov (1986). Transient Chaos in Quantum and Classical Mechanics. Foundations of Physics 16 (1):39-49.
    Bogolubov's classical example of statistical relaxation in a many-dimensional linear oscillator is discussed. The relation of the discovered relaxation mechanism to quantum dynamics as well as to some new problems in classical mechanics is considered.
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    My bibliography  
  46. Kamila Chodarcewicz (2008). Podmiot, chaos i ironia. Friedricha Schlegla pytania o kształtowanie jednostki. Estetyka I Krytyka 1 (1):83-92.
    Remove from this list  
    Translate
     
     
    Export citation  
     
    My bibliography  
  47. John Cleave & Ian J. Thompson (1988). Chaos and Order: An Interview with Professor Michael Berry F.R.S. Cogito 2 (1):1-5.
    Michael Berry, Professor of Physics at Bristol University, discusses the philosophical ideas underlying his research to the theories of catastrophes and chaotic systems. He is one of England's leading scientists, and has been instrumental in the growth of interest in qualitative phenomena.
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    My bibliography  
  48. R. Clifton (1995). Quantum Theory: Concepts and Methods. Foundations of Physics 25:205-205.
  49. 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 (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
  50. M. Colyvan (2005). Bigger Than Chaos: Understanding Complexity Through Probability. Biology and Philosophy 20 (4):869-879.
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
1 — 50 / 606