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  1. Structural Modeling Error and the System Individuation Problem.Jon Lawhead - forthcoming - British Journal for the Philosophy of Science.
    Recent work by Frigg et. al. and Mayo-Wilson have called attention to a particular sort of error associated with attempts to model certain complex systems: structural modeling error. The assessment of the degree of SME in a model presupposes agreement between modelers about the best way to individuate natural systems, an agreement which can be more problematic than it appears. This problem, which we dub “the system individuation problem” arises in many of the same contexts as SME, and the two (...)
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  2. Stability in Cosmology, From Einstein to Inflation.C. D. McCoy - 2020 - In Claus Beisbart, Tilman Sauer & Christian Wüthrich (eds.), Thinking About Space and Time. Cham: Birkhäuser. pp. 71-89.
    I investigate the role of stability in cosmology through two episodes from the recent history of cosmology: Einstein’s static universe and Eddington’s demonstration of its instability, and the flatness problem of the hot big bang model and its claimed solution by inflationary theory. These episodes illustrate differing reactions to instability in cosmological models, both positive ones and negative ones. To provide some context to these reactions, I also situate them in relation to perspectives on stability from dynamical systems theory and (...)
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  3. Panpsichismo, teoria della complessità e proprietà quanto-psicoidi del Sè.Donato Santarcangelo - 2020 - Ombra 13.
    The thesis of this paper is that panpsychism theory is very close to jungian theory, especially thinking of the quantum psychoid aspects of C.G.Jung and W.Pauli theory: a psyche that touches matter and matter with a “latent psyche”. The two theories seem to describe the same reality, an animation of matter in a spiritual sense, as the jungian Self seems to do at a higher level.The complexity theory appears instead to be a description of reality still nomothetic.
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  4. Stable Regularities Without Governing Laws?Aldo Filomeno - 2019 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 66:186-197.
    Can stable regularities be explained without appealing to governing laws or any other modal notion? In this paper, I consider what I will call a ‘Humean system’—a generic dynamical system without guiding laws—and assess whether it could display stable regularities. First, I present what can be interpreted as an account of the rise of stable regularities, following from Strevens [2003], which has been applied to explain the patterns of complex systems (such as those from meteorology and statistical mechanics). Second, since (...)
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  5. Человек – это память.Andrej Poleev - 2019 - Enzymes 17.
    Человек – это память. Чтобы понять, что такое человек, необходимо понять, что такое память.
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  6. Being Emergence Vs. Pattern Emergence: Complexity, Control, and Goal-Directedness in Biological Systems.Jason Winning & William Bechtel - 2019 - In Sophie Gibb, Robin Hendry & Tom Lancaster (eds.), The Routledge Handbook of Philosophy of Emergence. London: pp. 134-144.
    Emergence is much discussed by both philosophers and scientists. But, as noted by Mitchell (2012), there is a significant gulf; philosophers and scientists talk past each other. We contend that this is because philosophers and scientists typically mean different things by emergence, leading us to distinguish being emergence and pattern emergence. While related to distinctions offered by others between, for example, strong/weak emergence or epistemic/ontological emergence (Clayton, 2004, pp. 9–11), we argue that the being vs. pattern distinction better captures what (...)
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  7. Mind the Physics: Physics of Mind.Andrew And Alexander Fingelkurts - 2018 - Physics of Life Reviews 25:75-77.
    The target paper of Schoeller, Perlovsky, and Arseniev is an essential and timely contribution to a current shift of focus in neuroscience aiming to merge neurophysiological, psychological and physical principles in order to build the foundation for the physics of mind. Extending on previous work of Perlovsky et al. and Badre, the authors of the target paper present interesting mathematical models of several basic principles of the physics of mind, such as perception and cognition, concepts and emotions, instincts and learning. (...)
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  8. Complex Organisation and Fundamental Physics.Brian D. Josephson - 2018 - Streaming Media Service, Cambridge University.
    The file on this site provides the slides for a lecture given in Hangzhou in May 2018, and the lecture itself is available at the URL beginning 'sms' in the set of links provided in connection with this item. -/- It is commonly assumed that regular physics underpins biology. Here it is proposed, in a synthesis of ideas by various authors, that in reality structures and mechanisms of a biological character underpin the world studied by physicists, in principle supplying detail (...)
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  9. De amore.Andrej Poleev - 2018
  10. Cases, Clusters, Densities: Modeling the Nonlinear Dynamics of Complex Health Trajectories.Brian Castellani, Rajeev Rajaram, Jane Gunn & Frances Griffiths - 2016 - Complexity 21 (S1):160-180.
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  11. Distributional SAdS BH Spacetime-Induced Vacuum Dominance.Jaykov Foukzon - 2016 - Journal of Advances in Mathematics and Computer Science 13 (6):1-54.
    This paper dealing with extension of the Einstein eld equations using apparatus of contemporary generalization of the classical Lorentzian geometry named in literature Colombeau distributional geometry, see for example [1], [2], [3], [4], [5], [6], [7] and [32]. The regularizations of singularities presented in some solutions of the Einstein equations is an important part of this approach. Any singularities present in some solutions of the Einstein equations recognized only in the sense of Colombeau generalized functions [1], [2] and not classically. (...)
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  12. On Stability of Equilibrium Points in Nonlinear Fractional Differential Equations and Fractional Hamiltonian Systems.Fatemeh Keshtkar, Gholamhussian Erjaee & Mahmoud Boutefnouchet - 2016 - Complexity 21 (2):93-99.
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  13. Nonfragile Passivity and Passification of Nonlinear Singular Networked Control Systems with Randomly Occurring Controller Gain Fluctuation.Aichuan Li & Bin Liu - 2016 - Complexity 21 (S1):200-210.
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  14. Design of LMI-Based Global Sliding Mode Controller for Uncertain Nonlinear Systems with Application to Genesio's Chaotic System.Saleh Mobayen - 2016 - Complexity 21 (1):94-98.
    The fault ride-through capability and fault current issues are the main challenges in doubly fed induction generator- based wind turbines. Application of the bridge-type fault current limiter was recognized as a promising solution to cope with these challenges. This paper proposes a nonlinear sliding mode controller for the BFCL to enhance the FRT performance of the DFIG-based WT. This controller has robust performance in unpredicted voltage sag level and nonlinear features. Theoretical discussions, power circuit, and nonlinear control consideration of the (...)
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  15. Fast Terminal Sliding Mode Controller Design for Nonlinear Second-Order Systems with Time-Varying Uncertainties.Saleh Mobayen - 2016 - Complexity 21 (2):239-244.
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  16. Optimal LMI-Based State Feedback Stabilizer for Uncertain Nonlinear Systems with Time-Varying Uncertainties and Disturbances.Saleh Mobayen - 2016 - Complexity 21 (6):356-362.
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  17. Dissipative Sampled-Data Control of Uncertain Nonlinear Systems with Time-Varying Delays.P. Selvaraj, R. Sakthivel, S. Marshal Anthoni, M. Rathika & Mo Yong-Cheol - 2016 - Complexity 21 (6):142-154.
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  18. Nonlinear Models of Electric Charge and Magnetic Moment.I. Bersons & R. Veilande - 2015 - Foundations of Physics 45 (11):1526-1532.
    The models of the electric charge and magnetic moment are presented based on the nonlinear response of a vacuum on the applied electric and magnetic fields. The model of the electric charge contains one parameter—the radius of charge—and predicts one value of the electric charge for all elementary particles independently on the value of this radius. Different values of this parameter for the electron are discussed.
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  19. Chaos.Robert Bishop - 2015 - Stanford Encyclopedia of Philosophy.
    The big news about chaos is supposed to be that the smallest of changes in a system can result in very large differences in that system's behavior. The so-called butterfly effect has become one of the most popular images of chaos. The idea is that the flapping of a butterfly's wings in Argentina could cause a tornado in Texas three weeks later. By contrast, in an identical copy of the world sans the Argentinian butterfly, no such storm would have arisen (...)
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  20. Nonconservative Lagrangian Mechanics: Purely Causal Equations of Motion.David W. Dreisigmeyer & Peter M. Young - 2015 - Foundations of Physics 45 (6):661-672.
    This work builds on the Volterra series formalism presented in Dreisigmeyer and Young to model nonconservative systems. Here we treat Lagrangians and actions as ‘time dependent’ Volterra series. We present a new family of kernels to be used in these Volterra series that allow us to derive a single retarded equation of motion using a variational principle.
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  21. Structural Chaos.Conor Mayo-Wilson - 2015 - Philosophy of Science 82 (5):1236-1247.
    A dynamical system is called chaotic if small changes to its initial conditions can create large changes in its behavior. By analogy, we call a dynamical system structurally chaotic if small changes to the equations describing the evolution of the system produce large changes in its behavior. Although there are many definitions of “chaos,” there are few mathematically precise candidate definitions of “structural chaos.” I propose a definition, and I explain two new theorems that show that a set of models (...)
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  22. Iterative Learning Control for MIMO Nonlinear Systems with Arbitrary Relative Degree and No States Measurement.Farah Bouakrif - 2014 - Complexity 19 (1):37-45.
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  23. Nonlinear Response of Chemical Reaction Dynamics.Alfred Hubler & Andrew Friedl - 2014 - Complexity 19 (1):6-8.
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  24. Lightning in a Bottle: Complexity, Chaos, and Computation in Climate Science.Jon Lawhead - 2014 - Dissertation, Columbia University
    Climatology is a paradigmatic complex systems science. Understanding the global climate involves tackling problems in physics, chemistry, economics, and many other disciplines. I argue that complex systems like the global climate are characterized by certain dynamical features that explain how those systems change over time. A complex system's dynamics are shaped by the interaction of many different components operating at many different temporal and spatial scales. Examining the multidisciplinary and holistic methods of climatology can help us better understand the nature (...)
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  25. Leader‐Following Consensus Problem of Heterogeneous Multi‐Agent Systems with Nonlinear Dynamics Using Fuzzy Disturbance Observer.Tae H. Lee, Ju H. Park, D. H. Ji & H. Y. Jung - 2014 - Complexity 19 (4):20-31.
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  26. On Two Mathematical Definitions of Observational Equivalence: Manifest Isomorphism and Epsilon-Congruence Reconsidered.Christopher Belanger - 2013 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 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 (...)
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  27. Dissipative Many-Body Model and a Nested Operational Architectonics of the Brain.Andrew A. Fingelkurts & Alexander A. Fingelkurts - 2013 - Physics of Life Reviews 10:103-105.
    This paper briefly review a current trend in neuroscience aiming to combine neurophysiological and physical concepts in order to understand the emergence of spatio-temporal patterns within brain activity by which brain constructs knowledge from multiple streams of information. The authors further suggest that the meanings, which subjectively are experienced as thoughts or perceptions can best be described objectively as created and carried by large fields of neural activity within the operational architectonics of brain functioning.
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  28. Sense-Making and Symmetry-Breaking: Merleau-Ponty, Cognitive Science, and Dynamic Systems Theory.Noah Moss Brender - 2013 - Symposium: Canadian Journal of Continental Philosophy/Revue canadienne de philosophie continentale 17 (2):247-273.
    From his earliest work forward, phenomenologist Maurice Merleau-Ponty attempted to develop a new ontology of nature that would avoid the antinomies of realism and idealism by showing that nature has its own intrinsic sense which is prior to reflection. The key to this new ontology was the concept of form, which he appropriated from Gestalt psychology. However, Merleau-Ponty struggled to give a positive characterization of the phenomenon of form which would clarify its ontological status. Evan Thompson has recently taken up (...)
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  29. A Dynamical Model of Risky Choice.Marieke M. J. W. van Rooij, Luis H. Favela, MaryLauren Malone & Michael J. Richardson - 2013 - Proceedings of the 35th Annual Conference of the Cognitive Science Society 35:1510-1515.
    Individuals make decisions under uncertainty every day based on incomplete information concerning the potential outcome of the choice or chance levels. The choices individuals make often deviate from the rational or mathematically objective solution. Accordingly, the dynamics of human decision-making are difficult to capture using conventional, linear mathematical models. Here, we present data from a two-choice task with variable risk between sure loss and risky loss to illustrate how a simple nonlinear dynamical system can be employed to capture the dynamics (...)
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  30. Modeling the Dynamics of Risky Choice.Marieke M. J. W. van Rooij, Luis H. Favela, MaryLauren Malone & Michael J. Richardson - 2013 - Ecological Psychology 25:293-303.
    Individuals make decisions under uncertainty every day. Decisions are based on in- complete information concerning the potential outcome or the predicted likelihood with which events occur. In addition, individuals’ choices often deviate from the rational or mathematically objective solution. Accordingly, the dynamics of human decision making are difficult to capture using conventional, linear mathematical models. Here, we present data from a 2-choice task with variable risk between sure loss and risky loss to illustrate how a simple nonlinear dynamical system can (...)
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  31. Nonlinearity and Metaphysical Emergence.Jessica M. Wilson - 2013 - In Stephen Mumford & Matthew Tugby (eds.), Metaphysics and Science.
    The nonlinearity of a composite system, whereby certain of its features (including powers and behaviors) cannot be seen as linear or other broadly additive combinations of features of the system's composing entities, has been frequently seen as a mark of metaphysical emergence, coupling the dependence of a composite system on an underlying system of composing entities with the composite system's ontological autonomy from its underlying system. But why think that nonlinearity is a mark of emergence, and moreover, of metaphysical rather (...)
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  32. Evaluating Nonlinear Variability of Mental Fatigue Behavioral Indices During Long‐Term Attentive Task.Mahdi Azarnoosh, Ali Motie Nasrabadi, Mohammad Reza Mohammadi & Mohammad Firoozabadi - 2012 - Complexity 17 (6):7-16.
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  33. Heidegger and Cognitive Science.Julian Kiverstein & Michael Wheeler (eds.) - 2012 - Palgrave-Macmillan.
  34. Context-Switching and Responsiveness to Real Relevance.Erik Rietveld - 2012 - In Julian Kiverstein & Michael Wheeler (eds.), Heidegger and Cognitive Science. Palgrave-Macmillan.
  35. Catastrophe Models with Nonlinear Regression.Stephen Guastello - 2011 - In Stephen J. Guastello & R. A. M. Gregson (eds.), Nonlinear Dynamical Systems Analysis for the Behavioral Sciences Using Real Data. Crc Press.
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  36. A Nonlinear Integral Transform and a Global Inverse Bifurcation Theory.Yutaka Kamimura - 2011 - Annali della Scuola Normale Superiore di Pisa- Classe di Scienze 10 (4):863-911.
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  37. Quantum Cooperation.Johann Summhammer - 2011 - Axiomathes 21 (2):347-356.
    In a theoretical simulation the cooperation of two insects is investigated who share a large number of maximally entangled EPR-pairs to correlate their probabilistic actions. Specifically, two distant butterflies must find each other. Each butterfly moves in a chaotic form of short flights, guided only by the weak scent emanating from the other butterfly. The flight directions result from classical random choices. Each such decision of an individual is followed by a read-out of an internal quantum measurement on a spin, (...)
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  38. On Nonlinear Quantum Mechanics, Noncommutative Phase Spaces, Fractal-Scale Calculus and Vacuum Energy.Carlos Castro - 2010 - Foundations of Physics 40 (11):1712-1730.
    A (to our knowledge) novel Generalized Nonlinear Schrödinger equation based on the modifications of Nottale-Cresson’s fractal-scale calculus and resulting from the noncommutativity of the phase space coordinates is explicitly derived. The modifications to the ground state energy of a harmonic oscillator yields the observed value of the vacuum energy density. In the concluding remarks we discuss how nonlinear and nonlocal QM wave equations arise naturally from this fractal-scale calculus formalism which may have a key role in the final formulation of (...)
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  39. Nonlinear Dynamics and Intention According to Aquinas.Walter J. Freeman Iii - 2009 - Mind and Matter 6 (2).
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  40. Computing the Uncomputable; or, The Discrete Charm of Second-Order Simulacra.Matthew W. Parker - 2009 - Synthese 169 (3):447-463.
    We examine a case in which non-computable behavior in a model is revealed by computer simulation. This is possible due to differing notions of computability for sets in a continuous space. The argument originally given for the validity of the simulation involves a simpler simulation of the simulation, still further simulations thereof, and a universality conjecture. There are difficulties with that argument, but there are other, heuristic arguments supporting the qualitative results. It is urged, using this example, that absolute validation, (...)
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  41. Nonlinear Complex Dynamical Systems in Developmental Psychology.P. Van Geert - 2009 - In Stephen J. Guastello, Matthijs Koopmans & David Pincus (eds.), Chaos and Complexity in Psychology: The Theory of Nonlinear Dynamical Systems. Cambridge University Press.
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  42. ‘The Memory of Life Itself’: Bénard’s Cells and the Cinematography of Self-Organization.David Aubin - 2008 - Studies in History and Philosophy of Science Part A 39 (3):359-369.
    In 1900, the physicist Henri Bénard exhibited the spontaneous formation of cells in a layer of liquid heated from below. Six or seven decades later, drastic reinterpretations of this experiment formed an important component of ‘chaos theory’. This paper therefore is an attempt at writing the history of this experiment, its long neglect and its rediscovery. It examines Bénard’s experiments from three different perspectives. First, his results are viewed in the light of the relation between experimental and mathematical approaches in (...)
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  43. Downward Causation in Fluid Convection.Robert C. Bishop - 2008 - Synthese 160 (2):229 - 248.
    Recent developments in nonlinear dynamics have found wide application in many areas of science from physics to neuroscience. Nonlinear phenomena such as feedback loops, inter-level relations, wholes constraining and modifying the behavior of their parts, and memory effects are interesting candidates for emergence and downward causation. Rayleigh–Bénard convection is an example of a nonlinear system that, I suggest, yields important insights for metaphysics and philosophy of science. In this paper I propose convection as a model for downward causation in classical (...)
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  44. What Could Be Worse Than the Butterfly Effect?Robert C. Bishop - 2008 - Canadian Journal of Philosophy 38 (4):519-547.
    The discovery of sensitive dependence on initial conditions (SDIC) in nonlinear models runs counter to the textbook vision of CM, a vision guided by an almost exclusive focus on linear systems. Therefore, it is important to clearly distinguish between linear and nonlinear systems along with establishing some basic terminology (§I). The notions of SDIC and chaos also need clarification, since they play crucial roles in sensitive dependence (SD) arguments. This will require some discussion of Lyapunov exponents as well as the (...)
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  45. The Skillful Body as a Concernful System of Possible Actions: Phenomena and Neurodynamics.Erik Rietveld - 2008 - Theory & Psychology 18 (3):341-361.
    For Merleau-Ponty,consciousness in skillful coping is a matter of prereflective ‘I can’ and not explicit ‘I think that.’ The body unifies many domain-specific capacities. There exists a direct link between the perceived possibilities for action in the situation (‘affordances’) and the organism’s capacities. From Merleau-Ponty’s descriptions it is clear that in a flow of skillful actions, the leading ‘I can’ may change from moment to moment without explicit deliberation. How these transitions occur, however, is less clear. Given that Merleau-Ponty suggested (...)
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  46. Nonlinear Dynamics From Physics to Biology.Peter Schuster - 2007 - Complexity 12 (4):9-11.
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  47. Mathematizing Phenomenology.Jeffrey Yoshimi - 2007 - Phenomenology and the Cognitive Sciences 6 (3):271-291.
    Husserl is well known for his critique of the “mathematizing tendencies” of modern science, and is particularly emphatic that mathematics and phenomenology are distinct and in some sense incompatible. But Husserl himself uses mathematical methods in phenomenology. In the first half of the paper I give a detailed analysis of this tension, showing how those Husserlian doctrines which seem to speak against application of mathematics to phenomenology do not in fact do so. In the second half of the paper I (...)
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  48. Workshop on Specific Aspects of Computational Physics and Wavelet Analysis for Modelling Suddenly-Emerging Phenomena in Nonlinear Physics, and Nonlinear Applied Mathematics (PULSES 2006)-.Vincenzo Ciancio, Francesco Farsaci & Antonino Bartolotta - 2006 - In O. Stock & M. Schaerf (eds.), Lecture Notes in Computer Science. Springer Verlag. pp. 3980--821.
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  49. Physicalism, Chaos and Reductionism.Alwyn Scott - 2006 - In J. Tuszynski (ed.), The Emerging Physics of Consciousness. Springer Verlag. pp. 171--191.
  50. Nonlinear Dynamics at the Cutting Edge of Modernity: A Postmodern View.Gordon G. Globus - 2005 - Philosophy, Psychiatry, and Psychology 12 (3):229-234.
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