Search results for 'dynamical systems theory' (try it on Scholar)

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  1. Tjeerd Van De Laar (2006). Dynamical Systems Theory as an Approach to Mental Causation. Journal for General Philosophy of Science 37 (2):307-332.score: 540.0
    Dynamical systems theory (DST) is gaining popularity in cognitive science and philosophy of mind. Recently several authors (e.g. J.A.S. Kelso, 1995; A. Juarrero, 1999; F. Varela and E. Thompson, 2001) offered a DST approach to mental causation as an alternative for models of mental causation in the line of Jaegwon Kim (e.g. 1998). They claim that some dynamical systems exhibit a form of global to local determination or downward causation in that the large-scale, global activity (...)
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  2. Marco Van Leeuwen (2005). Questions for the Dynamicist: The Use of Dynamical Systems Theory in the Philosophy of Cognition. [REVIEW] Minds and Machines 15 (3-4):271-333.score: 474.0
    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 (...)
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  3. Scott Hotton & Jeff Yoshimi (2011). Extending Dynamical Systems Theory to Model Embodied Cognition. Cognitive Science 35 (3):444-479.score: 444.0
    We define a mathematical formalism based on the concept of an ‘‘open dynamical system” and show how it can be used to model embodied cognition. This formalism extends classical dynamical systems theory by distinguishing a ‘‘total system’’ (which models an agent in an environment) and an ‘‘agent system’’ (which models an agent by itself), and it includes tools for analyzing the collections of overlapping paths that occur in an embedded agent's state space. To illustrate the way (...)
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  4. Lois A. Gelfand & Sally Engelhart (2012). Dynamical Systems Theory in Psychology: Assistance for the Lay Reader is Required. Frontiers in Psychology 3.score: 444.0
    Dynamical Systems Theory in Psychology: Assistance for the Lay Reader is Required.
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  5. Sally Engelhart Lois A. Gelfand (2012). Dynamical Systems Theory in Psychology: Assistance for the Lay Reader is Required. Frontiers in Psychology 3.score: 444.0
    Dynamical Systems Theory in Psychology: Assistance for the Lay Reader is Required.
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  6. Whitney Tabor, Pyeong W. Cho & Harry Dankowicz (2013). Birth of an Abstraction: A Dynamical Systems Account of the Discovery of an Elsewhere Principle in a Category Learning Task. Cognitive Science 37 (7):1193-1227.score: 396.0
    Human participants and recurrent (“connectionist”) neural networks were both trained on a categorization system abstractly similar to natural language systems involving irregular (“strong”) classes and a default class. Both the humans and the networks exhibited staged learning and a generalization pattern reminiscent of the Elsewhere Condition (Kiparsky, 1973). Previous connectionist accounts of related phenomena have often been vague about the nature of the networks’ encoding systems. We analyzed our network using dynamical systems theory, revealing topological (...)
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  7. Jeff Yoshimi (2012). Supervenience, Dynamical Systems Theory, and Non-Reductive Physicalism. British Journal for the Philosophy of Science 63 (2):373-398.score: 360.0
    It is often claimed (1) that levels of nature are related by supervenience, and (2) that processes occurring at particular levels of nature should be studied using dynamical systems theory. However, there has been little consideration of how these claims are related. To address the issue, I show how supervenience relations give rise to ‘supervenience functions’, and use these functions to show how dynamical systems at different levels are related to one another. I then use (...)
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  8. 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):411 - 434.score: 360.0
    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 (...)
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  9. Ralph D. Ellis (2005). Generating Predictions From a Dynamical Systems Emotion Theory. Behavioral and Brain Sciences 28 (2):202-203.score: 348.0
    Lewis's dynamical systems emotion theory continues a tradition including Merleau-Ponty, von Bertallanfy, and Aristotle. Understandably for a young theory, Lewis's new predictions do not follow strictly from the theory; thus their failure would not disconfirm the theory, nor their success confirm it – especially given that other self-organizational approaches to emotion (e.g., those of Ellis and of Newton) may not be inconsistent with these same predictions.
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  10. Carmel M. Martin (2010). Complexity in Dynamical Health Systems – Transforming Science and Theory, and Knowledge and Practice. Journal of Evaluation in Clinical Practice 16 (1):209-210.score: 345.0
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  11. Harald Atmanspacher (2006). Complementarity in Classical Dynamical Systems. Foundations of Physics 36 (2):291-306.score: 342.0
    The concept of complementarity, originally defined for non-commuting observables of quantum systems with states of non-vanishing dispersion, is extended to classical dynamical systems with a partitioned phase space. Interpreting partitions in terms of ensembles of epistemic states (symbols) with corresponding classical observables, it is shown that such observables are complementary to each other with respect to particular partitions unless those partitions are generating. This explains why symbolic descriptions based on an ad hoc partition of an underlying phase (...)
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  12. Stephen J. Guastello, Matthijs Koopmans & David Pincus (eds.) (2009). Chaos and Complexity in Psychology: The Theory of Nonlinear Dynamical Systems. Cambridge University Press.score: 337.0
  13. Esther Thelen, Gregor Schöner, Christian Scheier & Linda B. Smith (2001). The Dynamics of Embodiment: A Field Theory of Infant Perseverative Reaching. Behavioral and Brain Sciences 24 (1):1-34.score: 324.0
    The overall goal of this target article is to demonstrate a mechanism for an embodied cognition. The particular vehicle is a much-studied, but still widely debated phenomenon seen in 7–12 month-old-infants. In Piaget's classic “A-not-B error,” infants who have successfully uncovered a toy at location “A” continue to reach to that location even after they watch the toy hidden in a nearby location “B.” Here, we question the traditional explanations of the error as an indicator of infants' concepts of objects (...)
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  14. Evelyn Fox Keller (2005). DDS: Dynamics of Developmental Systems. [REVIEW] Biology and Philosophy 20 (2-3):409-416.score: 324.0
    The acronym Developmental systems theory (DST) has been introduced into the literature on development in at least three different contexts in recent years – twice for DST, and before that, for Dynamical Systems Theory – and in all cases, to designate a new perspective for understanding development. Subtle but significant differences in argument and aims distinguish these uses, and confound the difficulty of saying just what DST is. My aim in this paper is to disambiguate (...)
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  15. Noah Moss Brender (2013). Sense-Making and Symmetry-Breaking: Merleau-Ponty, Cognitive Science, and Dynamic Systems Theory. Symposium 17 (2):247-273.score: 316.0
    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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  16. A. Carati & L. Galgani (2001). Theory of Dynamical Systems and the Relations Between Classical and Quantum Mechanics. Foundations of Physics 31 (1):69-87.score: 297.0
    We give a review of some works where it is shown that certain quantum-like features are exhibited by classical systems. Two kinds of problems are considered. The first one concerns the specific heat of crystals (the so called Fermi–Pasta–Ulam problem), where a glassy behavior is observed, and the energy distribution is found to be of Planck-like type. The second kind of problems concerns the self-interaction of a charged particle with the electromagnetic field, where an analog of the tunnel effect (...)
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  17. 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.score: 292.0
    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 (...)
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  18. David Morris (1999). The Fold and the Body Schema in Merleau-Ponty and Dynamic Systems Theory. Chiasmi International 1:275-286.score: 292.0
    Contemporary thought, whether it be in psychology, biology, immunology, philosophy of perception or philosophy of mind, is confronted with the breakdown of barriers between organism and environment, self and other, subject and object, perceiver and perceived. In this paper I show how Merleau-Ponty can help us think about this problem, by attending to a methodological theme in the background of his dialectical conception of embodiment. In La structure du comportement, Merleau-Ponty conceives life as extension folding back upon itself so as (...)
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  19. Teed Rockwell (2005). Attractor Spaces as Modules: A Semi-Eliminative Reduction of Symbolic AI to Dynamic Systems Theory. [REVIEW] Minds and Machines 15 (1):23-55.score: 290.0
    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 (...)
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  20. 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.score: 290.0
    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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  21. Yvon Gauthier (2009). The Construction of Chaos Theory. Foundations of Science 14 (3):153-165.score: 288.0
    This paper aims at a logico-mathematical analysis of the concept of chaos from the point of view of a constructivist philosophy of physics. The idea of an internal logic of chaos theory is meant as an alternative to a realist conception of chaos. A brief historical overview of the theory of dynamical systems is provided in order to situate the philosophical problem in the context of probability theory. A finitary probabilistic account of chaos amounts to (...)
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  22. Randall D. Beer & Paul L. Williams (2014). Information Processing and Dynamics in Minimally Cognitive Agents. Cognitive Science 38 (5).score: 279.0
    There has been considerable debate in the literature about the relative merits of information processing versus dynamical approaches to understanding cognitive processes. In this article, we explore the relationship between these two styles of explanation using a model agent evolved to solve a relational categorization task. Specifically, we separately analyze the operation of this agent using the mathematical tools of information theory and dynamical systems theory. Information-theoretic analysis reveals how task-relevant information flows through the system (...)
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  23. Francisco Franchetti & William H. Sandholm (2013). An Introduction to Dynamo: Diagrams for Evolutionary Game Dynamics. [REVIEW] Biological Theory 8 (2):167-178.score: 279.0
    Dynamo: Diagrams for Evolutionary Game Dynamics is free, open-source software used to create phase diagrams and other images related to dynamical systems from evolutionary game theory. We describe how to use the software’s default settings to generate phase diagrams quickly and easily. We then explain how to take advantage of the software’s intermediate and advanced features to create diagrams that highlight the key properties of the dynamical system under study. Sample code and output are provided to (...)
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  24. Jeffrey Yoshimi (2007). Mathematizing Phenomenology. Phenomenology and the Cognitive Sciences 6 (3):271-291.score: 270.0
    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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  25. Mark W. Brown (2008). The Place of Description in Phenomenology's Naturalization. Phenomenology and the Cognitive Sciences 7 (4):563-583.score: 270.0
    The recent move to naturalize phenomenology through a mathematical protocol is a significant advance in consciousness research. It enables a new and fruitful level of dialogue between the cognitive sciences and phenomenology of such a nuanced kind that it also prompts advancement in our phenomenological analyses. But precisely what is going on at this point of ‘dialogue’ between phenomenological descriptions and mathematical algorithms, the latter of which are based on dynamical systems theory? It will be shown that (...)
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  26. Tom Froese & Thomas Fuchs (2012). The Extended Body: A Case Study in the Neurophenomenology of Social Interaction. [REVIEW] Phenomenology and the Cognitive Sciences 11 (2):205-235.score: 270.0
    There is a growing realization in cognitive science that a theory of embodied intersubjectivity is needed to better account for social cognition. We highlight some challenges that must be addressed by attempts to interpret ‘simulation theory’ in terms of embodiment, and argue for an alternative approach that integrates phenomenology and dynamical systems theory in a mutually informing manner. Instead of ‘simulation’ we put forward the concept of the ‘extended body’, an enactive and phenomenological notion that (...)
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  27. Matthew Botvinick (2012). Commentary: Why I Am Not a Dynamicist. Topics in Cognitive Science 4 (1):78-83.score: 270.0
    The dynamical systems approach in cognitive science offers a potentially useful perspective on both brain and behavior. Indeed, the importation of formal tools from dynamical systems research has already paid off for our field in many ways. However, like some other theoretical perspectives in cognitive science, the dynamical systems approach comes in both moderate or pragmatic and “fundamentalist” varieties (Jones & Love, 2011). In the latter form, dynamical systems theory can rise (...)
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  28. William Bechtel (2012). Understanding Endogenously Active Mechanisms: A Scientific and Philosophical Challenge. [REVIEW] European Journal for Philosophy of Science 2 (2):233-248.score: 270.0
    Abstract Although noting the importance of organization in mechanisms, the new mechanistic philosophers of science have followed most biologists in focusing primarily on only the simplest mode of organization in which operations are envisaged as occurring sequentially. Increasingly, though, biologists are recognizing that the mechanisms they confront are non-sequential and the operations nonlinear. To understand how such mechanisms function through time, they are turning to computational models and tools of dynamical systems theory. Recent research on circadian rhythms (...)
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  29. Gary Goldberg (1992). Dynamical Systems Theory and the Mobility Gradient: Information, Homology and Self-Similar Structure. Behavioral and Brain Sciences 15 (2):278-279.score: 270.0
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  30. Pak Kin Ho & Alcibiades Malapi-Nelson (2011). Dynamical Systems Theory, Understanding, and Explanation: Comments on Malapi-Nelson's Paper with Responses From the Author. Gnosis 6 (1).score: 270.0
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  31. Alcibiades Malapi-Nelson (2011). Dynamical Systems Theory in Cognition: Are We Really Gaining? Gnosis 6 (1).score: 270.0
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  32. Charles Tresser (1995). Aspects of Renormalization in Dynamical Systems Theory. In R. J. Russell, N. Murphy & A. R. Peacocke (eds.), Chaos and Complexity. Vatican Observatory Publications. 11--19.score: 270.0
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  33. R. Brown, J. F. Glazebrook & I. C. Baianu (2007). A Conceptual Construction of Complexity Levels Theory in Spacetime Categorical Ontology: Non-Abelian Algebraic Topology, Many-Valued Logics and Dynamic Systems. [REVIEW] Axiomathes 17 (3-4):409-493.score: 264.0
    A novel conceptual framework is introduced for the Complexity Levels Theory in a Categorical Ontology of Space and Time. This conceptual and formal construction is intended for ontological studies of Emergent Biosystems, Super-complex Dynamics, Evolution and Human Consciousness. A claim is defended concerning the universal representation of an item’s essence in categorical terms. As an essential example, relational structures of living organisms are well represented by applying the important categorical concept of natural transformations to biomolecular reactions and relational structures (...)
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  34. Greg Hjorth (2001). Foreman Matthew. A Descriptive View of Ergodic Theory. Descriptive Set Theory and Dynamical Systems, Edited by Foreman M., Kechris AS, Louveau A., and Weiss B., London Mathematical Society Lecture Note Series, No. 277, Cambridge University Press, Cambridge, New York, Etc., 2000, Pp. 87–171. [REVIEW] Bulletin of Symbolic Logic 7 (4):545-546.score: 261.0
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  35. Anita Feferman, Solomon Feferman, Robert Goldblatt, Yuri Gurevich, Klaus Grue, Sven Ove Hansson, Lauri Hella, Robert K. Meyer & Petri Mäenpää (1997). Stål Anderaa (Oslo), A Traktenbrot Inseparability Theorem for Groups. Peter Dybjer (G Öteborg), Normalization by Yoneda Embedding (Joint Work with D. Cubric and PJ Scott). Abbas Edalat (Imperial College), Dynamical Systems, Measures, Fractals, and Exact Real Number Arithmetic Via Domain Theory. [REVIEW] Bulletin of Symbolic Logic 3 (4).score: 261.0
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  36. Alexander Gimelfarb & Steven Orzack (1989). Mathematical Unity The Theory of Evolution and Dynamical Systems Josef Hofbauer Karl Sigmund. Bioscience 39 (11):820-821.score: 261.0
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  37. Sumiyoshi Abe (2014). Fokker–Planck Theory of Nonequilibrium Systems Governed by Hierarchical Dynamics. Foundations of Physics 44 (2):175-182.score: 252.0
    Dynamics of complex systems is often hierarchically organized on different time scales. To understand the physics of such hierarchy, here Brownian motion of a particle moving through a fluctuating medium with slowly varying temperature is studied as an analytically tractable example, and a kinetic theory is formulated for describing the states of the particle. What is peculiar here is that the (inverse) temperature is treated as a dynamical variable. Dynamical hierarchy is introduced in conformity with the (...)
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  38. W. Schonbein (2005). Cognition and the Power of Continuous Dynamical Systems. Minds and Machines 15 (1):57-71.score: 240.0
    Traditional approaches to modeling cognitive systems are computational, based on utilizing the standard tools and concepts of the theory of computation. More recently, a number of philosophers have argued that cognition is too subtle or complex for these tools to handle. These philosophers propose an alternative based on dynamical systems theory. Proponents of this view characterize dynamical systems as (i) utilizing continuous rather than discrete mathematics, and, as a result, (ii) being computationally more (...)
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  39. Noboru Watanabe (2011). Note on Entropies of Quantum Dynamical Systems. Foundations of Physics 41 (3):549-563.score: 234.0
    We review some techniques and notions for quantum information theory. It is shown that the dynamical entropies is discussed and some numerical computations of these entropies are carried for several states.
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  40. Lawrence A. Shapiro (2013). Dynamics and Cognition. Minds and Machines 23 (3):353-375.score: 231.0
    Many who advocate dynamical systems approaches to cognitive science believe themselves committed to the thesis of extended cognition and to the rejection of representation. I argue that this belief is false. In part, this misapprehension rests on a warrantless re-conception of cognition as intelligent behavior. In part also, it rests on thinking that conceptual issues can be resolved empirically. Once these issues are sorted out, the way is cleared for a dynamical systems approach to cognition that (...)
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  41. John T. Sanders, Dynamical Systems and Scientific Method.score: 219.0
    Progress in the last few decades in what is widely known as “Chaos Theory” has plainly advanced understanding in the several sciences it has been applied to. But the manner in which such progress has been achieved raises important questions about scientific method and, indeed, about the very objectives and character of science. In this presentation, I hope to engage my audience in a discussion of several of these important new topics.
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  42. Vadim Batitsky & Zoltan Domotor (2007). When Good Theories Make Bad Predictions. Synthese 157 (1):79 - 103.score: 219.0
    Chaos-related obstructions to predictability have been used to challenge accounts of theory validation based on the agreement between theoretical predictions and experimental data (Rueger & Sharp, 1996. The British Journal for the Philosophy of Science, 47, 93–112; Koperski, 1998. Philosophy of Science, 40, 194–212). These challenges are incomplete in two respects: (a) they do not show that chaotic regimes are unpredictable in principle (i.e., with unbounded resources) and, as a result, that there is something conceptually wrong with idealized expectations (...)
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  43. Marc D. Lewis (2005). Bridging Emotion Theory and Neurobiology Through Dynamic Systems Modeling. Behavioral and Brain Sciences 28 (2):169-194.score: 216.0
    Efforts to bridge emotion theory with neurobiology can be facilitated by dynamic systems (DS) modeling. DS principles stipulate higher-order wholes emerging from lower-order constituents through bidirectional causal processes cognition relations. I then present a psychological model based on this reconceptualization, identifying trigger, self-amplification, and self-stabilization phases of emotion-appraisal states, leading to consolidating traits. The article goes on to describe neural structures and functions involved in appraisal and emotion, as well as DS mechanisms of integration by which they interact. (...)
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  44. Fred A. Keijzer & Sacha Bem (1996). Behavioral Systems Interpreted as Autonomous Agents and as Coupled Dynamical Systems: A Criticism. Philosophical Psychology 9 (3):323-46.score: 216.0
    Cognitive science's basic premises are under attack. In particular, its focus on internal cognitive processes is a target. Intelligence is increasingly interpreted, not as a matter of reclusive thought, but as successful agent-environment interaction. The critics claim that a major reorientation of the field is necessary. However, this will only occur when there is a distinct alternative conceptual framework to replace the old one. Whether or not a serious alternative is provided is not clear. Among the critics there is some (...)
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  45. Herbert Jaeger (1998). Today's Dynamical Systems Are Too Simple. Behavioral and Brain Sciences 21 (5):643-644.score: 216.0
    Cognitive systems are wilder than today's dynamical systems theory can handle. Cognitive systems might be tamed in principle, but the very notion of a dynamical system will change in the process.
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  46. David Spurrett (2002). Information Processing and Dynamical Systems Approaches Are Complementary. Behavioral and Brain Sciences 25 (5):639-640.score: 216.0
    Shanker & King (S&K) trumpet the adoption of a “new paradigm” in communication studies, exemplified by ape language research. Though cautiously sympathetic, I maintain that their argument relies on a false dichotomy between “information” and “dynamical systemstheory, and that the resulting confusion prevents them from recognizing the main chance their line of thinking suggests.
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  47. John Collier, Functionality and Autonomy in Open Dynamical Systems.score: 216.0
    In Robert West’s talk last week, dynamical systems theory (DST) was applied to a specific problem involving interacting symbolic systems, without much reference to how those systems are embodied or related to other types of systems. Despite this level of abstraction, DST can yield interesting results, though one might be left wondering if it really leads to understanding, or what it all means. In particular, Robert noted problems he has in convincing referees that the (...)
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  48. Wolfgang Tschacher Sergio Salvatore (2012). Time Dependency of Psychotherapeutic Exchanges: The Contribution of the Theory of Dynamic Systems in Analyzing Process. Frontiers in Psychology 3.score: 216.0
    This paper provides a general framework for the use of TDS in the field of psychotherapy research. Psychotherapy is inherently dynamic, namely a function of time. Consequently, the improvement of construct validity and clinical relevance of psychotherapy process research require the development of models of investigation allowing dynamic mappings of clinical exchange. Thus, the Theory of Dynamic Systems (TDS) becomes a significant theoretical and methodological reference. The paper focuses two topics. First, the main concepts of TDS are briefly (...)
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  49. Douglas T. Kenrick, Norman Li & Jonathan E. Butner (2000). Dynamical Systems and Mating Decision Rules. Behavioral and Brain Sciences 23 (4):607-608.score: 216.0
    Dynamical simulations of male and female mating strategies illustrate how traits such as restrictedness constrain, and are constrained by, local ecology. Such traits cannot be defined solely by genotype or by phenotype, but are better considered as decision rules gauged to ecological inputs. Gangestad & Simpson's work draws attention to the need for additional bridges between evolutionary psychology and dynamical systems theory.
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  50. John Collier, Complexly Organised Dynamical Systems.score: 213.0
    Both natural and engineered systems are fundamentally dynamical in nature: their defining properties are causal, and their functional capacities are causally grounded. Among dynamical systems, an interesting and important sub-class are those that are autonomous, anticipative and adaptive (AAA). Living systems, intelligent systems, sophisticated robots and social systems belong to this class, and the use of these terms has recently spread rapidly through the scientific literature. Central to understanding these dynamical systems (...)
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