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  1. Adele A. Abrahamsen & William P. Bechtel (2006). Phenomena and Mechanisms: Putting the Symbolic, Connectionist, and Dynamical Systems Debate in Broader Perspective. In R. Stainton (ed.), Contemporary Debates in Cognitive Science. Basil Blackwell.
    Cognitive science is, more than anything else, a pursuit of cognitive mechanisms. To make headway towards a mechanistic account of any particular cognitive phenomenon, a researcher must choose among the many architectures available to guide and constrain the account. It is thus fitting that this volume on contemporary debates in cognitive science includes two issues of architecture, each articulated in the 1980s but still unresolved:
    • Just how modular is the mind? (section 1) – a debate initially pitting encapsulated (...)
    Our project here is to consider the second issue within the broader context of where cognitive science has been and where it is headed. The notion that cognition in general—not just language processing—involves rules operating on language-like representations actually predates cognitive science. In traditional philosophy of mind, mental life is construed as involving propositional attitudes—that is, such attitudes towards propositions as believing, fearing, and desiring that they be true—and logical inferences from them. On this view, if a person desires that a proposition be true and believes that if she performs a certain action it will become true, she will make the inference and (absent any overriding consideration) perform the action. (shrink)
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  2. William P. Bechtel (1998). Representations and Cognitive Explanations: Assessing the Dynamicist Challenge in Cognitive Science. Cognitive Science 22 (3):295-317.
    Advocates of dynamical systems theory (DST) sometimes employ revolutionary rhetoric. In an attempt to clarify how DST models differ from others in cognitive science, I focus on two issues raised by DST: the role for representations in mental models and the conception of explanation invoked. Two features of representations are their role in standing-in for features external to the system and their format. DST advocates sometimes claim to have repudiated the need for stand-ins in DST models, but I argue that (...)
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  3. William P. Bechtel, Dynamics and Decomposition: Are They Compatible?
    Much of cognitive neuroscience as well as traditional cognitive science is engaged in a quest for mechanisms through a project of decomposition and localization of cognitive functions. Some advocates of the emerging dynamical systems approach to cognition construe it as in opposition to the attempt to decompose and localize functions. I argue that this case is not established and rather explore how dynamical systems tools can be used to analyze and model cognitive functions without abandoning the use of decomposition and (...)
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  4. Mark A. Bedau (1997). Emergent Models of Supple Dynamics in Life and Mind. Brain and Cognition 34:5-27.
    The dynamical patterns in mental phenomena have a characteristic suppleness&emdash;a looseness or softness that persistently resists precise formulation&emdash;which apparently underlies the frame problem of artificial intelligence. This suppleness also undermines contemporary philosophical functionalist attempts to define mental capacities. Living systems display an analogous form of supple dynamics. However, the supple dynamics of living systems have been captured in recent artificial life models, due to the emergent architecture of those models. This suggests that analogous emergent models might be able to explain (...)
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  5. Randall D. Beer (1998). Framing the Debate Between Computational and Dynamical Approaches to Cognitive Science. Behavioral and Brain Sciences 21 (5):630-630.
    van Gelder argues that computational and dynamical systems are mathematically distinct kinds of systems. Although there are real experimental and theoretical differences between adopting a computational or dynamical perspective on cognition, and the dynamical approach has much to recommend it, the debate cannot be framed this rigorously. Instead, what is needed is careful study of concrete models to improve our intuitions.
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  6. John Bickle (2001). Understanding Neural Complexity: A Role for Reduction. [REVIEW] Minds and Machines 11 (4):467-481.
    Psychoneural reduction is under attack again, only this time from a former ally: cognitive neuroscience. It has become popular to think of the brain as a complex system whose theoretically important properties emerge from dynamic, non-linear interactions between its component parts. ``Emergence'' is supposed to replace reduction: the latter is thought to be incapable of explaining the brain qua complex system. Rather than engage this issue at the level of theories of reduction versus theories of emergence, I here emphasize a (...)
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  7. Noah Moss Brender (2013). Sense-Making and Symmetry-Breaking. Symposium 17 (2):246-270.
    From his earliest work forward, 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 endogenous 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 Merleau-Ponty’s ontology (...)
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  8. Martin Carrier & Peter K. Machamer (eds.) (1997). Mindscapes: Philosophy, Science, and the Mind. Pittsburgh University Press.
  9. Anthony Chemero (2000). Anti-Representationalism and the Dynamical Stance. Philosophy of Science 67 (4):625-647.
    Arguments in favor of anti-representationalism in cognitive science often suffer from a lack of attention to detail. The purpose of this paper is to fill in the gaps in these arguments, and in so doing show that at least one form of anti- representationalism is potentially viable. After giving a teleological definition of representation and applying it to a few models that have inspired anti- representationalist claims, I argue that anti-representationalism must be divided into two distinct theses, one ontological, one (...)
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  10. Anthony Chemero & William Cordeiro, Dynamical, Ecological Sub-Persons.
    Scientific and Philosophical Studies of Mind Franklin and Marshall College Lancaster, PA 17604-3003 USA .
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  11. Tony Chemero (2001). Dynamical Explanation and Mental Representations. Trends in Cognitive Sciences 5 (4):141-142.
    Markman and Dietrich1 recently recommended extending our understanding of representation to incorporate insights from some “alternative” theories of cognition: perceptual symbol systems, situated action, embodied cognition, and dynamical systems. In particular, they suggest that allowances be made for new types of representation which had been previously under-emphasized in cognitive science. The amendments they recommend are based upon the assumption that the alternative positions each agree with the classical view that cognition requires representations, internal mediating states that bear information.2 In the (...)
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  12. Andy Clark, Commentary on "the Modularity of Dynamic Systems".
    1. Throughout the paper, and especially in the section called "LISP vs. DST", I worried that there was not enough focus on EXPLANATION. For the real question, it seems to me, is not whether some dynamical system can implement human cognition, but whether the dynamical description of the system is more explanatorily potent than a computational/representational one. Thus we know, for example, that a purely physical specification can fix a system capable of computing any LISP function. But from this it (...)
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  13. Andy Clark (1998). Time and Mind. Journal of Philosophy 95 (7):354-76.
    Mind, it has recently been argued1, is a thoroughly temporal phenomenon: so temporal, indeed, as to defy description and analysis using the traditional computational tools of cognitive scientific understanding. The proper explanatory tools, so the suggestion goes, are instead the geometric constructs and differential equations of Dynamical Systems Theory. I consider various aspects of the putative temporal challenge to computational understanding, and show that the root problem turns on the presence of a certain kind of causal web: a web that (...)
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  14. David Cole (2010). Anthony Chemero: Radical Embodied Cognitive Science. [REVIEW] Minds and Machines 20 (3):475-479.
  15. Roberto Cordeschi & Marcello Frixione (2007). Computationalism Under Attack. In M. Marraffa, M. De Caro & F. Ferretti (eds.), Cartographies of the Mind: Philosophy and Psychology in Intersection. Springer.
    Since the early eighties, computationalism in the study of the mind has been “under attack” by several critics of the so-called “classic” or “symbolic” approaches in AI and cognitive science. Computationalism was generically identified with such approaches. For example, it was identified with both Allen Newell and Herbert Simon’s Physical Symbol System Hypothesis and Jerry Fodor’s theory of Language of Thought, usually without taking into account the fact ,that such approaches are very different as to their methods and aims. Zenon (...)
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  16. Joe Cruz, Psychological Explanation and Noise in Modeling. Comments on Whit Schonbein's "Cognition and the Power of Continuous Dynamical Systems".
    I find myself ambivalent with respect to the line of argument that Schonbein offers. I certainly want to acknowledge and emphasize at the outset that Schonbein’s discussion has brought to the fore a number of central, compelling and intriguing issues regarding the nature of the dynamical approach to cognition. Though there is much that seems right in this essay, perhaps my view is that the paper invites more questions than it answers. My remarks here then are in the spirit of (...)
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  17. Eric Dietrich (2000). A Counterexample T o All Future Dynamic Systems Theories of Cognition. J. Of Experimental and Theoretical AI 12 (2):377-382.
    Years ago, when I was an undergraduate math major at the University of Wyoming, I came across an interesting book in our library. It was a book of counterexamples t o propositions in real analysis (the mathematics of the real numbers). Mathematicians work more or less like the rest of us. They consider propositions. If one seems to them to be plausibly true, then they set about to prove it, to establish the proposition as a theorem. Instead o f setting (...)
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  18. J. Richard Eiser (1994). Attitudes, Chaos, and the Connectionist Mind. Cambridge: Blackwell.
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  19. Chris Eliasmith (2003). Moving Beyond Metaphors: Understanding the Mind for What It Is. Journal of Philosophy 100 (10):493-520.
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  20. Chris Eliasmith (2001). Attractive and in-Discrete: A Critique of Two Putative Virtues of the Dynamicist Theory of Mind. Minds and Machines 11 (3):417-426.
    I argue that dynamicism does not provide a convincing alternative to currently available cognitive theories. First, I show that the attractor dynamics of dynamicist models are inadequate for accounting for high-level cognition. Second, I argue that dynamicist arguments for the rejection of computation and representation are unsound in light of recent empirical findings. This new evidence provides a basis for questioning the importance of continuity to cognitive function, challenging a central commitment of dynamicism. Coupled with a defense of current connectionist (...)
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  21. Chris Eliasmith (1998). Dynamical Models and Van Gelder's Dynamicism. Behavioral and Brain Sciences 21 (5):639-639.
    Van Gelder has presented a position which he ties closely to a broad class of models known as dynamical models. While supporting many of his broader claims about the importance of this class (as has been argued by connectionists for quite some time), I note that there are a number of unique characteristics of his brand of dynamicism. I suggest that these characteristics engender difficulties for his view.
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  22. Chris Eliasmith (1997). Computation and Dynamical Models of Mind. Minds and Machines 7 (4):531-41.
    Van Gelder (1995) has recently spearheaded a movement to challenge the dominance of connectionist and classicist models in cognitive science. The dynamical conception of cognition is van Gelder's replacement for the computation bound paradigms provided by connectionism and classicism. He relies on the Watt governor to fulfill the role of a dynamicist Turing machine and claims that the Motivational Oscillatory Theory (MOT) provides a sound empirical basis for dynamicism. In other words, the Watt governor is to be the theoretical exemplar (...)
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  23. Chris Eliasmith (1996). The Third Contender: A Critical Examination of the Dynamicist Theory of Cognition. Philosophical Psychology 9 (4):441-63.
    In a recent series of publications, dynamicist researchers have proposed a new conception of cognitive functioning. This conception is intended to replace the currently dominant theories of connectionism and symbolicism. The dynamicist approach to cognitive modeling employs concepts developed in the mathematical field of dynamical systems theory. They claim that cognitive models should be embedded, low-dimensional, complex, described by coupled differential equations, and non-representational. In this paper I begin with a short description of the dynamicist project and its role as (...)
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  24. Andrew A. Fingelkurts, Alexander A. Fingelkurts & Carlos F. H. Neves (2009). Brain and Mind Operational Architectonics and Man-Made “Machine” Consciousness. Cognitive Processing 10 (2):105-111.
    To build a true conscious robot requires that a robot’s “brain” be capable of supporting the phenomenal consciousness as human’s brain enjoys. Operational Architectonics framework through exploration of the temporal structure of information flow and inter-area interactions within the network of functional neuronal populations [by examining topographic sharp transition processes in the scalp electroencephalogram (EEG) on the millisecond scale] reveals and describes the EEG architecture which is analogous to the architecture of the phenomenal world. This suggests that the task of (...)
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  25. Jeffrey E. Foss (1992). Introduction to the Epistemology of the Brain: Indeterminacy, Micro-Specificity, Chaos, and Openness. Topoi 11 (1):45-57.
    Given that the mind is the brain, as materialists insist, those who would understand the mind must understand the brain. Assuming that arrays of neural firing frequencies are highly salient aspects of brain information processing (the vector functional account), four hurdles to an understanding of the brain are identified and inspected: indeterminacy, micro-specificity, chaos, and openness.
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  26. Walter J. Freeman (1997). Nonlinear Neurodynamics of Intentionality. Journal of Mind and Behavior 18 (2-3):291-304.
  27. Robert M. French & Elizabeth Thomas (2001). The Dynamical Hypothesis in Cognitive Science: A Review Essay of Mind As Motion. [REVIEW] Minds and Machines 11 (1):101-111.
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  28. Robert M. French & Elizabeth Thomas (1998). The Dynamical Hypothesis: One Battle Behind. Behavioral and Brain Sciences 21 (5):640-641.
    What new implications does the dynamical hypothesis have for cognitive science? The short answer is: None. The _Behavior and Brain Sciences _target article, “The dynamical hypothesis in cognitive science” by Tim Van Gelder is basically an attack on traditional symbolic AI and differs very little from prior connectionist criticisms of it. For the past ten years, the connectionist community has been well aware of the necessity of using (and understanding) dynamically evolving, recurrent network models of cognition.
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  29. James W. Garson (1998). Chaotic Emergence and the Language of Thought. Philosophical Psychology 11 (3):303-315.
    The purpose of this paper is to explore the merits of the idea that dynamical systems theory (also known as chaos theory) provides a model of the mind that can vindicate the language of thought (LOT). I investigate the nature of emergent structure in dynamical systems to assess its compatibility with causally efficacious syntactic structure in the brain. I will argue that anyone who is committed to the idea that the brain's functioning depends on emergent features of dynamical systems should (...)
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  30. James W. Garson (1997). Syntax in a Dynamic Brain. Synthese 110 (3):343-55.
    Proponents of the language of thought (LOT) thesis are realists when it comes to syntactically structured representations, and must defend their view against instrumentalists, who would claim that syntactic structures may be useful in describing cognition, but have no more causal powers in governing cognition than do the equations of physics in guiding the planets. This paper explores what it will take to provide an argument for LOT that can defend its conclusion from instrumentalism. I illustrate a difficulty in this (...)
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  31. James W. Garson (1996). Cognition Poised at the Edge of Chaos: A Complex Alternative to a Symbolic Mind. Philosophical Psychology 9 (3):301-22.
    This paper explores a line of argument against the classical paradigm in cognitive science that is based upon properties of non-linear dynamical systems, especially in their chaotic and near-chaotic behavior. Systems of this kind are capable of generating information-rich macro behavior that could be useful to cognition. I argue that a brain operating at the edge of chaos could generate high-complexity cognition in this way. If this hypothesis is correct, then the symbolic processing methodology in cognitive science faces serious obstacles. (...)
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  32. T. van Gelder & Robert Port (eds.) (1995). Mind As Motion. MIT Press.
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  33. Marco Giunti (1996). Computers, Dynamical Systems, and the Mind. Oxford University Press.
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  34. Marco Giunti (1995). Dynamic Models of Cognition. In T. Van Gelder & Robert Port (eds.), Mind As Motion. MIT Press.
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  35. Gordon G. Globus (1992). Toward a Noncomputational Cognitive Science. Journal of Cognitive Neuroscience 4:299-310.
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  36. Mitchell R. Haney (1999). Dynamical Cognition, Soft Laws, and Moral Theorizing. Acta Analytica 22 (22):227-240.
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  37. E. Rae Harcum (1991). Behavioral Paradigm for a Psychological Resolution of the Free Will Issue. Journal of Mind and Behavior 93:93-114.
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  38. Cliff A. Hooker & Wayne D. Christensen (1998). Towards a New Science of the Mind: Wide Content and the Metaphysics of Organizational Properties in Nonlinear Dynamic Models. Mind and Language 13 (1):98-109.
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  39. Christopher Hookway & Donald M. Peterson (eds.) (1993). Philosophy and Cognitive Science. Cambridge University Press.
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  40. Terence E. Horgan & John L. Tienson (1994). A Nonclassical Framework for Cognitive Science. Synthese 101 (3):305-45.
    David Marr provided a useful framework for theorizing about cognition within classical, AI-style cognitive science, in terms of three levels of description: the levels of (i) cognitive function, (ii) algorithm and (iii) physical implementation. We generalize this framework: (i) cognitive state transitions, (ii) mathematical/functional design and (iii) physical implementation or realization. Specifying the middle, design level to be the theory of dynamical systems yields a nonclassical, alternative framework that suits (but is not committed to) connectionism. We consider how a brain's (...)
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  41. Terence E. Horgan & John L. Tienson (1992). Cognitive Systems as Dynamic Systems. Topoi 11 (1):27-43.
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  42. 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.
    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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  43. Robert M. French & Elizabeth Thomas (2001). The Dynamical Hypothesis in Cognitive Science: A Review Essay of Mind As Motion. [REVIEW] Minds and Machines 11 (1):101-111.
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  44. Jacques Mallah (forthcoming). Structure and Dynamics in Implementation of Computations. In Yasemin J. Erden (ed.), Proceedings of the 7th AISB Symposium on Computing and Philosophy:. AISB.
    Without a proper restriction on mappings, virtually any system could be seen as implementing any computation. That would not allow characterization of systems in terms of implemented computations and is not compatible with a computationalist philosophy of mind. Information-based criteria for independence of substates within structured states are proposed as a solution. Objections to the use of requirements for transitions in counterfactual states are addressed, in part using the partial-brain argument as a general counterargument to neural replacement arguments.
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  45. Drew Mcdermott (2011). A Little Static for the Dynamicists Review of Shanahan. International Journal of Machine Consciousness 3 (02):361-365.
  46. Stephen L. Mills (1999). Noncomputable Dynamical Cognitivism: An Eliminativist Perspective. Acta Analytica 22 (22):151-168.
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  47. Adam Morton (1988). The Chaology of Mind. Analysis 48 (June):135-142.
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  48. Noah Moss Brender (2013). Sense-Making and Symmetry-Breaking: Merleau-Ponty, Cognitive Science, and Dynamic Systems Theory. Symposium 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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  49. Gerard O.’Brien (1998). Digital Computers Versus Dynamical Systems: A Conflation of Distinctions. Behavioral and Brain Sciences 21 (5):648-649.
    The distinction at the heart of van Gelder’s target article is one between digital computers and dynamical systems. But this distinction conflates two more fundamental distinctions in cognitive science that should be keep apart. When this conflation is undone, it becomes apparent that the “computational hypothesis” (CH) is not as dominant in contemporary cognitive science as van Gelder contends; nor has the “dynamical hypothesis” (DH) been neglected.
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  50. Erich Rast (2013). Review of Fenstad's "Grammar, Geometry & Brain&Quot;. [REVIEW] Studia Logica 101 (5).
    In this small book logician and mathematician Jens Erik Fenstad addresses some of the most important foundational questions of linguistics: What should a theory of meaning look like and how might we provide the missing link between meaning theory and our knowledge of how the brain works? The author’s answer is twofold. On the one hand, he suggests that logical semantics in the Montague tradition and other broadly conceived symbolic approaches do not suffice. On the other hand, he does not (...)
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