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  1. Phenomena and Mechanisms: Putting the Symbolic, Connectionist, and Dynamical Systems Debate in Broader Perspective.Adele A. Abrahamsen & William P. Bechtel - 2006 - In R. Stainton (ed.), Contemporary Debates in Cognitive Science. 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? – a debate initially pitting encapsulated mechanisms against (...)
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  2. Control of Non-Integer-Order Dynamical Systems Using Sliding Mode Scheme.Mohammad Pourmahmood Aghababa - 2016 - Complexity 21 (6):224-233.
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  3. Dynamical Effects in Moiré Fringes.D. L. Allinson - 1968 - Philosophical Magazine 17 (146):339-352.
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  4. Toward Scale‐Free Like Behavior Under Increasing Cognitive Load.Mario Altamura, Brita Elvevåg, Gaetano Campi, Michela De Salvia, Daniele Marasco, Alessandro Ricci & Antonello Bellomo - 2013 - Complexity 18 (1):38-43.
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  5. Circuit Sharing and the Implementation of Intelligent Systems.Michael Anderson - manuscript
    One of the most foundational and continually contested questions in the cognitive sciences is the degree to which the functional organization of the brain can be understood as modular. In its classic formulation, a module was defined as a cognitive sub-system with nine specific properties; the classic module is, among other things, domain specific, encapsulated, and implemented in dedicated neural substrates. Most of the examinations—and especially the criticisms—of the modularity thesis have focused on these properties individually, for instance by finding (...)
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  6. Correlates of Perceptive Instabilities in Event-Related Potentials.Harald Atmanspacher - manuscript
    The study of instabilities in perception has attracted much interest in recent decades. The presented investigations focus on electrophysiological correlates of orientation reversals of both ambiguous visual stimuli and alternating non-ambiguous stimuli, representing the two options of the ambiguous version. Based on a refined experimental setup, significant features in the event-related potentials associated with the perception of orientation reversal were found in both cases. Their occipital location, their early occurence (200–250 ms), and their latency difference (50 ms) offer interesting perspectives (...)
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  7. Biological and Social Constraints on Cognitive Processes: The Need for Dynamical Interactions Between Levels of Inquiry.William Bechtel - 1994 - Canadian Journal of Philosophy 24 (sup1):133-164.
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  8. Representations and Cognitive Explanations: Assessing the Dynamicist Challenge in Cognitive Science.William P. Bechtel - 1998 - 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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  9. Dynamics and Decomposition: Are They Compatible?William P. Bechtel - manuscript
    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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  10. Emergent Models of Supple Dynamics in Life and Mind.Mark A. Bedau - 1997 - 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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  11. Dynamical Approaches to Cognitive Science.Randall D. Beer - 2000 - Trends in Cognitive Sciences 4 (3):91-99.
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  12. Framing the Debate Between Computational and Dynamical Approaches to Cognitive Science.Randall D. Beer - 1998 - 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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  13. Computational and Dynamical Languages for Autonomous Agents.Randall D. Beer - 1995 - In Tim van Gelder & Robert Port (eds.), Mind as Motion: Explorations in the Dynamics of Cognition. MIT Press. pp. 121--147.
  14. Information Processing and Dynamics in Minimally Cognitive Agents.Randall D. Beer & Paul L. Williams - 2015 - Cognitive Science 39 (1):1-38.
    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 to be combined into a (...)
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  15. Behavioral Systems as Autonomous Agents and as Coupled Dynamical Systems: A Criticism.S. Bern & F. A. Keigzer - 1996 - Philosophical Psychology 9 (3):323-46.
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  16. Understanding Neural Complexity: A Role for Reduction. [REVIEW]John Bickle - 2001 - 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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  17. Commentary: Why I Am Not a Dynamicist.Matthew Botvinick - 2012 - Topics in Cognitive Science 4 (1):78-83.
    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 to some stirring rhetorical heights. However, as argued here, (...)
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  18. Why the Dynamical Hypothesis Cannot Qualify as a Law of Qualitative Structure.Nick Braisby, Richard Cooper & Bradley Franks - 1998 - Behavioral and Brain Sciences 21 (5):630-631.
    Van Gelder presents the dynamical hypothesis as a novel law of qualitative structure to compete with Newell and Simon's (1976) physical symbol systems hypothesis. Unlike Newell and Simon's hypothesis, the dynamical hypothesis fails to provide necessary and sufficient conditions for cognition. Furthermore, imprecision in the statement of the dynamical hypothesis renders it unfalsifiable.
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  19. The Dynamical Model is a Perceptron.Bruce Bridgeman - 1998 - Behavioral and Brain Sciences 21 (5):631-632.
    Van Gelder's example of a dynamical model is a Perceptron. The similarity of dynamical models and Perceptrons in turn exemplifies the close relationship between dynamical and algorithmic models. Both are models, not literal descriptions of brains. The brain states of standard modeling are better conceived as processes in the dynamical sense, but algorithmic models remain useful.
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  20. A Note on the Undecidability of the Reachability Problem for o‐Minimal Dynamical Systems.Thomas Brihaye - 2006 - Mathematical Logic Quarterly 52 (2):165-170.
    In this paper we prove that the reachability problem is BSS-undecidable for o-minimal dynamical systems.
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  21. Fracture Surface Energies From Dynamical Cleavage Analysis.S. J. Burns - 1972 - Philosophical Magazine 25 (1):131-138.
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  22. Towards a New Science of the Mind: Wide Content and the Metaphysics of Organizational Properties in Non‐Linear Dynamical Models.W. Christensen C. Hooker - 1998 - Mind and Language 13 (1):98-109.
    Tim van Gelder, following Brandom, Collins and others, uses the so‐called wide content of capacities which support social, norm governed activities, such as language, to argue for their anti‐natural, abstract, but socially instituted nature and thence for the failure of the entire traditional mind‐body discussion as ill‐posed. We argue that his former conclusion is wrong, that such properties are naturalisable, complicated organisational properties of the complexly organised, non‐linearly interactive systems that human beings are. This analysis also provides principled support, but (...)
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  23. Mindscapes: Philosophy, Science, and the Mind.Martin Carrier & Peter Machamer (eds.) - 1997 - University of Pittsburgh Press.
    Leading scholars in the fields of philosophy and the sciences of the mind have contributed to this newest volume in the prestigious Pittsburgh-Konstanz series. Among the problem areas discussed are folk psychology, meanings as conceptual structures, functional and qualitative properties of colors, the role of conscious mental states, representation and mental content, the impact of connectionism on the philosophy of the mind, and supervenience, emergence, and realization. Most of the essays are followed by commentaries that reflect ongoing debates in the (...)
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  24. What is the Dynamical Hypothesis?Nick Chater & Ulrike Hahn - 1998 - Behavioral and Brain Sciences 21 (5):633-634.
    Van Gelder's specification of the dynamical hypothesis does not improve on previous notions. All three key attributes of dynamical systems apply to Turing machines and are hence too general. However, when a more restricted definition of a dynamical system is adopted, it becomes clear that the dynamical hypothesis is too underspecified to constitute an interesting cognitive claim.
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  25. Information for Perception and Information Processing.Anthony Chemero - 2003 - Minds and Machines 13 (4):577-588.
    Do psychologists and computer/cognitive scientists mean the same thing by the term `information'? In this essay, I answer this question by comparing information as understood by Gibsonian, ecological psychologists with information as understood in Barwise and Perry's situation semantics. I argue that, with suitable massaging, these views of information can be brought into line. I end by discussing some issues in (the philosophy of) cognitive science and artificial intelligence.
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  26. Dynamical Explanation and Mental Representations.Anthony Chemero - 2001 - Trends in Cognitive Sciences 5 (4):141-142.
  27. Anti-Representationalism and the Dynamical Stance.Anthony Chemero - 2000 - 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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  28. Dynamical, Ecological Sub-Persons.Anthony Chemero & William Cordeiro - manuscript
    Scientific and Philosophical Studies of Mind Franklin and Marshall College Lancaster, PA 17604-3003 USA .
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  29. Dynamical Explanation and Mental Representations.Tony Chemero - 2001 - 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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  30. What Might Dynamical Intentionality Be, If Not Computation?Ronald L. Chrisley - 1998 - Behavioral and Brain Sciences 21 (5):634-635.
    (1) Van Gelder's concession that the dynamical hypothesis is not in opposition to computation in general does not agree well with his anticomputational stance. (2) There are problems with the claim that dynamic systems allow for nonrepresentational aspects of computation in a way in which digital computation cannot. (3) There are two senses of the “cognition is computation” claim and van Gelder argues against only one of them. (4) Dynamical systems as characterized in the target article share problems of universal (...)
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  31. Commentary on "the Modularity of Dynamic Systems".Andy Clark - manuscript
    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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  32. Proof Only.Andy Clark - manuscript
    Beer’s (2003) paper is a tour de force of detailed comments on the more general notion of “situated- dynamical modeling, and provides a concrete sample ness”, Beer suggests that “on this view, situated action of the kinds of understanding dynamicists may realis- is the fundamental concern and cognition is … one tically hope to achieve. The analysis is thus, as Beer resource among many that can be brought to bear as an states, a “tool for building intuition”, and in this (...)
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  33. Time and Mind.Andy Clark - 1998 - Journal of Philosophy 95 (7):354.
    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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  34. The Dynamical Challenge.Andy Clark - 1997 - Cognitive Science 21 (4):461-481.
    Recent studies such as Thelen and Smith (1994), Kelso (1995), Van Gelder (1995), Beer (1995), and others have presented a forceful case for a dynamical systems approach to understanding cognition and adaptive behavior. These studies call into question some foundational assumptions concerning the nature of cognitive scientific explanation and (in particular) the role of notions such as internal representation and computation. These are exciting and important challenges. But they must be handled with care. It is all to easy in this (...)
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  35. Anthony Chemero: Radical Embodied Cognitive Science. [REVIEW]David Cole - 2010 - Minds and Machines 20 (3):475-479.
  36. Functionality and Autonomy in Open Dynamical Systems.John Collier - unknown
    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 sort of explanation he gave can (...)
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  37. Emergence in Dynamical Systems.John Collier - 2013 - Analiza I Egzystencja 24:17-42.
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  38. A Dynamical Approach to Identity and Diversity in Complex Systems.John Collier - unknown
    The subject of this chapter is the identity of individual dynamical objects and properties. Two problems have dominated the literature: transtemporal identity and the relation between composition and identity. Most traditional approaches to identity rely on some version of classification via essential or typical properties, whether nominal or real. Nominal properties have the disadvantage of producing unnatural classifications, and have several other problems. Real properties, however, are often inaccessible or hard to define (strict definition would make them nominal). I suggest (...)
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  39. Complexly Organised Dynamical Systems.John Collier & Cliff Hooker - 1999 - Open Systems and Information Dynamics 6 (3):241–302.
    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 is their complicated organisation and their consequent capacities for (...)
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  40. Cybernetics.Roberto Cordeschi - 2008 - In L. Floridi (ed.), The Blackwell Guide to the Philosophy of Computing and Information. Blackwell.
    The term cybernetics was first used in 1947 by Norbert Wiener with reference to the centrifugal governor that James Watt had fitted to his steam engine, and above all to Clerk Maxwell, who had subjected governors to a general mathematical treatment in 1868. Wiener used the word “governor” in the sense of the Latin corruption of the Greek term kubernetes, or “steersman.” Wiener defined cybernetics as the study of “control and communication in the animal and the machine” (Wiener 1948). This (...)
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  41. Computationalism Under Attack.Roberto Cordeschi & Marcello Frixione - 2007 - 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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  42. When the “Chaos” is Too Chaotic and the “Limit Cycles” Too Limited, the Mind Boggles and the Brain Flounders.Michael A. Corner & Andre J. Noest - 1987 - Behavioral and Brain Sciences 10 (2):176.
  43. Dynamical Embodiments of Computation in Cognitive Processes.James P. Crutchfield - 1998 - Behavioral and Brain Sciences 21 (5):635-635.
    Dynamics is not enough for cognition, nor it is a substitute for information-processing aspects of brain behavior. Moreover, dynamics and computation are not at odds, but are quite compatible. They can be synthesized so that any dynamical system can be analyzed in terms of its intrinsic computational components.
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  44. Psychological Explanation and Noise in Modeling. Comments on Whit Schonbein's "Cognition and the Power of Continuous Dynamical Systems".Joe Cruz - manuscript
    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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  45. The Concept of Time and Dynamical Implications.Ubiratan D'ambrosio - 1980 - International Logic Review: Rassegna Internazionale di Logica 11:29.
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  46. The Dynamical Hypothesis: The Role of Biological Constraints on Cognition.Keith Davids & Simon Bennett - 1998 - Behavioral and Brain Sciences 21 (5):636-636.
    For the dynamical hypothesis to be defended as a viable alternative to a computational perspective on natural cognition, the role of biological constraints needs to be considered. This task requires a detailed understanding of the structural organization and function of the dynamic nervous system, as well as a theoretical approach that grounds cognitive activity within the constraints of organism and ecological context.
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  47. Revolution, No! Reform, Si!Daniel C. Dennett - 1998 - Behavioral and Brain Sciences 21 (5):636-637.
    Van Gelder's hard line against representations is not supported or supportable, and his soft line in favor of dynamical systems thinking as a supplement to representational models of cognition is good advice, but not revolutionary, as he seems to think.
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  48. A Counterexample T o All Future Dynamic Systems Theories of Cognition.Eric Dietrich - 2000 - 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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  49. Dynamical Description Versus Dynamical Modeling.Eric Dietrich & Arthur B. Markman - 2001 - Trends in Cognitive Sciences 5 (8):332.
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  50. Identities: The Dynamical Dimensions of Diversity.Chuck Dyke & Carl Dyke - 2002 - In Philip Alperson (ed.), Diversity and Community: An Interdisciplinary Reader. Blackwell. pp. 65--87.
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