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Physical symbol systems

Cognitive Science 4 (2):135-83 (1980)

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  1. Model-based Cognitive Neuroscience: Multifield Mechanistic Integration in Practice.Mark Povich - 2019 - Theory & Psychology 5 (29):640–656.
    Autonomist accounts of cognitive science suggest that cognitive model building and theory construction (can or should) proceed independently of findings in neuroscience. Common functionalist justifications of autonomy rely on there being relatively few constraints between neural structure and cognitive function (e.g., Weiskopf, 2011). In contrast, an integrative mechanistic perspective stresses the mutual constraining of structure and function (e.g., Piccinini & Craver, 2011; Povich, 2015). In this paper, I show how model-based cognitive neuroscience (MBCN) epitomizes the integrative mechanistic perspective and concentrates (...)
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  • The Bit (and Three Other Abstractions) Define the Borderline Between Hardware and Software.Russ Abbott - 2019 - Minds and Machines 29 (2):239-285.
    Modern computing is generally taken to consist primarily of symbol manipulation. But symbols are abstract, and computers are physical. How can a physical device manipulate abstract symbols? Neither Church nor Turing considered this question. My answer is that the bit, as a hardware-implemented abstract data type, serves as a bridge between materiality and abstraction. Computing also relies on three other primitive—but more straightforward—abstractions: Sequentiality, State, and Transition. These physically-implemented abstractions define the borderline between hardware and software and between physicality and (...)
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  • Objections to Computationalism: A Survey.Marcin Miłkowski - 2018 - Roczniki Filozoficzne 66 (3):57-75.
    In this paper, the Author reviewed the typical objections against the claim that brains are computers, or, to be more precise, information-processing mechanisms. By showing that practically all the popular objections are based on uncharitable interpretations of the claim, he argues that the claim is likely to be true, relevant to contemporary cognitive science, and non-trivial.
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  • Philosophy and theory of artificial intelligence 2017.Vincent C. Müller (ed.) - 2017 - Berlin: Springer.
    This book reports on the results of the third edition of the premier conference in the field of philosophy of artificial intelligence, PT-AI 2017, held on November 4 - 5, 2017 at the University of Leeds, UK. It covers: advanced knowledge on key AI concepts, including complexity, computation, creativity, embodiment, representation and superintelligence; cutting-edge ethical issues, such as the AI impact on human dignity and society, responsibilities and rights of machines, as well as AI threats to humanity and AI safety; (...)
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  • From Computer Metaphor to Computational Modeling: The Evolution of Computationalism.Marcin Miłkowski - 2018 - Minds and Machines 28 (3):515-541.
    In this paper, I argue that computationalism is a progressive research tradition. Its metaphysical assumptions are that nervous systems are computational, and that information processing is necessary for cognition to occur. First, the primary reasons why information processing should explain cognition are reviewed. Then I argue that early formulations of these reasons are outdated. However, by relying on the mechanistic account of physical computation, they can be recast in a compelling way. Next, I contrast two computational models of working memory (...)
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  • Why think that the brain is not a computer?Marcin Miłkowski - 2016 - APA Newsletter on Philosophy and Computers 16 (2):22-28.
    In this paper, I review the objections against the claim that brains are computers, or, to be precise, information-processing mechanisms. By showing that practically all the popular objections are either based on uncharitable interpretation of the claim, or simply wrong, I argue that the claim is likely to be true, relevant to contemporary cognitive (neuro)science, and non-trivial.
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  • Cognitivism about Epistemic Modality.David Elohim - manuscript
    This paper aims to vindicate the thesis that cognitive computational properties are abstract objects implemented in physical systems. I avail of the equivalence relations countenanced in Homotopy Type Theory, in order to specify an abstraction principle for epistemic intensions. The homotopic abstraction principle for epistemic intensions provides an epistemic conduit into our knowledge of intensions as abstract objects. I examine, then, how intensional functions in Epistemic Modal Algebra are deployed as core models in the philosophy of mind, Bayesian perceptual psychology, (...)
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  • The Mind as Neural Software? Understanding Functionalism, Computationalism, and Computational Functionalism.Gualtiero Piccinini - 2010 - Philosophy and Phenomenological Research 81 (2):269-311.
    Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goal here is not to evaluate their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism, recruit recent philosophical work on mechanisms and computation to shed light on them, and (...)
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  • (1 other version)Forms of Luminosity: Epistemic Modality and Hyperintensionality in Mathematics.David Elohim - 2017 - Dissertation, Arché, University of St Andrews
    This book concerns the foundations of epistemic modality and hyperintensionality and their applications to the philosophy of mathematics. David Elohim examines the nature of epistemic modality, when the modal operator is interpreted as concerning both apriority and conceivability, as well as states of knowledge and belief. The book demonstrates how epistemic modality and hyperintensionality relate to the computational theory of mind; metaphysical modality and hyperintensionality; the types of mathematical modality and hyperintensionality; to the epistemic status of large cardinal axioms, undecidable (...)
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  • (1 other version)Forms of Luminosity: Epistemic Modality and Hyperintensionality in Mathematics.David Elohim - 2017
    This book concerns the foundations of epistemic modality and hyperintensionality and their applications to the philosophy of mathematics. David Elohim examines the nature of epistemic modality, when the modal operator is interpreted as concerning both apriority and conceivability, as well as states of knowledge and belief. The book demonstrates how epistemic modality and hyperintensionality relate to the computational theory of mind; metaphysical modality and hyperintensionality; the types of mathematical modality and hyperintensionality; to the epistemic status of large cardinal axioms, undecidable (...)
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  • Elme és evolúció.Bence Nanay - 2000 - Kávé..
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  • For a dynamical approach to human computation.Marco Giunti & Simone Pinna - 2016 - Logic Journal of the IGPL 24 (4).
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  • The cognitive neuroscience revolution.Worth Boone & Gualtiero Piccinini - 2016 - Synthese 193 (5):1509-1534.
    We outline a framework of multilevel neurocognitive mechanisms that incorporates representation and computation. We argue that paradigmatic explanations in cognitive neuroscience fit this framework and thus that cognitive neuroscience constitutes a revolutionary break from traditional cognitive science. Whereas traditional cognitive scientific explanations were supposed to be distinct and autonomous from mechanistic explanations, neurocognitive explanations aim to be mechanistic through and through. Neurocognitive explanations aim to integrate computational and representational functions and structures across multiple levels of organization in order to explain (...)
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  • Towards the naturalization of agency based on an interactivist account of autonomy.Argyris Arnellos, Thomas Spyrtou & Ioannis Darzentas - 2010 - New Ideas in Psychology 28 (3):296-311.
    This paper attempts to provide the basis for a broader naturalized account of agency. Naturalization is considered as the need for an ongoing and open-ended process of scientific inquiry driven by the continuous formulation of questions regarding a phenomenon. The naturalization of agency is focused around the interrelation of the fundamental notions of autonomy, functionality, intentionality and meaning. Certain naturalized frameworks of agency are critically considered in an attempt to bring together all the characteristic properties that constitute an autonomous agent, (...)
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  • Introduction: Philosophy and Cognitive Science.Richard Samuels, Eric Margolis & Stephen Stich - 2012 - In Eric Margolis, Richard Samuels & Stephen P. Stich (eds.), The Oxford Handbook of Philosophy of Cognitive Science. Oxford University Press. pp. 3-18.
    This chapter offers a high-level overview of the philosophy of cognitive science and an introduction to the Oxford Handbook of Philosophy of Cognitive Science. The philosophy of cognitive science emerged out of a set of common and overlapping interests among philosophers and scientists who study the mind. We identify five categories of issues that illustrate the best work in this broad field: (1) traditional philosophical issues about the mind that have been invigorated by research in cognitive science, (2) issues regarding (...)
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  • Must cognition be representational?William Ramsey - 2017 - Synthese 194 (11):4197-4214.
    In various contexts and for various reasons, writers often define cognitive processes and architectures as those involving representational states and structures. Similarly, cognitive theories are also often delineated as those that invoke representations. In this paper, I present several reasons for rejecting this way of demarcating the cognitive. Some of the reasons against defining cognition in representational terms are that doing so needlessly restricts our theorizing, it undermines the empirical status of the representational theory of mind, and it encourages wildly (...)
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  • Building Cognition: The Construction of Computational Representations for Scientific Discovery.Sanjay Chandrasekharan & Nancy J. Nersessian - 2015 - Cognitive Science 39 (8):1727-1763.
    Novel computational representations, such as simulation models of complex systems and video games for scientific discovery, are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a theoretical analysis of the cognitive roles such representations play, based on an ethnographic study of the building of computational models in a systems biology laboratory. Specifically, we focus on a case of model-building by an engineer that (...)
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  • Goals, analogy, and the social constraints of scientific discovery.Kevin Dunbar & Lisa M. Baker - 1994 - Behavioral and Brain Sciences 17 (3):538-539.
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  • Subsymbolic computation theory for the human intuitive processor.Paul Smolensky - 2012 - In S. Barry Cooper (ed.), How the World Computes. pp. 675--685.
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  • The embodied emotional mind.Piotr Winkielman, Paula M. Niedenthal & Lindsay Oberman - 2008 - In Gün R. Semin & Eliot R. Smith (eds.), Embodied grounding: social, cognitive, affective, and neuroscientific approaches. New York: Cambridge University Press. pp. 263--288.
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  • Art for art's sake.Alan Garnham - 1994 - Behavioral and Brain Sciences 17 (3):543-544.
    This piece is a commentary on a precis of Maggie Boden's book "The creative mind" published in Behavioral and Brain Sciences.
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  • Is Unified theories of cognition good strategy?Nico H. Frijda & Jan Elshout - 1992 - Behavioral and Brain Sciences 15 (3):445-446.
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  • A cognitive process shell.Steven A. Vere - 1992 - Behavioral and Brain Sciences 15 (3):460-461.
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  • Minds beyond brains and algorithms.Jan M. Zytkow - 1990 - Behavioral and Brain Sciences 13 (4):691-692.
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  • Perceptive questions about computation and cognition.Jon Doyle - 1990 - Behavioral and Brain Sciences 13 (4):661-661.
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  • Time-delays in conscious processes.Benjamin Libet - 1990 - Behavioral and Brain Sciences 13 (4):672-672.
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  • Rationality and irrationality: Still fighting words.Paul Snow - 1991 - Behavioral and Brain Sciences 14 (3):505-506.
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  • Précis of The creative mind: Myths and mechanisms.Margaret A. Boden - 1994 - Behavioral and Brain Sciences 17 (3):519-531.
    What is creativity? One new idea may be creative, whereas another is merely new: What's the difference? And how is creativity possible? These questions about human creativity can be answered, at least in outline, using computational concepts. There are two broad types of creativity, improbabilist and impossibilist. Improbabilist creativity involves novel combinations of familiar ideas. A deeper type involves METCS: the mapping, exploration, and transformation of conceptual spaces. It is impossibilist, in that ideas may be generated which – with respect (...)
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  • Memory: A matter of fitness.Juan D. Delius - 1982 - Behavioral and Brain Sciences 5 (3):375-376.
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  • Cognitive psychology's representation of behaviorism.A. W. Logue - 1982 - Behavioral and Brain Sciences 5 (3):381-382.
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  • Metatheory of animal behavior.Erwin M. Segal - 1982 - Behavioral and Brain Sciences 5 (3):386-387.
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  • Brains + programs = minds.Bruce Bridgeman - 1980 - Behavioral and Brain Sciences 3 (3):427-428.
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  • Intrinsic intentionality.John Searle - 1980 - Behavioral and Brain Sciences 3 (3):450-457.
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  • Computers, cognition and philosophy.Robert Wilensky - 1980 - Behavioral and Brain Sciences 3 (3):449-450.
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  • Information processing abstractions: The message still counts more than the medium.B. Chandrasekaran, Ashok Goel & Dean Allemang - 1988 - Behavioral and Brain Sciences 11 (1):26-27.
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  • Is Smolensky's treatment of connectionism on the level?Carol E. Cleland - 1988 - Behavioral and Brain Sciences 11 (1):27-28.
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  • Behavioral flexibility and the organization of action.David S. Olton - 1981 - Behavioral and Brain Sciences 4 (4):634-635.
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  • Dynamic servomechanisms are more fun: A critical look at chapters 6 and 7 of The organization of action.E. R. Lewis - 1981 - Behavioral and Brain Sciences 4 (4):629-630.
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  • Searle's demon and the brain simulator.Steven F. Savitt - 1982 - Behavioral and Brain Sciences 5 (2):342-343.
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  • Applying Marr to memory.Keith Stenning - 1987 - Behavioral and Brain Sciences 10 (3):494-495.
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  • Representation in semiotics and in computer science.Winfried Nöth - 1997 - Semiotica 115 (3-4):203-214.
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  • A non-representational approach to imagined action.I. van Rooij - 2002 - Cognitive Science 26 (3):345-375.
    This study addresses the dynamical nature of a “representation‐hungry” cognitive task involving an imagined action. In our experiment, participants were handed rods that systematically increased or decreased in length on subsequent trials. Participants were asked to judge whether or not they thought they could reach for a distant object with the hand‐held rod. The results are in agreement with a dynamical model, extended from Tuller, Case, Ding, and Kelso (1994). The dynamical effects observed in this study suggest that predictive judgments (...)
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  • Sign machines in the framework of Semiotics Unbounded.Winfried Nöth - 2008 - Semiotica 2008 (169):319-341.
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  • A non‐representational approach to imagined action.Iris Rooij, Raoul M. Bongers & F. G. Haselager - 2002 - Cognitive Science 26 (3):345-375.
    This study addresses the dynamical nature of a “representation‐hungry” cognitive task involving an imagined action. In our experiment, participants were handed rods that systematically increased or decreased in length on subsequent trials. Participants were asked to judge whether or not they thought they could reach for a distant object with the hand‐held rod. The results are in agreement with a dynamical model, extended from Tuller, Case, Ding, and Kelso (1994). The dynamical effects observed in this study suggest that predictive judgments (...)
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  • Testability of expert systems in system development and application.Elke Steven, Michael Hoenen & Matthias Kloth - 1992 - AI and Society 6 (4):337-344.
    In this paper the difficulties arising out of a necessary examination of expert systems as to the ‘correctness’ of functioning are outlined. The argumentation is based on the problematic use of the knowledge term in expert system development and the design perspectives connected with the cognitivistic knowledge concept. It becomes obvious that fundamental problems in system development will involve negative consequences for utilization. The perspective developed from this analysis is assuming that these problems have to be taken into account in (...)
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  • What the <0.70, 1.17, 0.99, 1.07> is a Symbol?Istvan S. N. Berkeley - 2008 - Minds and Machines 18 (1):93-105.
    The notion of a ‘symbol’ plays an important role in the disciplines of Philosophy, Psychology, Computer Science, and Cognitive Science. However, there is comparatively little agreement on how this notion is to be understood, either between disciplines, or even within particular disciplines. This paper does not attempt to defend some putatively ‘correct’ version of the concept of a ‘symbol.’ Rather, some terminological conventions are suggested, some constraints are proposed and a taxonomy of the kinds of issue that give rise to (...)
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  • The myth of language universals: Language diversity and its importance for cognitive science.Nicholas Evans & Stephen C. Levinson - 2009 - Behavioral and Brain Sciences 32 (5):429-448.
    Talk of linguistic universals has given cognitive scientists the impression that languages are all built to a common pattern. In fact, there are vanishingly few universals of language in the direct sense that all languages exhibit them. Instead, diversity can be found at almost every level of linguistic organization. This fundamentally changes the object of enquiry from a cognitive science perspective. This target article summarizes decades of cross-linguistic work by typologists and descriptive linguists, showing just how few and unprofound the (...)
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  • With diversity in mind: Freeing the language sciences from Universal Grammar.Nicholas Evans & Stephen C. Levinson - 2009 - Behavioral and Brain Sciences 32 (5):472-492.
    Our response takes advantage of the wide-ranging commentary to clarify some aspects of our original proposal and augment others. We argue against the generative critics of our coevolutionary program for the language sciences, defend the use of close-to-surface models as minimizing cross-linguistic data distortion, and stress the growing role of stochastic simulations in making generalized historical accounts testable. These methods lead the search for general principles away from idealized representations and towards selective processes. Putting cultural evolution central in understanding language (...)
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  • Dal Simulazionismo al Paradigma Galileiano.Marco Giunti - 2005 - In Atti del XIX Congresso Nazionale dell'Associazione Italiana di Psicologia, sez. di Psicologia Sperimentale, Cagliari, 18-20 settembre, 2005. (CD-ROM). Associazione Italiana di Psicologia Sperimentale.
    Il lavoro esamina criticamente i presupposti di cinque differenti approcci alla Scienza Cognitiva, (simbolico, connessionista, dinamico, della cognizione incarnata e della vita artificiale) e sostiene che tutti e cinque condividono tacitamente un’ipotesi metodologica molto generale. Tale ipotesi, che propongo di chiamare simulazionismo , postula che i fenomeni cognitivi di un qualunque sistema reale possono essere adeguatamente spiegati sulla base di opportuni modelli di simulazione del sistema stesso. Tuttavia, a causa della loro costituzione, i modelli di simulazione hanno forti limitazioni, sia (...)
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  • A Defense of Cartesian Materialism.Jonathan Opie - 1999 - Philosophy and Phenomenological Research 59 (4):939-963.
    One of the principal tasks Dennett sets himself in Consciousness Explained is to demolish the Cartesian theater model of phenomenal consciousness, which in its contemporary garb takes the form of Cartesian materialism: the idea that conscious experience is a process of presentation realized in the physical materials of the brain. The now standard response to Dennett is that, in focusing on Cartesian materialism, he attacks an impossibly naive account of consciousness held by no one currently working in cognitive science or (...)
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