Results for 'Computational theory of mind'

965 found
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  1.  41
    Emotion and the computational theory of mind.Craig DeLancey - 1997 - In S. O'Nuillain, Paul McKevitt & E. MacAogain, Two Sciences of Mind. John Benjamins.
    The case for computationalism about the mind is in doubt when we acknowledge that there are mental phenomena that require, for a proper accounting, that we get below the level of symbol processing. Such phenomena show us that a computational theory of mind cannot be complete. Chief among these phenomena is emotion.
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  2. Easy's gettin' harder all the time: The computational theory and affective states.Jason Megill & Jon Cogburn - 2005 - Ratio 18 (3):306-316.
    We argue that A. Damasio’s (1994) Somatic Marker hypothesis can explain why humans don’t generally suffer from the frame problem, arguably the greatest obstacle facing the Computational Theory of Mind. This involves showing how humans with damaged emotional centers are best understood as actually suffering from the frame problem. We are then able to show that, paradoxically, these results provide evidence for the Computational Theory of Mind, and in addition call into question the very (...)
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  3. Computer Models On Mind: Computational Approaches In Theoretical Psychology.Margaret A. Boden - 1988 - Cambridge University Press.
    What is the mind? How does it work? How does it influence behavior? Some psychologists hope to answer such questions in terms of concepts drawn from computer science and artificial intelligence. They test their theories by modeling mental processes in computers. This book shows how computer models are used to study many psychological phenomena--including vision, language, reasoning, and learning. It also shows that computer modeling involves differing theoretical approaches. Computational psychologists disagree about some basic questions. For instance, should (...)
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  4. Computers and the mind-body problem: On ontological and epistemological dualism.Adam Drozdek - 1993 - Idealistic Studies 23 (1):39-48.
    There seems to exist an indirect link between computer science and theology via psychology, which is founded on dualism. First, these theories from psychology, computer science and theology are considered that acknowledge the existence of (at least) two different kinds of reality, or, possibly, two different realms of the same reality. In order to express a root of incompatibility of science and theology, a distinction is drawn between ontological and epistemological dualism. It seems that computer science combines ontological monism with (...)
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  5. Minds, Machines and Meaning in Philosophy and Technology II. Information Technology and Computers in Theory and Practice.F. Dretske - 1986 - Boston Studies in the Philosophy of Science 90:97-109.
  6. What we can learn from Polanyi about the computational theory of mind?Sheldon Richmond - 2004 - Appraisal 5.
  7. The neurobiological bases for the computational theory of mind.Randy C. Gallistel - 2017 - In Roberto G. De Almeida & Lila R. Gleitman, On Concepts, Modules, and Language: Cognitive Science at its Core. New York, NY: Oup Usa.
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  8. Constructivism, Computability, and Physical Theories.Wayne C. Myrvold - 1994 - Dissertation, Boston University
    This dissertation is an investigation into the degree to which the mathematics used in physical theories can be constructivized. The techniques of recursive function theory and classical logic are used to separate out the algorithmic content of mathematical theories rather than attempting to reformulate them in terms of "intuitionistic" logic. The guiding question is: are there experimentally testable predictions in physics which are not computable from the data? ;The nature of Church's thesis, that the class of effectively calculable functions (...)
     
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  9.  47
    Computers in Abstraction/Representation Theory.Samuel C. Fletcher - 2018 - Minds and Machines 28 (3):445-463.
    Recently, Horsman et al. have proposed a new framework, Abstraction/Representation theory, for understanding and evaluating claims about unconventional or non-standard computation. Among its attractive features, the theory in particular implies a novel account of what is means to be a computer. After expounding on this account, I compare it with other accounts of concrete computation, finding that it does not quite fit in the standard categorization: while it is most similar to some semantic accounts, it is not itself (...)
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  10.  33
    Neural Computations Underlying Phenomenal Consciousness: A Higher Order Syntactic Thought Theory.Edmund T. Rolls - 2020 - Frontiers in Psychology 11:526178.
    Problems are raised with the global workspace hypothesis of consciousness, for example about exactly how global the workspace needs to be for consciousness to suddenly be present. Problems are also raised with Carruthers’s (2019) version that excludes conceptual (categorical or discrete) representations, and in which phenomenal consciousness can be reduced to physical processes, with instead a different levels of explanation approach to the relation between the brain and the mind advocated. A different theory of phenomenal consciousness is described, (...)
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  11.  61
    Flexible features, connectionism, and computational learning theory.Georg Dorffner - 1998 - Behavioral and Brain Sciences 21 (1):24-25.
    This commentary is an elaboration on Schyns, Goldstone & Thibaut's proposal for flexible features in categorization in the light of three areas not explicitly discussed by the authors: connectionist models of categorization, computational learning theory, and constructivist theories of the mind. In general, the authors' proposal is strongly supported, paving the way for model extensions and for interesting novel cognitive research. Nor is the authors' proposal incompatible with theories positing some fixed set of features.
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  12.  53
    Mind the gap: an attempt to bridge computational and neuroscientific approaches to study creativity.Geraint A. Wiggins & Joydeep Bhattacharya - 2014 - Frontiers in Human Neuroscience 8:56498.
    Creativity is the hallmark of human cognition, yet scientific understanding of creative processes is limited. However, there is increasing interest in revealing the neural correlates of human creativity. Though many of these studies, pioneering in nature, help demystification of creativity, but the field is still dominated by popular beliefs in associating creativity with "right brain thinking", "divergent thinking", "altered states" and so on (Dietrich and Kanso, 2010). In this article, we discuss a computational framework for creativity based on Baars' (...)
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  13. Extended mind and the brain-computer interface. A pluralist approach to the human-computer integration.Federico Zilio - 2020 - Rivista Internazionale di Filosofia e Psicologia 11 (2):169-189.
    : This paper uses Extended Mind Theory to explore Brain-Computer Interfaces, demonstrating how this conceptual framework provides a wide-ranging interpretation of the potential integration of user and computer. After a preliminary analysis of first- and second-wave EMT arguments and other pragmatic criteria, I present BCI technology, addressing the issues that arise. Can BCIs extend our mental processes and to what degree? What EMT criteria should be applied to this technology? What is the role of the body in the (...)
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  14. How minds can be computational systems.William J. Rapaport - 1998 - Journal of Experimental and Theoretical Artificial Intelligence 10 (4):403-419.
    The proper treatment of computationalism, as the thesis that cognition is computable, is presented and defended. Some arguments of James H. Fetzer against computationalism are examined and found wanting, and his positive theory of minds as semiotic systems is shown to be consistent with computationalism. An objection is raised to an argument of Selmer Bringsjord against one strand of computationalism, namely, that Turing-Test± passing artifacts are persons, it is argued that, whether or not this objection holds, such artifacts will (...)
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  15.  41
    Computers, Minds and Conduct.Graham Button, Jeff Coulter, John Lee & Wes Sharrock - 1995 - Polity.
    This book provides a sustained and penetrating critique of a wide range of views in modern cognitive science and philosophy of the mind, from Turing's famous test for intelligence in machines to recent work in computational linguistic theory. While discussing many of the key arguments and topics, the authors also develop a distinctive analytic approach. Drawing on the methods of conceptual analysis first elaborated by Wittgenstein and Ryle, the authors seek to show that these methods still have (...)
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  16.  85
    Mind control? Creating illusory intentions through a phony brain–computer interface.Margaret T. Lynn, Christopher C. Berger, Travis A. Riddle & Ezequiel Morsella - 2010 - Consciousness and Cognition 19 (4):1007-1012.
    Can one be fooled into believing that one intended an action that one in fact did not intend? Past experimental paradigms have demonstrated that participants, when provided with false perceptual feedback about their actions, can be fooled into misperceiving the nature of their intended motor act. However, because veridical proprioceptive/perceptual feedback limits the extent to which participants can be fooled, few studies have been able to answer our question and induce the illusion to intend. In a novel paradigm addressing this (...)
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  17. Computation, Implementation, Cognition.Oron Shagrir - 2012 - Minds and Machines 22 (2):137-148.
    Putnam (Representations and reality. MIT Press, Cambridge, 1988) and Searle (The rediscovery of the mind. MIT Press, Cambridge, 1992) famously argue that almost every physical system implements every finite computation. This universal implementation claim, if correct, puts at the risk of triviality certain functional and computational views of the mind. Several authors have offered theories of implementation that allegedly avoid the pitfalls of universal implementation. My aim in this paper is to suggest that these theories are still (...)
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  18.  43
    (1 other version)Mind causality : a computational neuroscience approach.Edmund T. Rolls - forthcoming - Frontiers in Computational Neuroscience.
    A neuroscience-based approach has recently been proposed for the relation between the mind and the brain. The proposal is that events at the sub-neuronal, neuronal, and neuronal network levels take place simultaneously to perform a computation that can be described at a high level as a mental state, with content about the world. It is argued that as the processes at the different levels of explanation take place at the same time, they are linked by a non-causal supervenient relationship: (...)
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  19.  16
    Human-mind-inspired processing model for computing.Chinthanie Weerakoon, Asoka Karunananda & Naomal Dias - 2020 - Mind and Society 19 (2):237-256.
    Among various computing models, it is difficult to find a model inspired from the human mind to improve the computational efficiency of the computer. In fact, the human mind becomes competent in responding for the inputs, resourcefully and mindfully acquiring knowledge and experience over continuous processing with the time. Further, as it is possible to find deeper explanation for the human mind in the Buddhism, the introduction of a computing model imitating the human mind based (...)
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  20. Computational models: a modest role for content.Frances Egan - 2010 - Studies in History and Philosophy of Science Part A 41 (3):253-259.
    The computational theory of mind construes the mind as an information-processor and cognitive capacities as essentially representational capacities. Proponents of the view claim a central role for representational content in computational models of these capacities. In this paper I argue that the standard view of the role of representational content in computational models is mistaken; I argue that representational content is to be understood as a gloss on the computational characterization of a cognitive (...)
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  21. Emotion as a natural kind: Towards a computational foundation for emotion theory.Louis C. Charland - 1995 - Philosophical Psychology 8 (1):59-84.
    In this paper I link two hitherto disconnected sets of results in the philosophy of emotions and explore their implications for the computational theory of mind. The argument of the paper is that, for just the same reasons that some computationalists have thought that cognition may be a natural kind, so the same can plausibly be argued of emotion. The core of the argument is that emotions are a representation-governed phenomenon and that the explanation of how they (...)
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  22.  26
    Deconstructing the Conspiratorial Mind: the Computational Logic Behind Conspiracy Theories.Francesco Rigoli - 2024 - Review of Philosophy and Psychology 15 (2):567-584.
    In the social sciences, research on conspiracy theories is accumulating fast. To contribute to this research, here I introduce a computational model about the psychological processes underlying support for conspiracy theories. The proposal is that endorsement of these theories depends on three factors: prior beliefs, novel evidence, and expected consequences. Thanks to the latter, a conspiracy hypothesis might be selected because it is the costliest to reject even if it is not the best supported by evidence and by prior (...)
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  23.  21
    Structuring Thought: Concepts, Computational Syntax, and Cognitive Explanation.Matthew B. Gifford - 2016 - Dissertation, University of Massachusetts, Amherst
    The topic of this dissertation is what thought must be like in order for the laws and generalizations of psychology to be true. I address a number of contemporary problems in the philosophy of mind concerning the nature and structure of concepts and the ontological status of mental content. Drawing on empirical work in psychology, I develop a number of new conceptual tools for theorizing about concepts, including a counterpart model of concepts' role in linguistic communication, and a deflationary (...)
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  24. Computers Aren’t Syntax All the Way Down or Content All the Way Up.Cem Bozşahin - 2018 - Minds and Machines 28 (3):543-567.
    This paper argues that the idea of a computer is unique. Calculators and analog computers are not different ideas about computers, and nature does not compute by itself. Computers, once clearly defined in all their terms and mechanisms, rather than enumerated by behavioral examples, can be more than instrumental tools in science, and more than source of analogies and taxonomies in philosophy. They can help us understand semantic content and its relation to form. This can be achieved because they have (...)
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  25. Computation vs. information processing: why their difference matters to cognitive science.Gualtiero Piccinini & Andrea Scarantino - 2010 - Studies in History and Philosophy of Science Part A 41 (3):237-246.
    Since the cognitive revolution, it has become commonplace that cognition involves both computation and information processing. Is this one claim or two? Is computation the same as information processing? The two terms are often used interchangeably, but this usage masks important differences. In this paper, we distinguish information processing from computation and examine some of their mutual relations, shedding light on the role each can play in a theory of cognition. We recommend that theorists of cognition be explicit and (...)
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  26. Commonsense Faculty Psychology: Reidian Foundations for Computational Cognitive Science.John-Christian Smith - 1985 - Dissertation, The University of Arizona
    This work locates the historical and conceptual foundations of cognitive science in the "commonsense" psychology of the philosopher Thomas Reid. I begin with Reid's attack on his rationalist and empiricist competitors of the 17th and 18th centuries. I then present his positive theory as a sophisticated faculty psychology appealing to innateness of mental structure. Reidian psychological faculties are equally trustworthy, causally independent mental powers, and I argue that they share nine distinct properties. This distinguishes Reidian 'intentionalism' from idealist 'representationalism,' (...)
     
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  27.  8
    The Mind: From Cartesian Dualism to Piccinini’s Computational Functionalism.Tripathi Rl - 2024 - Philosophy International Journal 7 (3):1-8.
    The concept of the mind in philosophy encompasses a diverse range of theories and perspectives, examining its immaterial nature, unitary function, self-activity, self-consciousness, and persistence despite bodily changes. This paper explores the attributes of the mind, addressing classical materialism, dualism, and behaviorism, along with contemporary theories like functionalism and computational functionalism. Key philosophical debates include the mind-body problem, the subjectivity of mental states, and the epistemological and conceptual challenges in understanding other minds. Contrasting views from Aristotle, (...)
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  28. Cognitive Computation sans Representation.Paul Schweizer - 2017 - In Thomas M. Powers, Philosophy and Computing: Essays in epistemology, philosophy of mind, logic, and ethics. Cham: Springer. pp. 65-84.
    The Computational Theory of Mind (CTM) holds that cognitive processes are essentially computational, and hence computation provides the scientific key to explaining mentality. The Representational Theory of Mind (RTM) holds that representational content is the key feature in distinguishing mental from non-mental systems. I argue that there is a deep incompatibility between these two theoretical frameworks, and that the acceptance of CTM provides strong grounds for rejecting RTM. The focal point of the incompatibility is (...)
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  29. Explaining computation without semantics: Keeping it simple.Nir Fresco - 2010 - Minds and Machines 20 (2):165-181.
    This paper deals with the question: how is computation best individuated? -/- 1. The semantic view of computation: computation is best individuated by its semantic properties. 2. The causal view of computation: computation is best individuated by its causal properties. 3. The functional view of computation: computation is best individuated by its functional properties. -/- Some scientific theories explain the capacities of brains by appealing to computations that they supposedly perform. The reason for that is usually that computation is individuated (...)
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  30. Content, computation and externalism.Oron Shagrir - 2001 - Mind 110 (438):369-400.
    The paper presents an extended argument for the claim that mental content impacts the computational individuation of a cognitive system (section 2). The argument starts with the observation that a cognitive system may simultaneously implement a variety of different syntactic structures, but that the computational identity of a cognitive system is given by only one of these implemented syntactic structures. It is then asked what are the features that determine which of implemented syntactic structures is the computational (...)
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  31.  26
    Mind the gap: bridging the divide between computer scientists and ethicists in shaping moral machines.Pablo Muruzábal Lamberti, Gunter Bombaerts & Wijnand IJsselsteijn - 2025 - Ethics and Information Technology 27 (1):1-11.
    This paper examines the ongoing challenges of interdisciplinary collaboration in Machine Ethics (ME), particularly the integration of ethical decision-making capacities into AI systems. Despite increasing demands for ethical AI, ethicists often remain on the sidelines, contributing primarily to metaethical discussions without directly influencing the development of moral machines. This paper revisits concerns highlighted by Tolmeijer et al. (2020), who identified the pitfall that computer scientists may misinterpret ethical theories without philosophical input. Using the MACHIAVELLI moral benchmark and the Delphi artificial (...)
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  32. Computational explanation in neuroscience.Gualtiero Piccinini - 2006 - Synthese 153 (3):343-353.
    According to some philosophers, computational explanation is proprietary
    to psychology—it does not belong in neuroscience. But neuroscientists routinely offer computational explanations of cognitive phenomena. In fact, computational explanation was initially imported from computability theory into the science of mind by neuroscientists, who justified this move on neurophysiological grounds. Establishing the legitimacy and importance of computational explanation in neuroscience is one thing; shedding light on it is another. I raise some philosophical questions pertaining to computational (...)
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  33. Computers, Persons, and the Chinese Room. Part 1: The Human Computer.Ricardo Restrepo - 2012 - Journal of Mind and Behavior 33 (1):27-48.
    Detractors of Searle’s Chinese Room Argument have arrived at a virtual consensus that the mental properties of the Man performing the computations stipulated by the argument are irrelevant to whether computational cognitive science is true. This paper challenges this virtual consensus to argue for the first of the two main theses of the persons reply, namely, that the mental properties of the Man are what matter. It does this by challenging many of the arguments and conceptions put forth by (...)
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  34.  39
    Is the mind in the brain in contemporary computational neuroscience?Meir Hemmo & Orly Shenker - 2023 - Studies in History and Philosophy of Science Part A 100 (C):64-80.
    According to contemporary computational neuroscience the mental is associated with computations implemented in the brain. We analyze in physical terms based on recent results in the foundations of statistical mechanics two well-known (independent) problems that arise for this approach: the problem of multiple-computations and the problem of multiple-realization. We show that within the computational theory of the mind the two problems are insoluble by the physics of the brain. We further show that attempts to solve the (...)
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  35.  89
    Computational Rationality: Linking Mechanism and Behavior Through Bounded Utility Maximization.Richard L. Lewis, Andrew Howes & Satinder Singh - 2014 - Topics in Cognitive Science 6 (2):279-311.
    We propose a framework for including information‐processing bounds in rational analyses. It is an application of bounded optimality (Russell & Subramanian, 1995) to the challenges of developing theories of mechanism and behavior. The framework is based on the idea that behaviors are generated by cognitive mechanisms that are adapted to the structure of not only the environment but also the mind and brain itself. We call the framework computational rationality to emphasize the incorporation of computational mechanism into (...)
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  36. Tractability and the computational mind.Rineke Verbrugge & Jakub Szymanik - 2018 - In Mark Sprevak & Matteo Colombo, The Routledge Handbook of the Computational Mind. Routledge. pp. 339-353.
    We overview logical and computational explanations of the notion of tractability as applied in cognitive science. We start by introducing the basics of mathematical theories of complexity: computability theory, computational complexity theory, and descriptive complexity theory. Computational philosophy of mind often identifies mental algorithms with computable functions. However, with the development of programming practice it has become apparent that for some computable problems finding effective algorithms is hardly possible. Some problems need too much (...)
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  37. Computers, Dynamical Systems, Phenomena, and the Mind.Marco Giunti - 1992 - Dissertation, Indiana University
    This work addresses a broad range of questions which belong to four fields: computation theory, general philosophy of science, philosophy of cognitive science, and philosophy of mind. Dynamical system theory provides the framework for a unified treatment of these questions. ;The main goal of this dissertation is to propose a new view of the aims and methods of cognitive science--the dynamical approach . According to this view, the object of cognitive science is a particular set of dynamical (...)
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  38. What is computation?B. Jack Copeland - 1996 - Synthese 108 (3):335-59.
    To compute is to execute an algorithm. More precisely, to say that a device or organ computes is to say that there exists a modelling relationship of a certain kind between it and a formal specification of an algorithm and supporting architecture. The key issue is to delimit the phrase of a certain kind. I call this the problem of distinguishing between standard and nonstandard models of computation. The successful drawing of this distinction guards Turing's 1936 analysis of computation against (...)
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  39. Computational Creativity: A Continuing Journey. [REVIEW]Tony Veale, Pablo Gervás & Rafael Pérez Y. Pérez - 2010 - Minds and Machines 20 (4):483-487.
    Computational Creativity: A Continuing Journey Content Type Journal Article DOI 10.1007/s11023-010-9212-0 Authors Tony Veale, Departamento de Ingeniera del Software e Inteligencia Artificial, Universidad Complutense de Madrid, Madrid, Spain Pablo Gervás, Departamento de Ingeniera del Software e Inteligencia Artificial, Universidad Complutense de Madrid, Madrid, Spain Rafael Pérez y Pérez, Departamento de Ingeniera del Software e Inteligencia Artificial, Universidad Complutense de Madrid, Madrid, Spain Journal Minds and Machines Online ISSN 1572-8641 Print ISSN 0924-6495 Journal Volume Volume 20 Journal Issue Volume 20, (...)
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  40.  30
    Computation, Dynamics, and Cognition.Marco Giunti - 1997 - Oxford University Press.
    This book explores the application of dynamical theory to cognitive science. Giunti shows how the dynamical approach can illuminate problems of cognition, information processing, consciousness, meaning, and the relation between body and mind.
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  41.  64
    Useful Theories Make Predictions.Andrew Howes - 2012 - Topics in Cognitive Science 4 (1):84-86.
    Stephen and Van Orden (this issue) propose that there is a complex system approach to cognitive science, and collectively the authors of the papers presented in this issue believe that this approach provides the means to drive a revolution in the science of the mind. Unfortunately, however illuminating, this explanation is absent and hyperbole is all too extensive. In contrast, I argue (1) that dynamic systems theory is not new to cognitive science and does not provide a basis (...)
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  42. Computation, among other things, is beneath us.Selmer Bringsjord - 1994 - Minds and Machines 4 (4):469-88.
    What''s computation? The received answer is that computation is a computer at work, and a computer at work is that which can be modelled as a Turing machine at work. Unfortunately, as John Searle has recently argued, and as others have agreed, the received answer appears to imply that AI and Cog Sci are a royal waste of time. The argument here is alarmingly simple: AI and Cog Sci (of the Strong sort, anyway) are committed to the view that cognition (...)
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  43. Computation is just interpretable symbol manipulation; cognition isn't.Stevan Harnad - 1994 - Minds and Machines 4 (4):379-90.
    Computation is interpretable symbol manipulation. Symbols are objects that are manipulated on the basis of rules operating only on theirshapes, which are arbitrary in relation to what they can be interpreted as meaning. Even if one accepts the Church/Turing Thesis that computation is unique, universal and very near omnipotent, not everything is a computer, because not everything can be given a systematic interpretation; and certainly everything can''t be givenevery systematic interpretation. But even after computers and computation have been successfully distinguished (...)
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  44. Computation and hypercomputation.Mike Stannett - 2003 - Minds and Machines 13 (1):115-153.
    Does Nature permit the implementation of behaviours that cannot be simulated computationally? We consider the meaning of physical computation in some detail, and present arguments in favour of physical hypercomputation: for example, modern scientific method does not allow the specification of any experiment capable of refuting hypercomputation. We consider the implications of relativistic algorithms capable of solving the (Turing) Halting Problem. We also reject as a fallacy the argument that hypercomputation has no relevance because non-computable values are indistinguishable from sufficiently (...)
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  45.  39
    Game arguments in computability theory and algorithmic information theory.Alexander Shen - 2012 - In S. Barry Cooper, How the World Computes. pp. 655--666.
    We provide some examples showing how game-theoretic arguments can be used in computability theory and algorithmic information theory: unique numbering theorem (Friedberg), the gap between conditional complexity and total conditional complexity, Epstein–Levin theorem and some (yet unpublished) result of Muchnik and Vyugin.
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  46. Computational Explanation in Cognitive Sciences: The Mechanist Turn.S. Delarivière & J. Frans - 2015 - Constructivist Foundations 10 (3):426-429.
    Upshot: The computational theory of mind has been elaborated in many different ways throughout the last decades. In Explaining the Computational Mind, Milkowski defends his view that the mind can be explained as computational through his defense of mechanistic explanation. At no point in this book is there explicit mention of constructivist approaches to this topic. We will, nevertheless, argue that it is interesting for constructivist readers.
     
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  47.  57
    Computability Theory.S. Barry Cooper - 2003 - Chapman & Hall.
    Computability theory originated with the seminal work of Gödel, Church, Turing, Kleene and Post in the 1930s. This theory includes a wide spectrum of topics, such as the theory of reducibilities and their degree structures, computably enumerable sets and their automorphisms, and subrecursive hierarchy classifications. Recent work in computability theory has focused on Turing definability and promises to have far-reaching mathematical, scientific, and philosophical consequences. Written by a leading researcher, Computability Theory provides a concise, comprehensive, (...)
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  48.  56
    Astrology, Computers, and the Volksgeist.Denis Dutton - 1995 - Philosophy and Literature 19 (2):424-434.
    In lieu of an abstract, here is a brief excerpt of the content:Astrology, Computers, and the VolksgeistDenis DuttonCarroll Righter is not a name you will recognize, unless, perhaps, you’re old enough and you grew up reading the Los Angeles Times. Righter was the Times’s astrologer, and encountering his name recently brought back a couple of memories from the early 1950s. I remember finding it strange that a man (he was pictured alongside his column) was called Carroll, though he didn’t spell (...)
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  49. (1 other version)Computation and the Brain.Patricia Smith Churchland, Rick Grush, Rob Wilson & Frank Keil - unknown
    Two very different insights motivate characterizing the brain as a computer. One depends on mathematical theory that defines computability in a highly abstract sense. Here the foundational idea is that of a Turing machine. Not an actual machine, the Turing machine is really a conceptual way of making the point that any well-defined function could be executed, step by step, according to simple 'if-you-are-in-state-P-and-have-input-Q-then-do-R' rules, given enough time (maybe infinite time) [see COMPUTATION]. Insofar as the brain is a device (...)
     
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  50.  77
    Computation and the natural world.C. T. A. Schmidt - 2009 - Minds and Machines 19 (4):451-451.
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