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David J. Chalmers (1996). Does a Rock Implement Every Finite-State Automaton?

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  1.  2
    Cognition Wars.Fred Adams - forthcoming - Studies in History and Philosophy of Science Part A.
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  2.  41
    The Perception‐Action Model: Counting Computational Mechanisms.Thor Grünbaum - 2017 - Mind and Language 32 (4):416-445.
    Milner and Goodale's Two Visual Systems Hypothesis is regarded as common ground in recent discussions of visual consciousness. A central part of TVSH is a functional model of vision and action. In this paper, I provide a brief overview of these current discussions and argue that there is ambiguity between a strong and a weak version of PAM. I argue that, given a standard way of individuating computational mechanisms, the available evidence cannot be used to distinguish between these versions. This (...)
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    Extended Music Cognition.Kersten Luke - 2017 - Philosophical Psychology 30 (8):1078-1103.
    Discussions of extended cognition have increasingly engaged with the empirical and methodological practices of cognitive science and psychology. One topic that has received increased attention from those interested in the extended mind is music cognition. A number of authors have argued that music not only shapes emotional and cognitive processes, but also that it extends those processes beyond the bodily envelope. The aim of this paper is to evaluate the case for extended music cognition. Two accounts are examined in detail: (...)
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  4.  38
    Measurement and Computational Skepticism.Robert J. Matthews & Eli Dresner - 2016 - Noûs 50 (1).
    Putnam and Searle famously argue against computational theories of mind on the skeptical ground that there is no fact of the matter as to what mathematical function a physical system is computing: both conclude that virtually any physical object computes every computable function, implements every program or automaton. There has been considerable discussion of Putnam's and Searle's arguments, though as yet there is little consensus as to what, if anything, is wrong with these arguments. In the present paper we show (...)
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  5.  20
    Behavioural Explanation in the Realm of Non-Mental Computing Agents.Bernardo Aguilera - 2015 - Minds and Machines 25 (1):37-56.
    Recently, many philosophers have been inclined to ascribe mentality to animals on the main grounds that they possess certain complex computational abilities. In this paper I contend that this view is misleading, since it wrongly assumes that those computational abilities demand a psychological explanation. On the contrary, they can be just characterised from a computational level of explanation, which picks up a domain of computation and information processing that is common to many computing systems but is autonomous from the domain (...)
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  6.  4
    A Vindication of Program Verification.Selmer Bringsjord - 2015 - History and Philosophy of Logic 36 (3):262-277.
    Fetzer famously claims that program verification is not even a theoretical possibility, and offers a certain argument for this far-reaching claim. Unfortunately for Fetzer, and like-minded thinkers, this position-argument pair, while based on a seminal insight that program verification, despite its Platonic proof-theoretic airs, is plagued by the inevitable unreliability of messy, real-world causation, is demonstrably self-refuting. As I soon show, Fetzer is like the person who claims: ‘My sole claim is that every claim expressed by an English sentence and (...)
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  7.  21
    Objective Computation Versus Subjective Computation.Nir Fresco - 2015 - Erkenntnis 80 (5):1031-1053.
    The question ‘What is computation?’ might seem a trivial one to many, but this is far from being in consensus in philosophy of mind, cognitive science and even in physics. The lack of consensus leads to some interesting, yet contentious, claims, such as that cognition or even the universe is computational. Some have argued, though, that computation is a subjective phenomenon: whether or not a physical system is computational, and if so, which computation it performs, is entirely a matter of (...)
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  8. Sensorama: A Phenomenalist Analysis of Spacetime and Its Contents.Michael Pelczar - 2015 - Oxford University Press.
    How does the modern scientific conception of time constrain the project of assigning the mind its proper place in nature? On the scientific conception, it makes no sense to speak of the duration of a pain, or the simultaneity of sensations occurring in different parts of the brain. Such considerations led Henri Poincaré, one of the founders of the modern conception, to conclude that consciousness does not exist in spacetime, but serves as the basic material out of which we must (...)
     
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  9.  76
    A Theory of Computational Implementation.Michael Rescorla - 2014 - Synthese 191 (6):1277-1307.
    I articulate and defend a new theory of what it is for a physical system to implement an abstract computational model. According to my descriptivist theory, a physical system implements a computational model just in case the model accurately describes the system. Specifically, the system must reliably transit between computational states in accord with mechanical instructions encoded by the model. I contrast my theory with an influential approach to computational implementation espoused by Chalmers, Putnam, and others. I deploy my theory (...)
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  10.  32
    Programming Languages as Technical Artifacts.Raymond Turner - 2014 - Philosophy and Technology 27 (3):377-397.
    Taken at face value, a programming language is defined by a formal grammar. But, clearly, there is more to it. By themselves, the naked strings of the language do not determine when a program is correct relative to some specification. For this, the constructs of the language must be given some semantic content. Moreover, to be employed to generate physical computations, a programming language must have a physical implementation. How are we to conceptualize this complex package? Ontologically, what kind of (...)
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  11. What Is Nature-Like Computation? A Behavioural Approach and a Notion of Programmability.Hector Zenil - 2014 - Philosophy and Technology 27 (3):399-421.
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  12.  52
    Searle's Wall.James Blackmon - 2013 - Erkenntnis 78 (1):109-117.
    In addition to his famous Chinese Room argument, John Searle has posed a more radical problem for views on which minds can be understood as programs. Even his wall, he claims, implements the WordStar program according to the standard definition of implementation because there is some ‘‘pattern of molecule movements’’ that is isomorphic to the formal structure of WordStar. Program implementation, Searle charges, is merely observer-relative and thus not an intrinsic feature of the world. I argue, first, that analogous charges (...)
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  13. Against Structuralist Theories of Computational Implementation.Michael Rescorla - 2013 - British Journal for the Philosophy of Science 64 (4):681-707.
    Under what conditions does a physical system implement or realize a computation? Structuralism about computational implementation, espoused by Chalmers and others, holds that a physical system realizes a computation just in case the system instantiates a pattern of causal organization isomorphic to the computation’s formal structure. I argue against structuralism through counter-examples drawn from computer science. On my opposing view, computational implementation sometimes requires instantiating semantic properties that outstrip any relevant pattern of causal organization. In developing my argument, I defend (...)
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  14.  30
    What Is Nature-Like Computation? A Behavioural Approach and a Notion of Programmability.Hector Zenil - 2013 - Philosophy and Technology (3):1-23.
    The aim of this paper is to propose an alternative behavioural definition of computation (and of a computer) based simply on whether a system is capable of reacting to the environment—the input—as reflected in a measure of programmability. This definition is intended to have relevance beyond the realm of digital computers, particularly vis-à-vis natural systems. This will be done by using an extension of a phase transition coefficient previously defined in an attempt to characterise the dynamical behaviour of cellular automata (...)
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  15. Computational Theories of Conscious Experience: Between a Rock and a Hard Place.Gary Bartlett - 2012 - Erkenntnis 76 (2):195-209.
    Very plausibly, nothing can be a genuine computing system unless it meets an input-sensitivity requirement. Otherwise all sorts of objects, such as rocks or pails of water, can count as performing computations, even such as might suffice for mentality—thus threatening computationalism about the mind with panpsychism. Maudlin in J Philos 86:407–432, ( 1989 ) and Bishop ( 2002a , b ) have argued, however, that such a requirement creates difficulties for computationalism about conscious experience, putting it in conflict with the (...)
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  16.  58
    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 consistent with a (...)
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  17.  64
    Royce's Model of the Absolute.Eric Steinhart - 2012 - Transactions of the Charles S. Peirce Society 48 (3):356-384.
    At the end of the 19th century, Josiah Royce participated in what has come to be called the great debate (Royce, 1897; Armour, 2005).1 The great debate concerned issues in metaphysical theology, and, since metaphysics was primarily idealistic, it dealt considerably with the relations between the divine Self and lesser selves. After the great debate, Royce developed his idealism in his Gifford Lectures (1898-1900). These were published as The World and the Individual. At the end of the first volume, Royce (...)
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  18.  40
    Concrete Digital Computation: What Does It Take for a Physical System to Compute? [REVIEW]Nir Fresco - 2011 - Journal of Logic, Language and Information 20 (4):513-537.
    This paper deals with the question: what are the key requirements for a physical system to perform digital computation? Time and again cognitive scientists are quick to employ the notion of computation simpliciter when asserting basically that cognitive activities are computational. They employ this notion as if there was or is a consensus on just what it takes for a physical system to perform computation, and in particular digital computation. Some cognitive scientists in referring to digital computation simply adhere to (...)
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  19.  75
    Representational Systems.Tomer Fekete - 2010 - Minds and Machines 20 (1):69-101.
    The concept of representation has been a key element in the scientific study of mental processes, ever since such studies commenced. However, usage of the term has been all but too liberal—if one were to adhere to common use it remains unclear if there are examples of physical systems which cannot be construed in terms of representation. The problem is considered afresh, taking as the starting point the notion of activity spaces—spaces of spatiotemporal events produced by dynamical systems. It is (...)
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  20. 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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  21.  35
    Brains as Analog-Model Computers.Oron Shagrir - 2010 - Studies in History and Philosophy of Science Part A 41 (3):271-279.
    Computational neuroscientists not only employ computer models and simulations in studying brain functions. They also view the modeled nervous system itself as computing. What does it mean to say that the brain computes? And what is the utility of the ‘brain-as-computer’ assumption in studying brain functions? In previous work, I have argued that a structural conception of computation is not adequate to address these questions. Here I outline an alternative conception of computation, which I call the analog-model. The term ‘analog-model’ (...)
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  22. Why Computers Can't Feel Pain.John Mark Bishop - 2009 - Minds and Machines 19 (4):507-516.
    The most cursory examination of the history of artificial intelligence highlights numerous egregious claims of its researchers, especially in relation to a populist form of ‘strong’ computationalism which holds that any suitably programmed computer instantiates genuine conscious mental states purely in virtue of carrying out a specific series of computations. The argument presented herein is a simple development of that originally presented in Putnam’s (Representation & Reality, Bradford Books, Cambridge in 1988 ) monograph, “Representation & Reality”, which if correct, has (...)
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  23.  13
    Why Computers Can't Feel Pain.Mark Bishop - 2009 - Minds and Machines 19 (4):507-516.
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  24.  54
    Who's Driving the Syntactic Engine?Emiliano Boccardi - 2009 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 40 (1):23 - 50.
    The property of being the implementation of a computational structure has been argued to be vacuously instantiated. This claim provides the basis for most antirealist arguments in the field of the philosophy of computation. Standard manoeuvres for combating these antirealist arguments treat the problem as endogenous to computational theories. The contrastive analysis of computational and other mathematical representations put forward here reveals that the problem should instead be treated within the more general framework of the Newman problem in structuralist accounts (...)
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    Who’s Driving the Syntactic Engine?Emiliano Boccardi - 2009 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 40 (1):23-50.
    The property of being the implementation of a computational structure has been argued to be vacuously instantiated. This claim provides the basis for most antirealist arguments in the field of the philosophy of computation. Standard manoeuvres for combating these antirealist arguments treat the problem as endogenous to computational theories. The contrastive analysis of computational and other mathematical representations put forward here reveals that the problem should instead be treated within the more general framework of the Newman problem in structuralist accounts (...)
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  26. Triviality Arguments Against Functionalism.Peter Godfrey-Smith - 2009 - Philosophical Studies 145 (2):273 - 295.
    “Triviality arguments” against functionalism in the philosophy of mind hold that the claim that some complex physical system exhibits a given functional organization is either trivial or has much less content than is usually supposed. I survey several earlier arguments of this kind, and present a new one that overcomes some limitations in the earlier arguments. Resisting triviality arguments is possible, but requires functionalists to revise popular views about the “autonomy” of functional description.
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  27. Computationalism in the Philosophy of Mind.Gualtiero Piccinini - 2009 - Philosophy Compass 4 (3):515-532.
    Computationalism has been the mainstream view of cognition for decades. There are periodic reports of its demise, but they are greatly exaggerated. This essay surveys some recent literature on computationalism. It concludes that computationalism is a family of theories about the mechanisms of cognition. The main relevant evidence for testing it comes from neuroscience, though psychology and AI are relevant too. Computationalism comes in many versions, which continue to guide competing research programs in philosophy of mind as well as psychology (...)
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  28.  69
    Russell's Structuralism and the Supposed Death of Computational Cognitive Science.Restrepo Echavarria Ricardo - 2009 - Minds and Machines 19 (2):181-197.
    John Searle believes that computational properties are purely formal and that consequently, computational properties are not intrinsic, empirically discoverable, nor causal; and therefore, that an entity’s having certain computational properties could not be sufficient for its having certain mental properties. To make his case, Searle’s employs an argument that had been used before him by Max Newman, against Russell’s structuralism; one that Russell himself considered fatal to his own position. This paper formulates a not-so-explored version of Searle’s problem with computational (...)
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  29.  76
    A Tale of Two Methods.Eric Winsberg - 2009 - Synthese 169 (3):575 - 592.
    Simulations (both digital and analog) and experiments share many features. But what essential features distinguish them? I discuss two proposals in the literature. On one proposal, experiments investigate nature directly, while simulations merely investigate models. On another proposal, simulations differ from experiments in that simulationists manipulate objects that bear only a formal (rather than material) similarity to the targets of their investigations. Both of these proposals are rejected. I argue that simulations fundamentally differ from experiments with regard to the background (...)
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  30.  1
    Computation, Hypercomputation, and Physical Science.Konstantine Arkoudas - 2008 - Journal of Applied Logic 6 (4):461-475.
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  31.  47
    An Analysis of the Criteria for Evaluating Adequate Theories of Computation.Nir Fresco - 2008 - Minds and Machines 18 (3):379-401.
    This paper deals with the question: What are the criteria that an adequate theory of computation has to meet? 1. Smith's answer: it has to meet the empirical criterion (i.e. doing justice to computational practice), the conceptual criterion (i.e. explaining all the underlying concepts) and the cognitive criterion (i.e. providing solid grounds for computationalism). 2. Piccinini's answer: it has to meet the objectivity criterion (i.e. identifying computation as a matter of fact), the explanation criterion (i.e. explaining the computer's behaviour), the (...)
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  32. Computers.Gualtiero Piccinini - 2008 - Pacific Philosophical Quarterly 89 (1):32–73.
    I offer an explication of the notion of computer, grounded in the practices of computability theorists and computer scientists. I begin by explaining what distinguishes computers from calculators. Then, I offer a systematic taxonomy of kinds of computer, including hard-wired versus programmable, general-purpose versus special-purpose, analog versus digital, and serial versus parallel, giving explicit criteria for each kind. My account is mechanistic: which class a system belongs in, and which functions are computable by which system, depends on the system's mechanistic (...)
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  33. Computation Without Representation.Gualtiero Piccinini - 2008 - Philosophical Studies 137 (2):205-241.
    The received view is that computational states are individuated at least in part by their semantic properties. I offer an alternative, according to which computational states are individuated by their functional properties. Functional properties are specified by a mechanistic explanation without appealing to any semantic properties. The primary purpose of this paper is to formulate the alternative view of computational individuation, point out that it supports a robust notion of computational explanation, and defend it on the grounds of how computational (...)
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  34. Computing Mechanisms.Gualtiero Piccinini - 2007 - Philosophy of Science 74 (4):501-526.
    This paper offers an account of what it is for a physical system to be a computing mechanism—a system that performs computations. A computing mechanism is a mechanism whose function is to generate output strings from input strings and (possibly) internal states, in accordance with a general rule that applies to all relevant strings and depends on the input strings and (possibly) internal states for its application. This account is motivated by reasons endogenous to the philosophy of computing, namely, doing (...)
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  35. Computational Modeling Vs. Computational Explanation: Is Everything a Turing Machine, and Does It Matter to the Philosophy of Mind?Gualtiero Piccinini - 2007 - Australasian Journal of Philosophy 85 (1):93 – 115.
    According to pancomputationalism, everything is a computing system. In this paper, I distinguish between different varieties of pancomputationalism. I find that although some varieties are more plausible than others, only the strongest variety is relevant to the philosophy of mind, but only the most trivial varieties are true. As a side effect of this exercise, I offer a clarified distinction between computational modelling and computational explanation.<br><br>.
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  36. Realization and the Metaphysics of Mind.Thomas W. Polger - 2007 - Australasian Journal of Philosophy 85 (2):233 – 259.
    According to the received view in philosophy of mind, mental states or properties are _realized_ by brain states or properties but are not identical to them. This view is often called _realization_ _physicalism_. Carl Gillett has recently defended a detailed formulation of the realization relation. However, Gillett’s formulation cannot be the relation that realization physicalists have in mind. I argue that Gillett’s “dimensioned” view of realization fails to apply to a textbook case of realization. I also argue Gillett counts as (...)
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  37. Quantity of Experience: Brain-Duplication and Degrees of Consciousness. [REVIEW]Nick Bostrom - 2006 - Minds and Machines 16 (2):185-200.
    If a brain is duplicated so that there are two brains in identical states, are there then two numerically distinct phenomenal experiences or only one? There are two, I argue, and given computationalism, this has implications for what it is to implement a computation. I then consider what happens when a computation is implemented in a system that either uses unreliable components or possesses varying degrees of parallelism. I show that in some of these cases there can be, in a (...)
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  38.  86
    Real Realization: Dennett's Real Patterns Versus Putnam's Ubiquitous Automata. [REVIEW]David Joslin - 2006 - Minds and Machines 16 (1):29-41.
    Both Putnam and Searle have argued that that every abstract automaton is realized by every physical system, a claim that leads to a reductio argument against Cognitivism or Strong AI: if it is possible for a computer to be conscious by virtue of realizing some abstract automaton, then by Putnam’s theorem every physical system also realizes that automaton, and so every physical system is conscious—a conclusion few supporters of Strong AI would be willing to accept. Dennett has suggested a criterion (...)
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  39. 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 explanation and outline some promising answers that (...)
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  40. Why We View the Brain as a Computer.Oron Shagrir - 2006 - Synthese 153 (3):393-416.
    The view that the brain is a sort of computer has functioned as a theoretical guideline both in cognitive science and, more recently, in neuroscience. But since we can view every physical system as a computer, it has been less than clear what this view amounts to. By considering in some detail a seminal study in computational neuroscience, I first suggest that neuroscientists invoke the computational outlook to explain regularities that are formulated in terms of the information content of electrical (...)
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  41.  87
    Open Problems in the Philosophy of Information.Luciano Floridi - 2004 - Metaphilosophy 35 (4):554-582.
    The philosophy of information (PI) is a new area of research with its own field of investigation and methodology. This article, based on the Herbert A. Simon Lecture of Computing and Philosophy I gave at Carnegie Mellon University in 2001, analyses the eighteen principal open problems in PI. Section 1 introduces the analysis by outlining Herbert Simon's approach to PI. Section 2 discusses some methodological considerations about what counts as a good philosophical problem. The discussion centers on Hilbert's famous analysis (...)
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  42. Functionalism, Computationalism, & Mental States.Gualtiero Piccinini - 2004 - Studies in the History and Philosophy of Science 35 (4):811-833.
    Some philosophers have conflated functionalism and computationalism. I reconstruct how this came about and uncover two assumptions that made the conflation possible. They are the assumptions that (i) psychological functional analyses are computational descriptions and (ii) everything may be described as performing computations. I argue that, if we want to improve our understanding of both the metaphysics of mental states and the functional relations between them, we should reject these assumptions.
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  43.  44
    Functionalism, Computationalism, and Mental States.Gualtiero Piccinini - 2004 - Studies in History and Philosophy of Science Part A 35 (4):811-833.
  44. Representationalism Vs. Anti-Representationalism: A Debate for the Sake of Appearance.Pim Haselager, A. de Groot & H. van Rappard - 2003 - Philosophical Psychology 16 (1):5-23.
    In recent years the cognitive science community has witnessed the rise of a new, dynamical approach to cognition. This approach entails a framework in which cognition and behavior are taken to result from complex dynamical interactions between brain, body, and environment. The advent of the dynamical approach is grounded in a dissatisfaction with the classical computational view of cognition. A particularly strong claim has been that cognitive systems do not rely on internal representations and computations. Focusing on this claim, we (...)
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  45.  70
    Counterfactuals Cannot Count: A Rejoinder to David Chalmers.John Mark Bishop - 2002 - Consciousness and Cognition 11 (4):642-652.
    The initial argument presented herein is not significantly original—it is a simple reflection upon a notion of computation originally developed by Putnam and criticised by Chalmers et al. . In what follows, instead of seeking to justify Putnam’s conclusion that every open system implements every Finite State Automaton and hence that psychological states of the brain cannot be functional states of a computer, I will establish the weaker result that, over a finite time window every open system implements the trace (...)
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  46. On Implementing a Computation.David J. Chalmers - 1994 - Minds and Machines 4 (4):391-402.
    To clarify the notion of computation and its role in cognitive science, we need an account of implementation, the nexus between abstract computations and physical systems. I provide such an account, based on the idea that a physical system implements a computation if the causal structure of the system mirrors the formal structure of the computation. The account is developed for the class of combinatorial-state automata, but is sufficiently general to cover all other discrete computational formalisms. The implementation relation is (...)
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