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  1. 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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  • In defense of the semantic view of computation.Oron Shagrir - 2020 - Synthese 197 (9):4083-4108.
    The semantic view of computation is the claim that semantic properties play an essential role in the individuation of physical computing systems such as laptops and brains. The main argument for the semantic view rests on the fact that some physical systems simultaneously implement different automata at the same time, in the same space, and even in the very same physical properties. Recently, several authors have challenged this argument. They accept the premise of simultaneous implementation but reject the semantic conclusion. (...)
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  • Killing Kripkenstein's Monster.Jared Warren - 2020 - Noûs 54 (2):257-289.
    Here I defend dispositionalism about meaning and rule-following from Kripkenstein's infamous anti-dispositionalist arguments. The problems of finitude, error, and normativity are all addressed. The general lesson I draw is that Kripkenstein's arguments trade on an overly simplistic version of dispositionalism.
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  • 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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  • The Philosophy of Generative Linguistics.Peter Ludlow - 2011 - Oxford, GB: Oxford University Press.
    Peter Ludlow presents the first book on the philosophy of generative linguistics, including both Chomsky's government and binding theory and his minimalist ...
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  • Functionalism.Janet Levin - 2008 - Stanford Encyclopedia of Philosophy.
    Functionalism in the philosophy of mind is the doctrine that what makes something a mental state of a particular type does not depend on its internal constitution, but rather on the way it functions, or the role it plays, in the system of which it is a part. This doctrine is rooted in Aristotle's conception of the soul, and has antecedents in Hobbes's conception of the mind as a “calculating machine”, but it has become fully articulated (and popularly endorsed) only (...)
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  • Computation without representation.Gualtiero Piccinini - 2004 - 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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  • 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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  • Functionalism, integrity, and digital consciousness.Derek Shiller - 2024 - Synthese 203 (2):1-20.
    The prospect of consciousness in artificial systems is closely tied to the viability of functionalism about consciousness. Even if consciousness arises from the abstract functional relationships between the parts of a system, it does not follow that any digital system that implements the right functional organization would be conscious. Functionalism requires constraints on what it takes to properly implement an organization. Existing proposals for constraints on implementation relate to the integrity of the parts and states of the realizers of roles (...)
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  • Multiple realizability and the spirit of functionalism.Rosa Cao - 2022 - Synthese 200 (6):1-31.
    Multiple realizability says that the same kind of mental states may be manifested by systems with very different physical constitutions. Putnam ( 1967 ) supposed it to be “overwhelmingly probable” that there exist psychological properties with different physical realizations in different creatures. But because function constrains possible physical realizers, this empirical bet is far less favorable than it might initially have seemed, especially when we take on board the richer picture of neural and brain function that neuroscience has been uncovering (...)
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  • Computation, individuation, and the received view on representation.Mark Sprevak - 2010 - Studies in History and Philosophy of Science Part A 41 (3):260-270.
    The ‘received view’ about computation is that all computations must involve representational content. Egan and Piccinini argue against the received view. In this paper, I focus on Egan’s arguments, claiming that they fall short of establishing that computations do not involve representational content. I provide positive arguments explaining why computation has to involve representational content, and how that representational content may be of any type. I also argue that there is no need for computational psychology to be individualistic. Finally, I (...)
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  • 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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  • 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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  • The Virtual as the Digital.David J. Chalmers - 2019 - Disputatio 11 (55):453-486.
    I reply to seven commentaries on “The Virtual and the Real”. In response to Claus Beisbart, Jesper Juul, Peter Ludlow, and Neil McDonnell and Nathan Wildman, I clarify and develop my view that virtual are digital objects, with special attention to the nature of digital objects and data structures. In response to Alyssa Ney and Eric Schwitzgebel, I clarify and defend my spatial functionalism, with special attention to the connections between space and consciousness. In response to Marc Silcox, I clarify (...)
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  • Cognition wars.Fred Adams - 2018 - Studies in History and Philosophy of Science Part A 68:20-30.
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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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  • Computation in physical systems.Gualtiero Piccinini - 2010 - Stanford Encyclopedia of Philosophy.
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  • Are There Teleological Functions to Compute?Dimitri Coelho Mollo - 2019 - Philosophy of Science 86 (3):431-452.
    I analyze a tension at the core of the mechanistic view of computation generated by its joint commitment to the medium independence of computational vehicles and to computational systems possessing teleological functions to compute. While computation is individuated in medium-independent terms, teleology is sensitive to the constitutive physical properties of vehicles. This tension spells trouble for the mechanistic view, suggesting that there can be no teleological functions to compute. I argue that, once considerations about the relevant function-bestowing factors for computational (...)
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  • 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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  • A Simplicity Criterion for Physical Computation.Tyler Millhouse - 2019 - British Journal for the Philosophy of Science 70 (1):153-178.
    The aim of this paper is to offer a formal criterion for physical computation that allows us to objectively distinguish between competing computational interpretations of a physical system. The criterion construes a computational interpretation as an ordered pair of functions mapping (1) states of a physical system to states of an abstract machine, and (2) inputs to this machine to interventions in this physical system. This interpretation must ensure that counterfactuals true of the abstract machine have appropriate counterparts which are (...)
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  • 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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  • The indeterminacy of computation.Nir Fresco, B. Jack Copeland & Marty J. Wolf - 2021 - Synthese 199 (5-6):12753-12775.
    Do the dynamics of a physical system determine what function the system computes? Except in special cases, the answer is no: it is often indeterminate what function a given physical system computes. Accordingly, care should be taken when the question ‘What does a particular neuronal system do?’ is answered by hypothesising that the system computes a particular function. The phenomenon of the indeterminacy of computation has important implications for the development of computational explanations of biological systems. Additionally, the phenomenon lends (...)
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  • The physics of implementing logic: Landauer's principle and the multiple-computations theorem.Meir Hemmo & Orly Shenker - 2019 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 68:90-105.
    This paper makes a novel linkage between the multiple-computations theorem in philosophy of mind and Landauer’s principle in physics. The multiple-computations theorem implies that certain physical systems implement simultaneously more than one computation. Landauer’s principle implies that the physical implementation of “logically irreversible” functions is accompanied by minimal entropy increase. We show that the multiple-computations theorem is incompatible with, or at least challenges, the universal validity of Landauer’s principle. To this end we provide accounts of both ideas in terms of (...)
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  • 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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  • Artificial Intelligence Is Stupid and Causal Reasoning Will Not Fix It.J. Mark Bishop - 2021 - Frontiers in Psychology 11:513474.
    Artificial Neural Networks have reached “grandmaster” and even “super-human” performance across a variety of games, from those involving perfect information, such as Go, to those involving imperfect information, such as “Starcraft”. Such technological developments from artificial intelligence (AI) labs have ushered concomitant applications across the world of business, where an “AI” brand-tag is quickly becoming ubiquitous. A corollary of such widespread commercial deployment is that when AI gets things wrong—an autonomous vehicle crashes, a chatbot exhibits “racist” behavior, automated credit-scoring processes (...)
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  • 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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  • A dialogue concerning two world systems: Info-computational vs. mechanistic.Gordana Dodig-Crnkovic & Vincent C. Müller - 2011 - In Gordana Dodig Crnkovic & Mark Burgin (eds.), Information and computation: Essays on scientific and philosophical understanding of foundations of information and computation. World Scientific. pp. 149-184.
    The dialogue develops arguments for and against a broad new world system - info-computationalist naturalism - that is supposed to overcome the traditional mechanistic view. It would make the older mechanistic view into a special case of the new general info-computationalist framework (rather like Euclidian geometry remains valid inside a broader notion of geometry). We primarily discuss what the info-computational paradigm would mean, especially its pancomputationalist component. This includes the requirements for a the new generalized notion of computing that would (...)
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  • When physical systems realize functions.Matthias Scheutz - 1999 - Minds and Machines 9 (2):161-196.
    After briefly discussing the relevance of the notions computation and implementation for cognitive science, I summarize some of the problems that have been found in their most common interpretations. In particular, I argue that standard notions of computation together with a state-to-state correspondence view of implementation cannot overcome difficulties posed by Putnam's Realization Theorem and that, therefore, a different approach to implementation is required. The notion realization of a function, developed out of physical theories, is then introduced as a replacement (...)
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  • (1 other version)Functionalism, computationalism, and mental contents.Gualtiero Piccinini - 2004 - Canadian Journal of Philosophy 34 (3):375-410.
    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. # 2004 Elsevier Ltd. All rights reserved.
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  • (1 other version)Functionalism, Computationalism, & Mental States.Gualtiero Piccinini - 2004 - Studies in 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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  • The chinese room argument.David Cole - 2008 - Stanford Encyclopedia of Philosophy.
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  • Computation in Physical Systems: A Normative Mapping Account.Paul Schweizer - 2019 - In Matteo Vincenzo D'Alfonso & Don Berkich (eds.), On the Cognitive, Ethical, and Scientific Dimensions of Artificial Intelligence. Springer Verlag. pp. 27-47.
    The relationship between abstract formal procedures and the activities of actual physical systems has proved to be surprisingly subtle and controversial, and there are a number of competing accounts of when a physical system can be properly said to implement a mathematical formalism and hence perform a computation. I defend an account wherein computational descriptions of physical systems are high-level normative interpretations motivated by our pragmatic concerns. Furthermore, the criteria of utility and success vary according to our diverse purposes and (...)
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  • The Computational Origin of Representation.Steven T. Piantadosi - 2020 - Minds and Machines 31 (1):1-58.
    Each of our theories of mental representation provides some insight into how the mind works. However, these insights often seem incompatible, as the debates between symbolic, dynamical, emergentist, sub-symbolic, and grounded approaches to cognition attest. Mental representations—whatever they are—must share many features with each of our theories of representation, and yet there are few hypotheses about how a synthesis could be possible. Here, I develop a theory of the underpinnings of symbolic cognition that shows how sub-symbolic dynamics may give rise (...)
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  • 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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  • Sensorama: A Phenomenalist Analysis of Spacetime and Its Contents.Michael Pelczar - 2015 - Oxford, GB: 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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  • Triviality Arguments Reconsidered.Paul Schweizer - 2019 - Minds and Machines 29 (2):287-308.
    Opponents of the computational theory of mind have held that the theory is devoid of explanatory content, since whatever computational procedures are said to account for our cognitive attributes will also be realized by a host of other ‘deviant’ physical systems, such as buckets of water and possibly even stones. Such ‘triviality’ claims rely on a simple mapping account of physical implementation. Hence defenders of CTM traditionally attempt to block the trivialization critique by advocating additional constraints on the implementation relation. (...)
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  • 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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  • 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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  • On Two Different Kinds of Computational Indeterminacy.Philippos Papayannopoulos, Nir Fresco & Oron Shagrir - 2022 - The Monist 105 (2):229-246.
    It is often indeterminate what function a given computational system computes. This phenomenon has been referred to as “computational indeterminacy” or “multiplicity of computations.” In this paper, we argue that what has typically been considered and referred to as the challenge of computational indeterminacy in fact subsumes two distinct phenomena, which are typically bundled together and should be teased apart. One kind of indeterminacy concerns a functional characterization of the system’s relevant behavior. Another kind concerns the manner in which the (...)
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  • Toward Analog Neural Computation.Corey J. Maley - 2018 - Minds and Machines 28 (1):77-91.
    Computationalism about the brain is the view that the brain literally performs computations. For the view to be interesting, we need an account of computation. The most well-developed account of computation is Turing Machine computation, the account provided by theoretical computer science which provides the basis for contemporary digital computers. Some have thought that, given the seemingly-close analogy between the all-or-nothing nature of neural spikes in brains and the binary nature of digital logic, neural computation could be a species of (...)
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  • A Loosely Wittgensteinian Conception of the Linguistic Understanding of Large Language Models like BERT, GPT-3, and ChatGPT.Reto Gubelmann - 2023 - Grazer Philosophische Studien 99 (4):485-523.
    In this article, I develop a loosely Wittgensteinian conception of what it takes for a being, including an AI system, to understand language, and I suggest that current state of the art systems are closer to fulfilling these requirements than one might think. Developing and defending this claim has both empirical and conceptual aspects. The conceptual aspects concern the criteria that are reasonably applied when judging whether some being understands language; the empirical aspects concern the question whether a given being (...)
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  • 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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  • How to be a realist about computational neuroscience.Danielle J. Williams - 2025 - Synthese 205 (3):1-27.
    Recently, a version of realism has been offered to address the simplification strategies used in computational neuroscience. According to this view, computational models provide us with knowledge about the brain, but they should not be taken literally in _any_ sense, even rejecting the idea that the brain performs computations (computationalism). I acknowledge the need for considerations regarding simplification strategies in neuroscience and how they contribute to our interpretations of computational models; however, I argue that whether we should accept or reject (...)
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  • 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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  • The Social Furniture of Virtual Worlds.Peter Ludlow - 2019 - Disputatio 11 (55):345-369.
    David Chalmers argues that virtual objects exist in the form of data structures that have causal powers. I argue that there is a large class of virtual objects that are social objects and that do not depend upon data structures for their existence. I also argue that data structures are themselves fundamentally social objects. Thus, virtual objects are fundamentally social objects.
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  • The multiple-computations theorem and the physics of singling out a computation.Orly Shenker & Meir Hemmo - 2022 - The Monist 105 (1):175-193.
    The problem of multiple-computations discovered by Hilary Putnam presents a deep difficulty for functionalism (of all sorts, computational and causal). We describe in out- line why Putnam’s result, and likewise the more restricted result we call the Multiple- Computations Theorem, are in fact theorems of statistical mechanics. We show why the mere interaction of a computing system with its environment cannot single out a computation as the preferred one amongst the many computations implemented by the system. We explain why nonreductive (...)
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  • Measurement and Computational Skepticism.Robert J. Matthews & Eli Dresner - 2017 - Noûs 51 (4):832-854.
    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 (albeit for somewhat different reasons) 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 (...)
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  • Implementation as Resemblance.André Curtis-Trudel - 2021 - Philosophy of Science 88 (5):1021-1032.
    This article advertises a new account of computational implementation. According to the resemblance account, implementation is a matter of resembling a computational architecture. The resemblance account departs from previous theories by denying that computational architectures are exhausted by their formal, mathematical features. Instead, they are taken to be permeated with causality, spatiotemporality, and other nonmathematical features. I argue that this approach comports well with computer scientific practice and offers a novel response to so-called triviality arguments.
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  • System, Subsystem, Hive: boundary problems in computational theories of consciousness.Tomer Fekete, Cees van Leeuwen & Shimon Edelman - 2016 - Frontiers in Psychology 7:175618.
    A computational theory of consciousness should include a quantitative measure of consciousness, or MoC, that (i) would reveal to what extent a given system is conscious, (ii) would make it possible to compare not only different systems, but also the same system at different times, and (iii) would be graded, because so is consciousness. However, unless its design is properly constrained, such an MoC gives rise to what we call the boundary problem: an MoC that labels a system as conscious (...)
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  • Computational vs. causal complexity.Matthias Scheutz - 2001 - Minds and Machines 11 (4):543-566.
    The main claim of this paper is that notions of implementation based on an isomorphic correspondence between physical and computational states are not tenable. Rather, ``implementation'' has to be based on the notion of ``bisimulation'' in order to be able to block unwanted implementation results and incorporate intuitions from computational practice. A formal definition of implementation is suggested, which satisfies theoretical and practical requirements and may also be used to make the functionalist notion of ``physical realization'' precise. The upshot of (...)
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