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  1. Function-Theoretic Explanation and the Search for Neural Mechanisms.Frances Egan - 2017 - In David Michael Kaplan (ed.), Explanation and Integration in Mind and Brain Science. Oxford, United Kingdom: Oxford University Press. pp. 145-163.
    A common kind of explanation in cognitive neuroscience might be called functiontheoretic: with some target cognitive capacity in view, the theorist hypothesizes that the system computes a well-defined function (in the mathematical sense) and explains how computing this function constitutes (in the system’s normal environment) the exercise of the cognitive capacity. Recently, proponents of the so-called ‘new mechanist’ approach in philosophy of science have argued that a model of a cognitive capacity is explanatory only to the extent that it reveals (...)
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  • How Is Perception Tractable?Tyler Brooke-Wilson - forthcoming - The Philosophical Review.
    Perception solves computationally demanding problems at lightning fast speed. It recovers sophisticated representations of the world from degraded inputs, often in a matter of milliseconds. Any theory of perception must be able to explain how this is possible; in other words, it must be able to explain perception's computational tractability. One of the few attempts to move toward such an explanation has been the information encapsulation hypothesis, which posits that perception can be fast because it keeps computational costs low by (...)
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  • Rethinking Turing’s Test and the Philosophical Implications.Diane Proudfoot - 2020 - Minds and Machines 30 (4):487-512.
    In the 70 years since Alan Turing’s ‘Computing Machinery and Intelligence’ appeared in Mind, there have been two widely-accepted interpretations of the Turing test: the canonical behaviourist interpretation and the rival inductive or epistemic interpretation. These readings are based on Turing’s Mind paper; few seem aware that Turing described two other versions of the imitation game. I have argued that both readings are inconsistent with Turing’s 1948 and 1952 statements about intelligence, and fail to explain the design of his game. (...)
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  • Psychoneural Isomorphism: From Metaphysics to Robustness.Alfredo Vernazzani - 2020 - In Marco Viola & Fabrizio Calzavarini (eds.), Neural Mechanisms: New Challenges in the Philosophy of Neuroscience. Springer.
    At the beginning of the 20th century, Gestalt psychologists put forward the concept of psychoneural isomorphism, which was meant to replace Fechner’s obscure notion of psychophysical parallelism and provide a heuristics that may facilitate the search for the neural correlates of the mind. However, the concept has generated much confusion in the debate, and today its role is still unclear. In this contribution, I will attempt a little conceptual spadework in clarifying the concept of psychoneural isomorphism, focusing exclusively on conscious (...)
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  • Discussion on the Relationship between Computation, Information, Cognition, and Their Embodiment.Gordana Dodig-Crnkovic & Marcin Miłkowski - 2023 - Entropy 25 (2):310.
    Three special issues of Entropy journal have been dedicated to the topics of “InformationProcessing and Embodied, Embedded, Enactive Cognition”. They addressed morphological computing, cognitive agency, and the evolution of cognition. The contributions show the diversity of views present in the research community on the topic of computation and its relation to cognition. This paper is an attempt to elucidate current debates on computation that are central to cognitive science. It is written in the form of a dialog between two authors (...)
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  • How to Explain Miscomputation.Chris Tucker - 2018 - Philosophers' Imprint 18:1-17.
    Just as theory of representation is deficient if it can’t explain how misrepresentation is possible, a theory of computation is deficient if it can’t explain how miscomputation is possible. Nonetheless, philosophers have generally ignored miscomputation. My primary goal in this paper is to clarify both what miscomputation is and how to adequately explain it. Miscomputation is a special kind of malfunction: a system miscomputes when it computes in a way that it shouldn’t. To explain miscomputation, you must provide accounts of (...)
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  • Matriks jako metafizyka.Chalmers David - 2015 - Roczniki Filozoficzne 63 (4):187-229.
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  • Why Do We Need a Theory of Implementation?André Curtis-Trudel - 2022 - British Journal for the Philosophy of Science 73 (4):1067-1091.
    The received view of computation is methodologically bifurcated: it offers different accounts of computation in the mathematical and physical cases. But little in the way of argument has been given for this approach. This article rectifies the situation by arguing that the alternative, a unified account, is untenable. Furthermore, once these issues are brought into sharper relief we can see that work remains to be done to illuminate the relationship between physical and mathematical computation.
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  • Gualtiero Piccinini: Physical Computation: A Mechanistic Account: Oxford University Press, Oxford, 2015, ix + 313, £35.00, ISBN 9780199658855.Matteo Colombo - 2016 - Minds and Machines 26 (3):307-312.
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  • Editors’ Review and Introduction: Levels of Explanation in Cognitive Science: From Molecules to Culture.Matteo Colombo & Markus Knauff - 2020 - Topics in Cognitive Science 12 (4):1224-1240.
    Cognitive science began as a multidisciplinary endeavor to understand how the mind works. Since the beginning, cognitive scientists have been asking questions about the right methodologies and levels of explanation to pursue this goal, and make cognitive science a coherent science of the mind. Key questions include: Is there a privileged level of explanation in cognitive science? How do different levels of explanation fit together, or relate to one another? How should explanations at one level inform or constrain explanations at (...)
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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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  • 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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  • Does a rock implement every finite-state automaton?David J. Chalmers - 1996 - Synthese 108 (3):309-33.
    Hilary Putnam has argued that computational functionalism cannot serve as a foundation for the study of the mind, as every ordinary open physical system implements every finite-state automaton. I argue that Putnam's argument fails, but that it points out the need for a better understanding of the bridge between the theory of computation and the theory of physical systems: the relation of implementation. It also raises questions about the class of automata that can serve as a basis for understanding the (...)
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  • Are We Sims? How Computer Simulations Represent and What this Means for the Simulation Argument.Claus Beisbart - 2014 - The Monist 97 (3):399-417.
    N. Bostrom’s simulation argument and two additional assumptions imply that we likely live in a computer simulation. The argument is based upon the following assumption about the workings of realistic brain simulations: The hardware of a computer on which a brain simulation is run bears a close analogy to the brain itself. To inquire whether this is so, I analyze how computer simulations trace processes in their targets. I describe simulations as fictional, mathematical, pictorial, and material models. Even though the (...)
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  • A Mechanistic Account of Biological Computation.Lorenzo Baravalle & Davide Vecchi - forthcoming - British Journal for the Philosophy of Science.
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  • Rethinking the problem of cognition.Mikio Akagi - 2018 - Synthese 195 (8):3547-3570.
    The present century has seen renewed interest in characterizing cognition, the object of inquiry of the cognitive sciences. In this paper, I describe the problem of cognition—the absence of a positive characterization of cognition despite a felt need for one. It is widely recognized that the problem is motivated by decades of controversy among cognitive scientists over foundational questions, such as whether non-neural parts of the body or environment can realize cognitive processes, or whether plants and microbes have cognitive processes. (...)
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  • 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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  • The Representational Foundations of Computation.Michael Rescorla - 2015 - Philosophia Mathematica 23 (3):338-366.
    Turing computation over a non-linguistic domain presupposes a notation for the domain. Accordingly, computability theory studies notations for various non-linguistic domains. It illuminates how different ways of representing a domain support different finite mechanical procedures over that domain. Formal definitions and theorems yield a principled classification of notations based upon their computational properties. To understand computability theory, we must recognize that representation is a key target of mathematical inquiry. We must also recognize that computability theory is an intensional enterprise: it (...)
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  • Computation and Multiple Realizability.Marcin Miłkowski - 2016 - In Vincent C. Müller (ed.), Fundamental Issues of Artificial Intelligence. Cham: Springer. pp. 29-41.
    Multiple realizability (MR) is traditionally conceived of as the feature of computational systems, and has been used to argue for irreducibility of higher-level theories. I will show that there are several ways a computational system may be seen to display MR. These ways correspond to (at least) five ways one can conceive of the function of the physical computational system. However, they do not match common intuitions about MR. I show that MR is deeply interest-related, and for this reason, difficult (...)
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  • Against Computational Perspectivalism.Dimitri Coelho Mollo - 2021 - British Journal for the Philosophy of Science 72 (4):1129-1153.
    Computational perspectivalism has been recently proposed as an alternative to mainstream accounts of physical computation, and especially to the teleologically-based mechanistic view. It takes physical computation to be partly dependent on explanatory perspectives and eschews appeal to teleology in helping individuate computational systems. I assess several varieties of computational perspectivalism, showing that they either collapse into existing non-perspectival views or end up with unsatisfactory or implausible accounts of physical computation. Computational perspectivalism fails, therefore, to be a compelling alternative to perspective-independent (...)
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  • The Challenges of Artificial Judicial Decision-Making for Liberal Democracy.Christoph Winter - 2022 - In P. Bystranowski, Bartosz Janik & M. Prochnicki (eds.), Judicial Decision-Making: Integrating Empirical and Theoretical Perspectives. Springer Nature. pp. 179-204.
    The application of artificial intelligence (AI) to judicial decision-making has already begun in many jurisdictions around the world. While AI seems to promise greater fairness, access to justice, and legal certainty, issues of discrimination and transparency have emerged and put liberal democratic principles under pressure, most notably in the context of bail decisions. Despite this, there has been no systematic analysis of the risks to liberal democratic values from implementing AI into judicial decision-making. This article sets out to fill this (...)
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  • Artificial consciousness: A perspective from the free energy principle.Wanja Wiese - manuscript
    Could a sufficiently detailed computer simulation of consciousness replicate consciousness? In other words, is performing the right computations sufficient for artificial consciousness? Or will there remain a difference between simulating and being a conscious system, because the right computations must be implemented in the right way? From the perspective of Karl Friston's free energy principle, self-organising systems (such as living organisms) share a set of properties that could be realised in artificial systems, but are not instantiated by computers with a (...)
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  • Wide computationalism revisited: distributed mechanisms, parismony and testability.Luke Kersten - 2024 - Philosophical Explorations 27 (2):1-18.
    Recent years have seen a surge of interest in applying mechanistic thinking to computational accounts of implementation and individuation. One recent extension of this work involves so-called ‘wide’ approaches to computation, the view that computational processes spread out beyond the boundaries of the individual. These ‘mechanistic accounts of wide computation’ maintain that computational processes are wide in virtue of being part of mechanisms that extend beyond the boundary of the individual. This paper aims to further develop the mechanistic account of (...)
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  • Extended music cognition.Luke Kersten - 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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  • Pancomputationalism: Theory or metaphor?Vincent C. Müller - 2014 - In Ruth Hagenbruger & Uwe V. Riss (eds.), Philosophy, computing and information science. Pickering & Chattoo. pp. 213-221.
    The theory that all processes in the universe are computational is attractive in its promise to provide an understandable theory of everything. I want to suggest here that this pancomputationalism is not sufficiently clear on which problem it is trying to solve, and how. I propose two interpretations of pancomputationalism as a theory: I) the world is a computer and II) the world can be described as a computer. The first implies a thesis of supervenience of the physical over computation (...)
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  • The Cognitive Phenomenology Argument for Disembodied AI Consciousness.Cody Turner - 2020 - In Steven S. Gouveia (ed.), The Age of Artificial Intelligence: An Exploration. Vernon Press. pp. 111-132.
    In this chapter I offer two novel arguments for what I call strong primitivism about cognitive phenomenology, the thesis that there exists a phenomenology of cognition that is neither reducible to, nor dependent upon, sensory phenomenology. I then contend that strong primitivism implies that phenomenal consciousness does not require sensory processing. This latter contention has implications for the philosophy of artificial intelligence. For if sensory processing is not a necessary condition for phenomenal consciousness, then it plausibly follows that AI consciousness (...)
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  • The Cognitive Basis of Computation: Putting Computation in Its Place.Daniel D. Hutto, Erik Myin, Anco Peeters & Farid Zahnoun - 2018 - In Mark Sprevak & Matteo Colombo (eds.), The Routledge Handbook of the Computational Mind. Routledge. pp. 272-282.
    The mainstream view in cognitive science is that computation lies at the basis of and explains cognition. Our analysis reveals that there is no compelling evidence or argument for thinking that brains compute. It makes the case for inverting the explanatory order proposed by the computational basis of cognition thesis. We give reasons to reverse the polarity of standard thinking on this topic, and ask how it is possible that computation, natural and artificial, might be based on cognition and not (...)
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  • Functional individuation, mechanistic implementation: the proper way of seeing the mechanistic view of concrete computation.Dimitri Coelho Mollo - 2017 - Synthese 195 (8):3477-3497.
    I examine a major objection to the mechanistic view of concrete computation, stemming from an apparent tension between the abstract nature of computational explanation and the tenets of the mechanistic framework: while computational explanation is medium-independent, the mechanistic framework insists on the importance of providing some degree of structural detail about the systems target of the explanation. I show that a common reply to the objection, i.e. that mechanistic explanation of computational systems involves only weak structural constraints, is not enough (...)
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  • Transhumanismo, pregunta a la naturaleza humana.Giovanni Fernández Valdés - 2020 - Perseitas 9:389-421.
    El transhumanismo como filosofía e ideología tecnologicista tiene cada vez más adeptos y se coloca en los ámbitos académicos como una posición positiva, posible y deseable. Su implementación aparece solapada en una vida cotidiana que depende, como nunca antes, de los avances tecnológicos. La posición que manejaremos es que esta ideología, que sobredimensiona el papel de la tecnología en la sociedad, tiene una visión limitada respecto con los conflictos éticos, económicos y sociales que dimanan de sus presupuestos. El problema no (...)
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  • The Tractable Cognition Thesis.Iris Van Rooij - 2008 - Cognitive Science 32 (6):939-984.
    The recognition that human minds/brains are finite systems with limited resources for computation has led some researchers to advance theTractable Cognition thesis: Human cognitive capacities are constrained by computational tractability. This thesis, if true, serves cognitive psychology by constraining the space of computational‐level theories of cognition. To utilize this constraint, a precise and workable definition of “computational tractability” is needed. Following computer science tradition, many cognitive scientists and psychologists define computational tractability as polynomial‐time computability, leading to theP‐Cognition thesis. This article (...)
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  • Let's dance! The equivocation in Chalmers' dancing qualia argument.B. van Heuveln, Eric Dietrich & M. Oshima - 1998 - Minds and Machines 8 (2):237-249.
    David Chalmers' dancing qualia argument is intended to show that phenomenal experiences, or qualia, are organizational invariants. The dancing qualia argument is a reductio ad absurdum, attempting to demonstrate that holding an alternative position, such as the famous inverted spectrum argument, leads one to an implausible position about the relation between consciousness and cognition. In this paper, we argue that Chalmers' dancing qualia argument fails to establish the plausibility of qualia being organizational invariants. Even stronger, we will argue that the (...)
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  • A cognitive analysis of the chinese room argument.Norman Y. Teng - 2000 - Philosophical Psychology 13 (3):313-24.
    Searle's Chinese room argument is analyzed from a cognitive point of view. The analysis is based on a newly developed model of conceptual integration, the many space model proposed by Fauconnier and Turner. The main point of the analysis is that the central inference constructed in the Chinese room scenario is a result of a dynamic, cognitive activity of conceptual blending, with metaphor defining the basic features of the blending. Two important consequences follow: (1) Searle's recent contention that syntax is (...)
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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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  • 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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  • 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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  • 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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  • The Swapping Constraint.Henry Ian Schiller - 2018 - Minds and Machines 28 (3):605-622.
    Triviality arguments against the computational theory of mind claim that computational implementation is trivial and thus does not serve as an adequate metaphysical basis for mental states. It is common to take computational implementation to consist in a mapping from physical states to abstract computational states. In this paper, I propose a novel constraint on the kinds of physical states that can implement computational states, which helps to specify what it is for two physical states to non-trivially implement the same (...)
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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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  • Computing in the nick of time.J. Brendan Ritchie & Colin Klein - 2023 - Ratio 36 (3):169-179.
    The medium‐independence of computational descriptions has shaped common conceptions of computational explanation. So long as our goal is to explain how a system successfully carries out its computations, then we only need to describe the abstract series of operations that achieve the desired input–output mapping, however they may be implemented. It is argued that this abstract conception of computational explanation cannot be applied to so‐called real‐time computing systems, in which meeting temporal deadlines imposed by the systems with which a device (...)
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  • Bayesian Sensorimotor Psychology.Michael Rescorla - 2016 - Mind and Language 31 (1):3-36.
    Sensorimotor psychology studies the mental processes that control goal-directed bodily motion. Recently, sensorimotor psychologists have provided empirically successful Bayesian models of motor control. These models describe how the motor system uses sensory input to select motor commands that promote goals set by high-level cognition. I highlight the impressive explanatory benefits offered by Bayesian models of motor control. I argue that our current best models assign explanatory centrality to a robust notion of mental representation. I deploy my analysis to defend intentional (...)
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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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  • Філософські проблеми ідеї свідомої машини.Konstantin Rayhert - 2017 - Схід 6 (152):104-107.
    The study outlines the existing and potential philosophical issues of the idea of conscious machines originated from the development of artificial consciousness within the framework of contemporary research of artificial intelligence and cognitive robotics. The outline shows that the idea of conscious machines is concerned with two big philosophical issues. The first philosophical issue is a definition of consciousness, taking into account the selection of a set of objects that can have consciousness, the typology of consciousness, the clarifying of the (...)
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  • What is a Computer? A Survey.William J. Rapaport - 2018 - Minds and Machines 28 (3):385-426.
    A critical survey of some attempts to define ‘computer’, beginning with some informal ones, then critically evaluating those of three philosophers, and concluding with an examination of whether the brain and the universe are computers.
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  • From Turing to Peirce. A semiotic interpretation of computation.Luca M. Possati - 2023 - Foundations of Science 28 (4):1085-1110.
    The thesis of the paper is that semiotic processes are intrinsic to computation and computational systems. An explanation of computation that does not take this semiotic dimension into account is incomplete. Semiosis is essential to computation and therefore requires a rigorous definition. To prove this thesis, the author analyzes two concepts of computation: the Turing machine and the mechanistic conception of physical computation. The paper is organized in two parts. The first part (Sects. 2 and 3) develops a re-interpretation of (...)
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  • Neural Representations Beyond “Plus X”.Alessio Plebe & Vivian M. De La Cruz - 2018 - Minds and Machines 28 (1):93-117.
    In this paper we defend structural representations, more specifically neural structural representation. We are not alone in this, many are currently engaged in this endeavor. The direction we take, however, diverges from the main road, a road paved by the mathematical theory of measure that, in the 1970s, established homomorphism as the way to map empirical domains of things in the world to the codomain of numbers. By adopting the mind as codomain, this mapping became a boon for all those (...)
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  • Causation and Information: Where Is Biological Meaning to Be Found?Mark Pharoah - 2020 - Biosemiotics 13 (3):309-326.
    The term ‘information’ is used extensively in biology, cognitive science and the philosophy of consciousness in relation to the concepts of ‘meaning’ and ‘causation’. While ‘information’ is a term that serves a useful purpose in specific disciplines, there is much to the concept that is problematic. Part 1 is a critique of the stance that information is an independently existing entity. On this view, and in biological contexts, systems transmit, acquire, assimilate, decode and manipulate it, and in so doing, generate (...)
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  • The “Slicing Problem” for Computational Theories of Consciousness.Chris Percy & Andrés Gómez-Emilsson - 2022 - Open Philosophy 5 (1):718-736.
    The “Slicing Problem” is a thought experiment that raises questions for substrate-neutral computational theories of consciousness, including those that specify a certain causal structure for the computation like Integrated Information Theory. The thought experiment uses water-based logic gates to construct a computer in a way that permits cleanly slicing each gate and connection in half, creating two identical computers each instantiating the same computation. The slicing can be reversed and repeated via an on/off switch, without changing the amount of matter (...)
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  • A Theory of Practical Meaning.Carlotta Pavese - 2017 - Philosophical Topics 45 (2):65-96.
    This essay is divided into two parts. In the first part (§2), I introduce the idea of practical meaning by looking at a certain kind of procedural systems — the motor system — that play a central role in computational explanations of motor behavior. I argue that in order to give a satisfactory account of the content of the representations computed by motor systems (motor commands), we need to appeal to a distinctively practical kind of meaning. Defending the explanatory relevance (...)
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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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  • Are machines radically contextualist?Ryan M. Nefdt - 2023 - Mind and Language 38 (3):750-771.
    In this article, I describe a novel position on the semantics of artificial intelligence. I present a problem for the current artificial neural networks used in machine learning, specifically with relation to natural language tasks. I then propose that from a metasemantic level, meaning in machines can best be interpreted as radically contextualist. Finally, I consider what this might mean for human‐level semantic competence from a comparative perspective.
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