About this topic
Summary The theory of computation is a mathematical theory about the properties of abstract computational objects, such as algorithms and Turing machines. They are abstract in the sense that they ignore or leave out considerations about by features of physical implementations, such as finite memory.  In contrast, computations are done by physical systems: concrete machines made of silicon and metal, or brains made of biological materials, can run algorithms or implement Turing machines. This area is concerned with questions about how the abstract objects that are in the purview of the theory of computation relate to physical systems.
Key works The relationship between abstract computation and physical systems such as brains is a central issue in philosophy of mind, particularly given the rise of computational functionalism as a foundation for the study of the mind.  Here the work of Chalmers 1996 provides a good starting point for bridging the theory of computation with theories of physical systems by means of an implementation relation. 
Introductions A good introduction is Piccinini 2010
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  1. Implementing a Computing System: A Pluralistic Approach.Syed AbuMusab - 2023 - Global Philosophy 33 (1):1-19.
    In chapter eleven of "On The Foundation of Computing," Primiero takes on the implementation debate in computer science. He contrasts his theory with two other views—the Semantic and the specification—artifact. In this paper, I argue that there is a way to fine-tune the implementation concept further. Firstly, contrary to Primiero, I claim it is problematic to separate the implementation relationship from the conditions which make it correct. Secondly, by taking a pluralistic approach to implementation, I claim it is a mistake (...)
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  2. TC*.Didehvar Farzad - manuscript
    One of the possible hypotheses about time is to consider any instant of time as fuzzy number, so that two instants of time could be overlapped. Historically, some Mathematicians and Philosophers have had similar ideas like Brouwer and Husserl [5]. Throughout this article, the impact of this change on Theory of Computation and Complexity Theory are studied. In order to rebuild Theory of Computation in a more successful and productive approach to solve some major problems in Complexity Theory, the present (...)
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  3. Bruce D'Ambrosio, Qualitative Process Theory Using Linguistic Variables[REVIEW]Varol Akman - 1991 - ACM SIGART Bulletin 2 (2):25-27.
    Ken Forbus's Qualitative Process Theory (QPT) is a popular theory for reasoning about the physical aspects of the daily world. Qualitative Process Theory Using Linguistic Variables by Bruce D'Ambrosio (Springer-Verlag, New York, 1989) is an attempt to fill some gaps in QPT.
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  4. Strengthening Weak Emergence.Nora Berenstain - 2020 - Erkenntnis 87 (5):2457-2474.
    Bedau's influential (1997) account analyzes weak emergence in terms of the non-derivability of a system’s macrostates from its microstates except by simulation. I offer an improved version of Bedau’s account of weak emergence in light of insights from information theory. Non-derivability alone does not guarantee that a system’s macrostates are weakly emergent. Rather, it is non-derivability plus the algorithmic compressibility of the system’s macrostates that makes them weakly emergent. I argue that the resulting information-theoretic picture provides a metaphysical account of (...)
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  5. A Dilemma for Solomonoff Prediction.Sven Neth - forthcoming - Philosophy of Science.
    The framework of Solomonoff prediction assigns prior probability to hypotheses inversely proportional to their Kolmogorov complexity. There are two well-known problems. First, the Solomonoff prior is relative to a choice of Universal Turing machine. Second, the Solomonoff prior is not computable. However, there are responses to both problems. Different Solomonoff priors converge with more and more data. Further, there are computable approximations to the Solomonoff prior. I argue that there is a tension between these two responses. This is because computable (...)
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  6. Natural morphological computation as foundation of learning to learn in humans, other living organisms, and intelligent machines.G. Dodig-Crnkovic - 2020 - Philosophies 5 (3):17-32.
    The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial, natural sciences, and philosophy. The question is, what at this stage of the development the inspiration from nature, specifically its computational models such as (...)
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  7. Why Simpler Computer Simulation Models Can Be Epistemically Better for Informing Decisions.Casey Helgeson, Vivek Srikrishnan, Klaus Keller & Nancy Tuana - 2021 - Philosophy of Science 88 (2):213-233.
    For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many ti...
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  8. How to be concrete: mechanistic computation and the abstraction problem.Luke Kersten - 2020 - Philosophical Explorations 23 (3):251-266.
    This paper takes up a recent challenge to mechanistic approaches to computational implementation, the view that computational implementation is best explicated within a mechanistic framework. The challenge, what has been labelled “the abstraction problem”, claims that one of MAC’s central pillars – medium independence – is deeply confused when applied to the question of computational implementation. The concern is that while it makes sense to say that computational processes are abstract (i.e. medium-independent), it makes considerably less sense to say that (...)
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  9. Integrating computation into the mechanistic hierarchy in the cognitive and neural sciences.Lotem Elber-Dorozko & Oron Shagrir - 2019 - Synthese 199 (Suppl 1):43-66.
    It is generally accepted that, in the cognitive and neural sciences, there are both computational and mechanistic explanations. We ask how computational explanations can integrate into the mechanistic hierarchy. The problem stems from the fact that implementation and mechanistic relations have different forms. The implementation relation, from the states of an abstract computational system to the physical, implementing states is a homomorphism mapping relation. The mechanistic relation, however, is that of part/whole; the explaining features in a mechanistic explanation are the (...)
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  10. Punched Card Methods in Scientific Computation by Wallace J. Eckert; Calculating Machines: Recent and Prospective Developments and Their Impact on Mathematical Physics and Calculating Instruments and Machines by Douglas R. Hartree. [REVIEW]Paul Ceruzzi - 1986 - Isis 77:154-156.
  11. Qu’est-ce que l’informatique.Franck Varenne - 2009 - Paris: Vrin.
    Que peut bien être l’informatique pour nous envahir à ce point? Se fondant sur des travaux récents de philosophie de l’informatique, ce livre revient sur la notion de Machine de Turing et sur la Thèse de Church : l’ordinateur peut-il tout simuler? . Eclairant les notions de computation et d’abstraction à la lumière de celles de simulation et d’ontologie, il montre en quoi l’informatique n’est ni simplement une branche des mathématiques, ni une technologie de l’information, mais une technologie des croisements (...)
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  12. Social learning by observation is analogue, instruction is digital.Marion Blute - 2001 - Behavioral and Brain Sciences 24 (2):327-327.
    Social learning in the strict sense is learning by observation or instruction. Learning by observation appears to be an analogue process while learning by instruction is digital. In evolutionary biology this distinction is currently thought to have implications for the extent to which mechanisms can function successfully as an inheritance system in an evolutionary process.
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  13. Turing-, human- and physical computability: An unasked question. [REVIEW]Eli Dresner - 2008 - Minds and Machines 18 (3):349-355.
    In recent years it has been convincingly argued that the Church-Turing thesis concerns the bounds of human computability: The thesis was presented and justified as formally delineating the class of functions that can be computed by a human carrying out an algorithm. Thus the Thesis needs to be distinguished from the so-called Physical Church-Turing thesis, according to which all physically computable functions are Turing computable. The latter is often claimed to be false, or, if true, contingently so. On all accounts, (...)
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  14. Representation of sequential circuits in combinatory logic.Frederic B. Fitch - 1958 - Philosophy of Science 25 (4):263-279.
    We will be dealing with “sequential circuits” in the sense of E. F. Moore and G. H. Mealy. Each such circuit is assumed to have a finite number of input wires and a finite number of output wires. Each element of such a circuit will be assumed to be an and-circuit, an or-circuit, a not-circuit, or a delay circuit, for some specified temporal delay. Each element has one output wire which, however, may branch in order to serve several purposes simultaneously. (...)
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  15. The interactive nature of computing: Refuting the strong church–turing thesis. [REVIEW]Dina Goldin & Peter Wegner - 2008 - Minds and Machines 18 (1):17-38.
    The classical view of computing positions computation as a closed-box transformation of inputs (rational numbers or finite strings) to outputs. According to the interactive view of computing, computation is an ongoing interactive process rather than a function-based transformation of an input to an output. Specifically, communication with the outside world happens during the computation, not before or after it. This approach radically changes our understanding of what is computation and how it is modeled. The acceptance of interaction as a new (...)
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  16. Infinite time Turing machines.Joel David Hamkins - 2002 - Minds and Machines 12 (4):567-604.
    Infinite time Turing machines extend the operation of ordinary Turing machines into transfinite ordinal time. By doing so, they provide a natural model of infinitary computability, a theoretical setting for the analysis of the power and limitations of supertask algorithms.
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  17. Computational empiricism.Paul Humphreys - 1995 - Foundations of Science 1 (1):119-130.
    I argue here for a number of ways that modern computational science requires a change in the way we represent the relationship between theory and applications. It requires a switch away from logical reconstruction of theories in order to take surface mathematical syntax seriously. In addition, syntactically different versions of the same theory have important differences for applications, and this shows that the semantic account of theories is inappropriate for some purposes. I also argue against formalist approaches in the philosophy (...)
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  18. Synchronic and diachronic emergence.Paul Humphreys - 2008 - Minds and Machines 18 (4):431-442.
    I discuss here a number of different kinds of diachronic emergence, noting that they differ in important ways from synchronic conceptions. I argue that Bedau’s weak emergence has an essentially historical aspect, in that there can be two indistinguishable states, one of which is weakly emergent, the other of which is not. As a consequence, weak emergence is about tokens, not types, of states. I conclude by examining the question of whether the concept of weak emergence is too weak and (...)
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  19. Reflections on gödel's and Gandy's reflections on Turing's thesis.David Israel - 2002 - Minds and Machines 12 (2):181-201.
    We sketch the historical and conceptual context of Turing's analysis of algorithmic or mechanical computation. We then discuss two responses to that analysis, by Gödel and by Gandy, both of which raise, though in very different ways. The possibility of computation procedures that cannot be reduced to the basic procedures into which Turing decomposed computation. Along the way, we touch on some of Cleland's views.
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  20. The elementary units of meaning.Paul J. M. Jorion - 2000 - Behavioral and Brain Sciences 23 (4):483-484.
    Examining the implications of a localist model for linguistic performance, I show the strengths of the P-graph, a network of elementary units of meaning where utterance results from relaxation through the operation of a dynamics of affect values. A unit of meaning is stored in a synaptic connection that brings together two words. Such a model, consistent with the anatomy and physiology of the neural tissue, eschews a number of traditional pitfalls of “semantic networks”: (1) ambiguity ceases to be an (...)
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  21. Programs, grammars and arguments: A personal view of some connections between computation, language and logic.J. Lambek - 1997 - Bulletin of Symbolic Logic 3 (3):312-328.
    As an undergraduate I was taught to multiply two numbers with the help of log tables, using the formulaHaving graduated to teach calculus to Engineers, I learned that log tables were to be replaced by slide rules. It was then that Imade the fateful decision that there was no need for me to learn how to use this tedious device, as I could always rely on the students to perform the necessary computations. In the course of time, slide rules were (...)
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  22. Theories of structure versus theories of change.Melanie Mitchell - 1998 - Behavioral and Brain Sciences 21 (5):645-646.
    The dynamics/computation debate recalls a similar debate in the evolutionary biology community concerning the relative primacy of theories of structure versus theories of change. A full account of cognition will require a rapprochement between such theories and will include both computational and dynamical notions. The key to making computation relevant to cognition is not making it analog, but rather understanding how functional information-processing structures can emerge in complex dynamical systems.
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  23. The problem of the many minds.Bradley Monton & Sanford Goldberg - 2006 - Minds and Machines 16 (4):463-470.
    It is argued that, given certain reasonable premises, an infinite number of qualitatively identical but numerically distinct minds exist per functioning brain. The three main premises are (1) mental properties supervene on brain properties; (2) the universe is composed of particles with nonzero extension; and (3) each particle is composed of continuum-many point-sized bits of particle-stuff, and these points of particle-stuff persist through time.
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  24. Comments on `two undecidable problems of analysis'.Bruno Scarpellini - 2003 - Minds and Machines 13 (1):79-85.
    We first discuss some technical questions which arise in connection with the construction of undecidable propositions in analysis, in particular in connection with the notion of the normal form of a function representing a predicate. Then it is stressed that while a function f(x) may be computable in the sense of recursive function theory, it may nevertheless have undecidable properties in the realm of Fourier analysis. This has an implication for a conjecture of Penrose's which states that classical physics is (...)
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  25. Physical hypercomputation and the church–turing thesis.Oron Shagrir & Itamar Pitowsky - 2003 - Minds and Machines 13 (1):87-101.
    We describe a possible physical device that computes a function that cannot be computed by a Turing machine. The device is physical in the sense that it is compatible with General Relativity. We discuss some objections, focusing on those which deny that the device is either a computer or computes a function that is not Turing computable. Finally, we argue that the existence of the device does not refute the Church–Turing thesis, but nevertheless may be a counterexample to Gandy's thesis.
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  26. Logically possible machines.Eric Steinhart - 2002 - Minds and Machines 12 (2):259-280.
    I use modal logic and transfinite set-theory to define metaphysical foundations for a general theory of computation. A possible universe is a certain kind of situation; a situation is a set of facts. An algorithm is a certain kind of inductively defined property. A machine is a series of situations that instantiates an algorithm in a certain way. There are finite as well as transfinite algorithms and machines of any degree of complexity (e.g., Turing and super-Turing machines and more). There (...)
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  27. On physicalism and algorithmism: Can machines think?Hao Wang - 1993 - Philosophia Mathematica 1 (2):97-138.
    This essay discusses a number of questions which arise from attempts to reduce the mental to the physical or the mental and the physical to the computational. It makes, in an organized way, several basic distinctions between different kinds of accounts of the mind. It reconstructs and elaborates many discussions between Gödel and the author on the nature of the human mind, with special emphasis on its mathematical capabilities.
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  28. Is there a nonrecursive decidable equational theory?Benjamin Wells - 2002 - Minds and Machines 12 (2):301-324.
    The Church-Turing Thesis (CTT) is often paraphrased as ``every computable function is computable by means of a Turing machine.'' The author has constructed a family of equational theories that are not Turing-decidable, that is, given one of the theories, no Turing machine can recognize whether an arbitrary equation is in the theory or not. But the theory is called pseudorecursive because it has the additional property that when attention is limited to equations with a bounded number of variables, one obtains, (...)
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Analog and Digital Computation
  1. Contents and Vehicles in Analog Perception.Jacob Beck - 2023 - Crítica. Revista Hispanoamericana de Filosofía 55 (163):109–127.
    Building on Christopher Peacocke’s account of analog perceptual contentand my own account of analog perceptual vehicles, I defend three claims: that theperception of magnitudes often has analog contents; that the perception of magni-tudes often has analog vehicles; and that the first claim is true in virtue of the second—that is, the analog vehicles help to ground the analog contents.
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  2. Being and the screen: How the digital changes perception. [REVIEW]Anthony Longo - 2022 - Information, Communication and Society.
  3. Digital Praxis: Notes on a Phenomenological Synthesis.Íñigo García-Moncó - 2022 - Argumentos de Razón Técnica 15:255-274.
    This paper aims to provide a general phenomenological framework for the study of digital experiences as technological praxis. This approach is built through a synthesis of the categories proper to different currents of thought such as Merleau-Ponty's bodily phenomenology, the postphenomenology of Don Ihde and his school, hermeneutics and information theories. These notes develop a progressive analysis of the phenomenal dimensions that take place in the user-device interaction, from the stimulus base to virtual recreations. Through the intersubjective relationship with the (...)
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  4. Mind as Machine: The Influence of Mechanism on the Conceptual Foundations of the Computer Metaphor.Pavel Baryshnikov - 2022 - RUDN Journal of Philosophy 26 (4):755-769.
    his article will focus on the mechanistic origins of the computer metaphor, which forms the conceptual framework for the methodology of the cognitive sciences, some areas of artificial intelligence and the philosophy of mind. The connection between the history of computing technology, epistemology and the philosophy of mind is expressed through the metaphorical dictionaries of the philosophical discourse of a particular era. The conceptual clarification of this connection and the substantiation of the mechanistic components of the computer metaphor is the (...)
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  5. Position paper on ethical, legal and social challenges linked to audio- and video-based AAL solutions.Alin Ake-Kob, Slavisa Aleksic, Zoltán Alexin, Aurelija Blaževičiene, Anto Čartolovni, Liane Colonna, Carina Dantas, Anton Fedosov, Eduard Fosch-Villaronga, Francisco Florez-Revuelta, Zhicheng He, Aleksandar Jevremović, Andrzej Klimczuk, Maksymilian Kuźmicz, Lambros Lambrinos, Christoph Lutz, Anamaria Malešević, Renata Mekovec, Cristina Miguel, Tamar Mujirishvili, Zada Pajalic, Rodrigo Perez Vega, Barbara Pierscionek, Siddharth Ravi, Pika Sarf, Agusti Solanas & Aurelia Tamo-Larrieux - 2022 - Https://Goodbrother.Eu/.
    In this position paper, we have used Alan Cooper’s persona technique to illustrate the utility of audio- and video-based AAL technologies. Therefore, two primary examples of potential audio- and video-based AAL users, Anna and Irakli, serve as reference points for describing salient ethical, legal and social challenges related to use of AAL. These challenges are presented on three levels: individual, societal, and regulatory. For each challenge, a set of policy recommendations is suggested.
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  6. Counting with Cilia: The Role of Morphological Computation in Basal Cognition Research.Wiktor Rorot - 2022 - Entropy 24 (11):1581.
    “Morphological computation” is an increasingly important concept in robotics, artificial intelligence, and philosophy of the mind. It is used to understand how the body contributes to cognition and control of behavior. Its understanding in terms of "offloading" computation from the brain to the body has been criticized as misleading, and it has been suggested that the use of the concept conflates three classes of distinct processes. In fact, these criticisms implicitly hang on accepting a semantic definition of what constitutes computation. (...)
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  7. The Structure of Analog Representation.Andrew Y. Lee, Joshua Myers & Gabriel Oak Rabin - 2023 - Noûs 57 (1):209-237.
    This paper develops a theory of analog representation. We first argue that the mark of the analog is to be found in the nature of a representational system’s interpretation function, rather than in its vehicles or contents alone. We then develop the rulebound structure theory of analog representation, according to which analog systems are those that use interpretive rules to map syntactic structural features onto semantic structural features. The theory involves three degree-theoretic measures that capture three independent ways in which (...)
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  8. Computing, Modelling, and Scientific Practice: Foundational Analyses and Limitations.Filippos A. Papagiannopoulos - 2018 - Dissertation, University of Western Ontario
    This dissertation examines aspects of the interplay between computing and scientific practice. The appropriate foundational framework for such an endeavour is rather real computability than the classical computability theory. This is so because physical sciences, engineering, and applied mathematics mostly employ functions defined in continuous domains. But, contrary to the case of computation over natural numbers, there is no universally accepted framework for real computation; rather, there are two incompatible approaches --computable analysis and BSS model--, both claiming to formalise algorithmic (...)
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  9. Unrealistic models for realistic computations: how idealisations help represent mathematical structures and found scientific computing.Philippos Papayannopoulos - 2020 - Synthese 199 (1-2):249-283.
    We examine two very different approaches to formalising real computation, commonly referred to as “Computable Analysis” and “the BSS approach”. The main models of computation underlying these approaches—bit computation and BSS, respectively—have also been put forward as appropriate foundations for scientific computing. The two frameworks offer useful computability and complexity results about problems whose underlying domain is an uncountable space. Since typically the problems dealt with in physical sciences, applied mathematics, economics, and engineering are also defined in uncountable domains, it (...)
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  10. Perception is Analog: The Argument from Weber's Law.Jacob Beck - 2019 - Journal of Philosophy 116 (6):319-349.
    In the 1980s, a number of philosophers argued that perception is analog. In the ensuing years, these arguments were forcefully criticized, leaving the thesis in doubt. This paper draws on Weber’s Law, a well-entrenched finding from psychophysics, to advance a new argument that perception is analog. This new argument is an adaptation of an argument that cognitive scientists have leveraged in support of the contention that primitive numerical representations are analog. But the argument here is extended to the representation of (...)
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  11. Omnipresent Maxwell’s demons orchestrate information management in living cells.Antoine Danchin Gregory Boel, Olivier Danot, Victor de Lorenzo & Antoine Danchin - 2019 - Microbial Biotechnology 12 (2):210-242.
    The development of synthetic biology calls for accurate understanding of the critical functions that allow construction and operation of a living cell. Besides coding for ubiquitous structures, minimal genomes encode a wealth of functions that dissipate energy in an unanticipated way. Analysis of these functions shows that they are meant to manage information under conditions when discrimination of substrates in a noisy background is preferred over a simple recognition process. We show here that many of these functions, including transporters and (...)
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  12. Analog Mental Representation.Jacob Beck - forthcoming - WIREs Cognitive Science.
    Over the past 50 years, philosophers and psychologists have perennially argued for the existence of analog mental representations of one type or another. This study critically reviews a number of these arguments as they pertain to three different types of mental representation: perceptual representations, imagery representations, and numerosity representations. Along the way, careful consideration is given to the meaning of “analog” presupposed by these arguments for analog mental representation, and to open avenues for future research.
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  13. 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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  14. Computation in cognitive science: it is not all about Turing-equivalent computation.Kenneth Aizawa - 2010 - Studies in History and Philosophy of Science Part A 41 (3):227-236.
    It is sometimes suggested that the history of computation in cognitive science is one in which the formal apparatus of Turing-equivalent computation, or effective computability, was exported from mathematical logic to ever wider areas of cognitive science and its environs. This paper, however, indicates some respects in which this suggestion is inaccurate. Computability theory has not been focused exclusively on Turing-equivalent computation. Many essential features of Turing-equivalent computation are not captured in definitions of computation as symbol manipulation. Turing-equivalent computation did (...)
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  15. Some recent developments on Shannon's General Purpose Analog Computer.Daniel Graça - 2004 - Mathematical Logic Quarterly 50 (4-5):473-495.
    This paper revisits one of the first models of analog computation, the General Purpose Analog Computer. In particular, we restrict our attention to the improved model presented in [11] and we show that it can be further refined. With this we prove the following: the previous model can be simplified; it admits extensions having close connections with the class of smooth continuous time dynamical systems. As a consequence, we conclude that some of these extensions achieve Turing universality. Finally, it is (...)
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  16. David Wolpert on impossibility, incompleteness, the liar paradox, the limits of computation, a non-quantum mechanical uncertainty principle and the universe as computer—the ultimate theorem in Turing Machine Theory.Michael Starks - manuscript
    I have read many recent discussions of the limits of computation and the universe as computer, hoping to find some comments on the amazing work of polymath physicist and decision theorist David Wolpert but have not found a single citation and so I present this very brief summary. Wolpert proved some stunning impossibility or incompleteness theorems (1992 to 2008-see arxiv.org) on the limits to inference (computation) that are so general they are independent of the device doing the computation, and even (...)
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  17. 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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  18. What is a digital state?Vincent C. Müller - 2013 - In Mark J. Bishop & Yasemin Erden (eds.), The Scandal of Computation - What is Computation? - AISB Convention 2013. AISB. pp. 11-16.
    There is much discussion about whether the human mind is a computer, whether the human brain could be emulated on a computer, and whether at all physical entities are computers (pancomputationalism). These discussions, and others, require criteria for what is digital. I propose that a state is digital if and only if it is a token of a type that serves a particular function - typically a representational function for the system. This proposal is made on a syntactic level, assuming (...)
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  19. The Physical Church Thesis and Physical Computational Complexity.Itamar Pitowski - 1990 - Iyyun 39:81-99.
  20. Pancomputationalism: Theory or metaphor?Vincent C. Müller - 2014 - In Ruth Hagengruber & Uwe 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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  21. Susan Stuart & Gordana Dodig Crnkovic : 'Computation, Information, Cognition: The Nexus and the Liminal'. [REVIEW]Vincent C. Müller - 2009 - Cybernetics and Human Knowing 16 (3-4):201-203.
    Review of: "Computation, Information, Cognition: The Nexus and the Liminal", Ed. Susan Stuart & Gordana Dodig Crnkovic, Newcastle: Cambridge Scholars Publishing, September 2007, xxiv+340pp, ISBN: 9781847180902, Hardback: £39.99, $79.99 ---- Are you a computer? Is your cat a computer? A single biological cell in your stomach, perhaps? And your desk? You do not think so? Well, the authors of this book suggest that you think again. They propose a computational turn, a turn towards computational explanation and towards the explanation of (...)
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  22. Representation in digital systems.Vincent C. Müller - 2008 - In Adam Briggle, Katinka Waelbers & Brey Philip (eds.), Current Issues in Computing and Philosophy. IOS Press. pp. 116-121.
    Cognition is commonly taken to be computational manipulation of representations. These representations are assumed to be digital, but it is not usually specified what that means and what relevance it has for the theory. I propose a specification for being a digital state in a digital system, especially a digital computational system. The specification shows that identification of digital states requires functional directedness, either for someone or for the system of which it is a part. In the case or digital (...)
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