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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. Deep Learning and Artificial Intelligence: X, XX, XXX.Ilexa Yardley - 2017 - Https://Medium.Com/the-Circular-Theory/.
  2. Strengthening Weak Emergence.Nora Berenstain - forthcoming - Erkenntnis:1-18.
    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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  3. 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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  4. Integrating Computation Into the Mechanistic Hierarchy in the Cognitive and Neural Sciences.Lotem Elber-Dorozko & Oron Shagrir - forthcoming - Synthese:1-24.
    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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  5. 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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  6. 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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Analog and Digital Computation
  1. Unrealistic Models for Realistic Computations: How Idealisations Help Represent Mathematical Structures and Found Scientific Computing.Philippos Papayannopoulos - forthcoming - Synthese:1-35.
    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 or \). Since typically the problems dealt with in physical sciences, applied mathematics, economics, and engineering are also defined in uncountable (...)
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  2. 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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  3. 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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  4. 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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  5. 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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  6. 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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  7. 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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  8. 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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  9. 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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  10. 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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  11. The Physical Church Thesis and Physical Computational Complexity.Itamar Pitowski - 1990 - Iyyun 39:81-99.
  12. 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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  13. 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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  14. 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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  15. Why Digital Pictures Are Not Notational Representations.John Zeimbekis - 2015 - Journal of Aesthetics and Art Criticism 73 (4):449-453.
  16. Some Recent Developments on Shannon's General Purpose Analog Computer.Daniel Silva Graça - 2004 - Mathematical Logic Quarterly 50 (45):473-485.
    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 (...)
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  17. Objective Computation Versus Subjective Computation.Nir Fresco - 2015 - Erkenntnis 80 (5):1031-1053.
    The question ‘What is computation?’ might seem a trivial one to many, but this is far from being in consensus in philosophy of mind, cognitive science and even in physics. The lack of consensus leads to some interesting, yet contentious, claims, such as that cognition or even the universe is computational. Some have argued, though, that computation is a subjective phenomenon: whether or not a physical system is computational, and if so, which computation it performs, is entirely a matter of (...)
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  18. Analog Computationalism and Psychophysical Reduction.Michael King - 1998 - Dissertation, The University of Arizona
    In this dissertation I seek to overthrow the most sacred dogma in the philosophy of mind: the doctrine that the mind is multiply realizable. Ever since Hilary Putnam introduced Turing machine functionalism, the idea that the mind is multiply realizable has gone unquestioned, and a form of the multiple realizability thesis now permeates the thinking of most functionalists. Nevertheless, I argue, this thesis is mistaken. And precisely because multiple realizability is the main obstacle of a psychophysical reduction of the mind, (...)
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  19. The Analog-Digital Distinction and the Flow of Information.Paul Jeremiah Bohan Broderick - 2001 - Dissertation, Boston University
    The analog vs. digital distinction is frequently used in computer science, computer technology and elsewhere. However, its precise nature is more elusive than might be expected. This dissertation defines a set of problems hidden within the conventions of ordinary and technical language, and suggests solutions to them. ;Chapter 1 examines ordinary language uses of the analog-digital distinction. Chapter 2 considers its use in technical contexts. There are two main ways of making the distinction that appear in both of the opening (...)
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  20. Varieties of Analog and Digital Representation.Whit Schonbein - 2014 - Minds and Machines 24 (4):415-438.
    The ‘received view’ of the analog–digital distinction holds that analog representations are continuous while digital representations are discrete. In this paper I first provide support for the received view by showing how it (1) emerges from the theory of computation, and (2) explains engineering practices. Second, I critically assess several recently offered alternatives, arguing that to the degree they are justified they demonstrate not that the received view is incorrect, but rather that distinct senses of the terms have become entrenched (...)
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  21. Structure and Dynamics in Implementation of Computations.Jacques Mallah - forthcoming - In Yasemin J. Erden (ed.), Proceedings of the 7th AISB Symposium on Computing and Philosophy:. AISB.
    Without a proper restriction on mappings, virtually any system could be seen as implementing any computation. That would not allow characterization of systems in terms of implemented computations and is not compatible with a computationalist philosophy of mind. Information-based criteria for independence of substates within structured states are proposed as a solution. Objections to the use of requirements for transitions in counterfactual states are addressed, in part using the partial-brain argument as a general counterargument to neural replacement arguments.
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  22. The World is Either Digital or Analogue.Francesco Berto & Jacopo Tagliabue - 2014 - Synthese 191 (3):481-497.
    We address an argument by Floridi (Synthese 168(1):151–178, 2009; 2011a), to the effect that digital and analogue are not features of reality, only of modes of presentation of reality. One can therefore have an informational ontology, like Floridi’s Informational Structural Realism, without commitment to a supposedly digital or analogue world. After introducing the topic in Sect. 1, in Sect. 2 we explain what the proposition expressed by the title of our paper means. In Sect. 3, we describe Floridi’s argument. In (...)
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  23. An Analog VLSI Chip for Low-Level Computer Vision.Kenneth J. Janik, Shih-Lien Lu & Ben Lee - 1996 - Esda 1996: Expert Systems and Ai; Neural Networks 7:211.
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  24. Chaotic Neurons and Analog Computation.Kazuyuki Aihara & Jun Kyung Ryeu - 2001 - Behavioral and Brain Sciences 24 (5):810-811.
    Chaotic dynamics can be related to analog computation. A possibility of electronically implementing the chaos -driven contracting system in the target article is explored with an analog electronic circuit with inevitable noise from the viewpoint of analog computation with chaotic neurons.
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  25. The Informational Model of Language: Analog and Digital Coding in Animal and Human Communication (an Excerpt).Thomas A. Sebeok - 1967 - In Donald C. Hildum (ed.), Language and Thought: An Enduring Problem in Psychology. London: : Van Nostrand,. pp. 37--40.
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  26. Digital Approaches.A. Pagni - 1998 - In Enrique H. Ruspini, Piero Patrone Bonissone & Witold Pedrycz (eds.), Handbook of Fuzzy Computation. Institute of Physics.
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  27. The Analog Divide.Torin Monahan - 2001 - Acm Sigcas Computers and Society 31 (3):22-31.
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  28. An Association Between Understanding Cardinality and Analog Magnitude Representations in Preschoolers.Jennifer B. Wagner & Susan C. Johnson - 2011 - Cognition 119 (1):10-22.
  29. The Role of Analog Models in Our Digital Age.Bela Julesz - 1983 - Behavioral and Brain Sciences 6 (4):668.
  30. The Processing of Information (Analog/Digital) is the Causal Factor of the Emergence of Natural Hierarchies.Eugenio Andrade - 2003 - Ludus Vitalis 11 (20):85-106.
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  31. Effects of Familiarity and Sequence Length of Analog Matches in the Simultaneous Matching Task.Gail A. Bruder & Wayne Silverman - 1974 - Journal of Experimental Psychology 102 (5):875.
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  32. The Instructional Information Processing Account of Digital Computation.Nir Fresco & Marty J. Wolf - 2014 - Synthese 191 (7):1469-1492.
    What is nontrivial digital computation? It is the processing of discrete data through discrete state transitions in accordance with finite instructional information. The motivation for our account is that many previous attempts to answer this question are inadequate, and also that this account accords with the common intuition that digital computation is a type of information processing. We use the notion of reachability in a graph to defend this characterization in memory-based systems and underscore the importance of instructional information for (...)
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  33. Analog Computation.Albert S. Jackson - 1960 - McGraw-Hill.
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  34. A History of Modern Computing.Paul E. Ceruzzi - 2003 - MIT Press.
    Ceruzzi pens a history of computing from the development of the first electronic digital computer to the Web and dot-com crash.
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  35. The History of Early Computer Switching.Arthur W. Burks & Alice R. Burks - 1988 - Grazer Philosophische Studien 32 (1):3-36.
    We distinguish scanning switches, which only enumerate states, from function switches which transform input states into output states. For the latter we introduce a logical network symbolism. Our history of early computer switching begins with the suggestions of Ramon Lull and Gottfried Leibniz, surveys the evolution of mechanical scanning switches and the first mechanical function switches, and then describes the first electromechanical function switches. The main themes of the present paper are that William S. Jevons built the first substantial function (...)
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  36. Information Processing as an Account of Concrete Digital Computation.Nir Fresco - 2013 - Philosophy and Technology 26 (1):31-60.
    It is common in cognitive science to equate computation (and in particular digital computation) with information processing. Yet, it is hard to find a comprehensive explicit account of concrete digital computation in information processing terms. An information processing account seems like a natural candidate to explain digital computation. But when ‘information’ comes under scrutiny, this account becomes a less obvious candidate. Four interpretations of information are examined here as the basis for an information processing account of digital computation, namely Shannon (...)
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  37. Digital Immortality: Self or 0010110?Liz Stillwaggon Swan & Joshua Howard - 2012 - International Journal of Machine Consciousness 4 (01):245-256.
  38. Cellular Automata.Francesco Berto & Jacopo Tagliabue - 2012 - Stanford Encyclopedia of Philosophy.
    Cellular automata (henceforth: CA) are discrete, abstract computational systems that have proved useful both as general models of complexity and as more specific representations of non-linear dynamics in a variety of scientific fields. Firstly, CA are (typically) spatially and temporally discrete: they are composed of a finite or denumerable set of homogeneous, simple units, the atoms or cells. At each time unit, the cells instantiate one of a finite set of states. They evolve in parallel at discrete time steps, following (...)
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  39. On the Possibilities of Hypercomputing Supertasks.Vincent C. Müller - 2011 - Minds and Machines 21 (1):83-96.
    This paper investigates the view that digital hypercomputing is a good reason for rejection or re-interpretation of the Church-Turing thesis. After suggestion that such re-interpretation is historically problematic and often involves attack on a straw man (the ‘maximality thesis’), it discusses proposals for digital hypercomputing with Zeno-machines , i.e. computing machines that compute an infinite number of computing steps in finite time, thus performing supertasks. It argues that effective computing with Zeno-machines falls into a dilemma: either they are specified such (...)
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  40. Analog Versus Digital: Extrapolating From Electronics to Neurobiology.Rahul Sarpeshkar - 1998 - Neural Computation 10 (7):1601--1638.
    We review the pros and cons of analog and digital computation. We propose that computation that is most efficient in its use of resources is neither analog computation nor digital computation but, rather, a mixture of the two forms. For maximum efficiency, the information and information-processing resources of the hybrid form must be distributed over many wires, with an optimal signal-to-noise ratio per wire. Our results suggest that it is likely that the brain computes in a hybrid fashion and that (...)
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  41. Languages of Art.Nelson Goodman - 1968 - Bobbs-Merrill.
    . . . Unlike Dewey, he has provided detailed incisive argumentation, and has shown just where the dogmas and dualisms break down." -- Richard Rorty, The Yale Review.
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  42. Analog and Digital, Continuous and Discrete.Corey J. Maley - 2011 - Philosophical Studies 155 (1):117-131.
    Representation is central to contemporary theorizing about the mind/brain. But the nature of representation--both in the mind/brain and more generally--is a source of ongoing controversy. One way of categorizing representational types is to distinguish between the analog and the digital: the received view is that analog representations vary smoothly, while digital representations vary in a step-wise manner. I argue that this characterization is inadequate to account for the ways in which representation is used in cognitive science; in its place, I (...)
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  43. Analog Vs. Digital Computation.David J. Chalmers - manuscript
    It is fairly well-known that certain hard computational problems (that is, 'difficult' problems for a digital processor to solve) can in fact be solved much more easily with an analog machine. This raises questions about the true nature of the distinction between analog and digital computation (if such a distinction exists). I try to analyze the source of the observed difference in terms of (1) expanding parallelism and (2) more generally, infinite-state Turing machines. The issue of discreteness vs continuity will (...)
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  44. On Effective Procedures.Carol E. Cleland - 2002 - Minds and Machines 12 (2):159-179.
    Since the mid-twentieth century, the concept of the Turing machine has dominated thought about effective procedures. This paper presents an alternative to Turing's analysis; it unifies, refines, and extends my earlier work on this topic. I show that Turing machines cannot live up to their billing as paragons of effective procedure; at best, they may be said to provide us with mere procedure schemas. I argue that the concept of an effective procedure crucially depends upon distinguishing procedures as definite courses (...)
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