About this topic
Summary A crucial problem in the philosophy of computing is represented by the nature of computation. On the one hand, a computation is thought of as some representation of a formal process composed by well-defined steps, which allows to reach in a finite amount of time a given output from a given input. This is tantamount to the formulation of a mathematical or biological function or the design of an algorithm. On the other hand, a computation is inherently bound to its execution and thus to an implementation. This strongly relates to the problem of determining which physical systems can be said to implement a computation, in turn which systems can be said to be properly computational. The answer to this question can be offered by reduction to other relations (such as causation), but it triggered a widespread debate on whether it implies that almost any physical system is then by definition computational. This has been a particularly intense debate in the cognitive sciences. The duality formal-physical that affects the nature of computation is also of especially great importance in the philosophical debate on the nature of algorithms and programs, where the latter are considered physical implementations of the former.
Key works The thesis that certain human abilities cannot be considered implementation of computations is notoriously held by Dreyfus 1972 and Putnam 1987. This argument is even stronger in Searle 1980, where it is argued that even the interpretation of human abilites as implementation of computations is not enough for the mind. The thesis that a physical system implements a computation if the causal structure of the former reflects the formal structure of the latter is defended in Chalmers 1994. See also Piccinini 2007. A starting point for the  debate on the nature of algorithms is represented by Moschovakis 2001 and Gurevich 2012. Fetzer 1988 offers the very first critique of program verification in view of the formal-physical divide, with a large debate following.
Introductions See Piccinini 2010 for an overview of the notion of computation in physical systems, including an assessment of varieties of the physical Church-Turing thesis. 
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  1. added 2019-01-05
    Morphological Computation: Nothing but Physical Computation.Marcin Miłkowski - 2018 - Entropy 10 (20):942.
    The purpose of this paper is to argue against the claim that morphological computation is substantially different from other kinds of physical computation. I show that some (but not all) purported cases of morphological computation do not count as specifically computational, and that those that do are solely physical computational systems. These latter cases are not, however, specific enough: all computational systems, not only morphological ones, may (and sometimes should) be studied in various ways, including their energy efficiency, cost, reliability, (...)
  2. added 2018-10-22
    How to Explain Miscomputation.Chris Tucker - 2018 - Philosophers' Imprint 18 (24):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 (...)
  3. added 2018-10-04
    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. London: 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 (...)
  4. added 2018-08-20
    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 (...)
  5. added 2018-03-05
    Physical Perspectives on Computation, Computational Perspectives on Physics.Michael E. Cuffaro & Samuel C. Fletcher (eds.) - 2018 - Cambridge University Press.
    Although computation and the science of physical systems would appear to be unrelated, there are a number of ways in which computational and physical concepts can be brought together in ways that illuminate both. This volume examines fundamental questions which connect scholars from both disciplines: is the universe a computer? Can a universal computing machine simulate every physical process? What is the source of the computational power of quantum computers? Are computational approaches to solving physical problems and paradoxes always fruitful? (...)
  6. added 2018-01-25
    A Mechanistic Account of Wide Computationalism.Luke Kersten - 2017 - Review of Philosophy and Psychology 8 (3):501-517.
    The assumption that psychological states and processes are computational in character pervades much of cognitive science, what many call the computational theory of mind. In addition to occupying a central place in cognitive science, the computational theory of mind has also had a second life supporting “individualism”, the view that psychological states should be taxonomized so as to supervene only on the intrinsic, physical properties of individuals. One response to individualism has been to raise the prospect of “wide computational systems”, (...)
  7. added 2018-01-18
    Mechanisms in Cognitive Science.Carlos Zednik - 2017 - In Phyllis McKay Illari & Stuart Glennan (eds.), The Routledge Handbook of Mechanisms and Mechanical Philosophy. London: Routledge. pp. 389-400.
    This chapter subsumes David Marr’s levels of analysis account of explanation in cognitive science under the framework of mechanistic explanation: Answering the questions that define each one of Marr’s three levels is tantamount to describing the component parts and operations of mechanisms, as well as their organization, behavior, and environmental context. By explicating these questions and showing how they are answered in several different cognitive science research programs, this chapter resolves some of the ambiguities that remain in Marr’s account, and (...)
  8. added 2017-11-05
    Book Review: Jeff Buechner, Gödel, Putnam, and Functionalism: A New Reading of Representation and Reality. [REVIEW]Witold M. Hensel & Marcin Miłkowski - 2014 - Journal of Cognitive Science 15 (3):391-402.
  9. added 2017-11-04
    The False Dichotomy Between Causal Realization and Semantic Computation.Marcin Miłkowski - 2017 - Hybris. Internetowy Magazyn Filozoficzny 38:1-21.
    In this paper, I show how semantic factors constrain the understanding of the computational phenomena to be explained so that they help build better mechanistic models. In particular, understanding what cognitive systems may refer to is important in building better models of cognitive processes. For that purpose, a recent study of some phenomena in rats that are capable of ‘entertaining’ future paths (Pfeiffer and Foster 2013) is analyzed. The case shows that the mechanistic account of physical computation may be complemented (...)
  10. added 2017-05-31
    Many-Valued Logics. A Mathematical and Computational Introduction.Luis M. Augusto - 2017 - London: College Publications.
    Many-valued logics are those logics that have more than the two classical truth values, to wit, true and false; in fact, they can have from three to infinitely many truth values. This property, together with truth-functionality, provides a powerful formalism to reason in settings where classical logic—as well as other non-classical logics—is of no avail. Indeed, originally motivated by philosophical concerns, these logics soon proved relevant for a plethora of applications ranging from switching theory to cognitive modeling, and they are (...)
  11. added 2017-05-06
    A Simplicity Criterion for Physical Computation.Tyler Millhouse - forthcoming - British Journal for the Philosophy of Science:axx046.
    The aim of this paper is to offer a formal criterion for physical computation that allows us to objectively distinguish between competing computational interpretations of a physical system. The criterion construes a computational interpretation as an ordered pair of functions mapping (1) states of a physical system to states of an abstract machine, and (2) inputs to this machine to interventions in this physical system. This interpretation must ensure that counterfactuals true of the abstract machine have appropriate counterparts which are (...)
  12. added 2017-04-25
    Against Structuralist Theories of Computational Implementation.Michael Rescorla - 2013 - British Journal for the Philosophy of Science 64 (4):681-707.
    Under what conditions does a physical system implement or realize a computation? Structuralism about computational implementation, espoused by Chalmers and others, holds that a physical system realizes a computation just in case the system instantiates a pattern of causal organization isomorphic to the computation’s formal structure. I argue against structuralism through counter-examples drawn from computer science. On my opposing view, computational implementation sometimes requires instantiating semantic properties that outstrip any relevant pattern of causal organization. In developing my argument, I defend (...)
  13. added 2017-04-25
    Resolving Arguments by Different Conceptual Traditions of Realization.Ronald P. Endicott - 2012 - Philosophical Studies 159 (1):41-59.
    There is currently a significant amount of interest in understanding and developing theories of realization. Naturally arguments have arisen about the adequacy of some theories over others. Many of these arguments have a point. But some can be resolved by seeing that the theories of realization in question are not genuine competitors because they fall under different conceptual traditions with different but compatible goals. I will first describe three different conceptual traditions of realization that are implicated by the arguments under (...)
  14. added 2017-04-25
    Realization for Causal Nondeterministic Input-Output Systems.Norman Y. Foo & Pavlos Peppas - 2001 - Studia Logica 67 (3):419-437.
    There are two well-developed formalizations of discrete time dynamic systems that evidently share many concerns but suffer from a lack of mutual awareness. One formalization is classical systems and automata theory. The other is the logic of actions in which the situation and event calculi are the strongest representatives. Researchers in artificial intelligence are likely to be familiar with the latter but not the former. This is unfortunate, for systems and automata theory have much to offer by way of insight (...)
  15. added 2017-04-25
    Computational Commitment and Physical Realization.Robert M. Harrish - 1983 - Behavioral and Brain Sciences 6 (3):408.
  16. added 2017-04-25
    A New Lilliputian Argument Against Machine Functionalism.William G. Lycan - 1979 - Philosophical Studies 35 (April):279-87.
  17. added 2017-03-17
    Individuation Without Representation.Joe Dewhurst - 2016 - British Journal for the Philosophy of Science:axw018.
    Shagrir (2001) and Sprevak (2010) explore the apparent necessity of representation for the individuation of digits (and processors) in computational systems. I will first offer a response to Sprevak’s argument that does not mention Shagrir’s original formulation, which was more complex. I then extend my initial response to cover Shagrir’s argument, thus demonstrating that it is possible to individuate digits in non-representational computing mechanisms. I also consider the implications that the non-representational individuation of digits would have for the broader theory (...)
  18. added 2017-02-13
    Effective Procedures Versus Elementary Units of Behavior.John M. Hollerbach - 1981 - Behavioral and Brain Sciences 4 (4):625.
  19. added 2017-01-26
    Effective Blood Volume: An Effective Concept or a Modern Myth.Alastair Michell - 1996 - Perspectives in Biology and Medicine 39 (4):471-490.
  20. added 2017-01-24
    Understanding the Implementation of a Complex Intervention Aiming to Change a Health Professional Role: A Conceptual Framework for Implementation Evaluation.Abou-Malham Sabina, Hatem Marie & Leduc Nicole - 2013 - Open Journal of Philosophy 3 (4):491.
    This paper proposes a conceptual framework for understanding the implementation process of a complex intervention concerned with professional role change. The proposed framework holds that the intervention must address three interacting systems (socio-cultural, educational and disciplinary) through which a health professional role is evolved. Each system is operationalized by four dimensions (values, methods, actors and targets). As for the implementation, the framework posits that it can be analyzed, by depicting the barriers and facilitators located within the dimensions of the three (...)
  21. added 2017-01-23
    Implementation of Self-Managed Teams in Manufacturing: More of a Marathon Than a Sprint. [REVIEW]John R. Wilson & Claire M. Whittington - 2001 - AI and Society 15 (1-2):58-81.
    During the past decade teamwork in manufacturing, as in other sectors, has become the organisational form of choice. In contrast to earlier manifestations such as autonomous workgroups some 30 years earlier, this appears to have been largely for business and production reasons rather than being directly aimed at improving the quality of work life. Taken from part of a larger study of teamworking in several different manufacturing companies this paper draws upon a retrospective analysis of cases of self-managed team implementation (...)
  22. added 2017-01-23
    Globalisation and Local Innovation System: The Implementation of Government Policies to the Formation of Science Parks in Japan. [REVIEW]Sang-Chul Park - 2001 - AI and Society 15 (3):263-279.
  23. added 2017-01-14
    Implementation of a Group-Based Physical Activity Programme for Ageing Adults with ID: A Process Evaluation.Marieke van Schijndel-Speet, Heleen M. Evenhuis, Ruud van Wijck & Michael A. Echteld - 2014 - Journal of Evaluation in Clinical Practice 20 (4):401-407.
  24. added 2016-12-08
    Do Accelerating Turing Machines Compute the Uncomputable?B. Jack Copeland & Oron Shagrir - 2011 - Minds and Machines 21 (2):221-239.
  25. added 2016-12-08
    Effective Computation by Humans and Machines.Shagrir Oron - 2002 - Minds and Machines 12 (2):221-240.
    There is an intensive discussion nowadays about the meaning of effective computability, with implications to the status and provability of the Church–Turing Thesis (CTT). I begin by reviewing what has become the dominant account of the way Turing and Church viewed, in 1936, effective computability. According to this account, to which I refer as the Gandy–Sieg account, Turing and Church aimed to characterize the functions that can be computed by a human computer. In addition, Turing provided a highly convincing argument (...)
  26. added 2016-10-11
    A Cognitive Computation Fallacy? Cognition, Computations and Panpsychism.John Mark Bishop - 2009 - Cognitive Computation 1 (3):221-233.
    The journal of Cognitive Computation is defined in part by the notion that biologically inspired computational accounts are at the heart of cognitive processes in both natural and artificial systems. Many studies of various important aspects of cognition (memory, observational learning, decision making, reward prediction learning, attention control, etc.) have been made by modelling the various experimental results using ever-more sophisticated computer programs. In this manner progressive inroads have been made into gaining a better understanding of the many components of (...)
  27. added 2016-10-11
    Why Computers Can't Feel Pain.John Mark Bishop - 2009 - Minds and Machines 19 (4):507-516.
    The most cursory examination of the history of artificial intelligence highlights numerous egregious claims of its researchers, especially in relation to a populist form of ‘strong’ computationalism which holds that any suitably programmed computer instantiates genuine conscious mental states purely in virtue of carrying out a specific series of computations. The argument presented herein is a simple development of that originally presented in Putnam’s (Representation & Reality, Bradford Books, Cambridge in 1988 ) monograph, “Representation & Reality”, which if correct, has (...)
  28. added 2016-10-11
    Dancing with Pixies: Strong Artificial Intelligence and Panpsychism.J. M. Bishop - 2002 - In John Preston & John Mark Bishop (eds.), Views into the Chinese Room: New Essays on Searle and Artificial Intelligence. pp. 360-379.
    The argument presented in this paper is not a direct attack or defence of the Chinese Room Argument (CRA), but relates to the premise at its heart, that syntax is not sufficient for semantics, via the closely associated propositions that semantics is not intrinsic to syntax and that syntax is not intrinsic to physics. However, in contrast to the CRA’s critique of the link between syntax and semantics, this paper will explore the associated link between syntax and physics. The main (...)
  29. added 2016-10-11
    Counterfactuals Cannot Count: A Rejoinder to David Chalmers.John Mark Bishop - 2002 - Consciousness and Cognition 11 (4):642-652.
    The initial argument presented herein is not significantly original—it is a simple reflection upon a notion of computation originally developed by Putnam and criticised by Chalmers et al. . In what follows, instead of seeking to justify Putnam’s conclusion that every open system implements every Finite State Automaton and hence that psychological states of the brain cannot be functional states of a computer, I will establish the weaker result that, over a finite time window every open system implements the trace (...)
  30. added 2016-07-12
    Computational Mechanisms and Models of Computation.Marcin Miłkowski - 2014 - Philosophia Scientae 18:215-228.
    In most accounts of realization of computational processes by physical mechanisms, it is presupposed that there is one-to-one correspondence between the causally active states of the physical process and the states of the computation. Yet such proposals either stipulate that only one model of computation is implemented, or they do not reflect upon the variety of models that could be implemented physically. In this paper, I claim that mechanistic accounts of computation should allow for a broad variation of models of (...)
  31. added 2016-06-30
    System, Subsystem, Hive: Boundary Problems in Computational Theories of Consciousness.Tomer Fekete, Cees van Leeuwen & Shimon Edelman - 2016 - Frontiers in Psychology 7.
    A computational theory of consciousness should include a quantitative measure of consciousness, or MoC, that (i) would reveal to what extent a given system is conscious, (ii) would make it possible to compare not only different systems, but also the same system at different times, and (iii) would be graded, because so is consciousness. However, unless its design is properly constrained, such an MoC gives rise to what we call the boundary problem: an MoC that labels a system as conscious (...)
  32. added 2016-06-10
    A Mechanistic Account of Computational Explanation in Cognitive Science and Computational Neuroscience.Marcin Miłkowski - 2016 - In Vincent C. Müller (ed.), Computing and Philosophy. Springer. pp. 191-205.
    Explanations in cognitive science and computational neuroscience rely predominantly on computational modeling. Although the scientific practice is systematic, and there is little doubt about the empirical value of numerous models, the methodological account of computational explanation is not up-to-date. The current chapter offers a systematic account of computational explanation in cognitive science and computational neuroscience within a mechanistic framework. The account is illustrated with a short case study of modeling of the mirror neuron system in terms of predictive coding.
  33. added 2016-04-20
    You Can't Eat Causal Cake with an Abstract Fork: An Argument Against Computational Theories of Consciousness.Matthew Stuart Piper - 2012 - Journal of Consciousness Studies 19 (11-12):154-90.
    Two of the most important concepts in contemporary philosophy of mind are computation and consciousness. This paper explores whether there is a strong relationship between these concepts in the following sense: is a computational theory of consciousness possible? That is, is the right kind of computation sufficient for the instantiation of consciousness. In this paper, I argue that the abstract nature of computational processes precludes computations from instantiating the concrete properties constitutive of consciousness. If this is correct, then not only (...)
  34. added 2016-03-11
    Why Build a Virtual Brain? Large-Scale Neural Simulations as Jump Start for Cognitive Computing.Matteo Colombo - 2016 - Journal of Experimental and Theoretical Artificial Intelligence.
    Despite the impressive amount of financial resources recently invested in carrying out large-scale brain simulations, it is controversial what the pay-offs are of pursuing this project. One idea is that from designing, building, and running a large-scale neural simulation, scientists acquire knowledge about the computational performance of the simulating system, rather than about the neurobiological system represented in the simulation. It has been claimed that this knowledge may usher in a new era of neuromorphic, cognitive computing systems. This study elucidates (...)
  35. added 2016-03-11
    Deep and Beautiful. The Reward Prediction Error Hypothesis of Dopamine.Matteo Colombo - 2014 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 45 (1):57-67.
    According to the reward-prediction error hypothesis of dopamine, the phasic activity of dopaminergic neurons in the midbrain signals a discrepancy between the predicted and currently experienced reward of a particular event. It can be claimed that this hypothesis is deep, elegant and beautiful, representing one of the largest successes of computational neuroscience. This paper examines this claim, making two contributions to existing literature. First, it draws a comprehensive historical account of the main steps that led to the formulation and subsequent (...)
  36. added 2016-01-31
    20 Years After The Embodied Mind - Why is Cognitivism Alive and Kicking?Vincent C. Müller - 2013 - In Blay Whitby & Joel Parthmore (eds.), Re-Conceptualizing Mental "Illness": The View from Enactivist Philosophy and Cognitive Science - AISB Convention 2013. AISB. pp. 47-49.
    I want to suggest that the major influence of classical arguments for embodiment like "The Embodied Mind" by Varela, Thomson & Rosch (1991) has been a changing of positions rather than a refutation: Cognitivism has found ways to retreat and regroup at positions that have better fortification, especially when it concerns theses about artificial intelligence or artificial cognitive systems. For example: a) Agent-based cognitivism' that understands humans as taking in representations of the world, doing rule-based processing and then acting on (...)
  37. added 2016-01-31
    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 (...)
  38. added 2016-01-16
    Opinions and Outlooks on Morphological Computation.Helmut Hauser, Rudolf M. Füchslin & Rolf Pfeifer (eds.) - 2014 - E-Book.
    Morphological Computation is based on the observation that biological systems seem to carry out relevant computations with their morphology (physical body) in order to successfully interact with their environments. This can be observed in a whole range of systems and at many different scales. It has been studied in animals – e.g., while running, the functionality of coping with impact and slight unevenness in the ground is "delivered" by the shape of the legs and the damped elasticity of the muscle-tendon (...)
  39. added 2016-01-06
    The Transfer of Functions From Man To Machine.R. Caussin & W. F. Chamberlin - 1959 - Diogenes 7 (28):107-125.
  40. added 2016-01-05
    A Review of the LSAT Using Literature on Legal Reasoning.Gilbert E. Plumer - 2000 - Law School Admission Council Computerized Testing Report 97 (8):1-19.
    Research using current literature on legal reasoning was conducted with the goals of (a) determining what skills are most important in good legal reasoning according to such literature, (b) determining the extent to which existing Law School Admission Test item types and subtypes are designed to assess those skills, and (c) suggesting test specifications or new or refined item types and formats that could be developed in the future to assess any important skills that appear [by (a) and (b)] to (...)
  41. added 2015-11-17
    Laplace's Demon Consults an Oracle: The Computational Complexity of Prediction.I. Pitowsky - 1996 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 27 (2):161-180.
  42. added 2015-10-12
    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 (...)
  43. added 2015-06-23
    Programming the Emergence in Morphogenetically Architected Complex Systems.Franck Varenne, Pierre Chaigneau, Jean Petitot & René Doursat - 2015 - Acta Biotheoretica 63 (3):295-308.
    Large sets of elements interacting locally and producing specific architectures reliably form a category that transcends the usual dividing line between biological and engineered systems. We propose to call them morphogenetically architected complex systems (MACS). While taking the emergence of properties seriously, the notion of MACS enables at the same time the design (or “meta-design”) of operational means that allow controlling and even, paradoxically, programming this emergence. To demonstrate our claim, we first show that among all the self-organized systems studied (...)
  44. added 2015-04-09
    Computational Mechanisms and Models of Computation.Marcin Miłkowski - 2014 - Philosophia Scientiæ 18:215-228.
    In most accounts of realization of computational processes by physical mechanisms, it is presupposed that there is one-to-one correspondence between the causally active states of the physical process and the states of the computation. Yet such proposals either stipulate that only one model of computation is implemented, or they do not reflect upon the variety of models that could be implemented physically. -/- In this paper, I claim that mechanistic accounts of computation should allow for a broad variation of models (...)
  45. added 2015-04-04
    The Missing Link: Implementation and Realization of Computations in Computer and Cognitive Science.Matthias Josef Scheutz - 1999 - Dissertation, Indiana University
    The notion of computation has attracted researchers from a wide range of areas, cognitive psychology being one of them. The analogy underlying the usage of "computer" in cognitive psychology can be succinctly summarized by saying that the mind is to the brain as the program is to the hardware. Two main assumptions are buried in this analogy: that the mind can somehow be understood computationally, and that the same kind of relation-the implementation relation-that obtains between programs and computer hardware obtains (...)
  46. added 2015-03-24
    Chalmers on Implementation and Computational Sufficiency.J. Brendan Ritchie - unknown
    Chalmers argues for the following two principles: computational sufficiency and computational explanation. In this commentary I present two criticisms of Chalmers’ argument for the principle of computational sufficiency, which states that implementing the appropriate kind of computational structure suffices for possessing mentality. First, Chalmers only establishes that a system has its mental properties in virtue of the computations it performs in the trivial sense that any physical system can be described computationally to some arbitrary level of detail; further argumentation is (...)
  47. added 2015-03-23
    Implementation: Closing the Gap.Anne Pascasio - 1968 - In Peter Koestenbaum (ed.), Proceedings. [San Jose? Calif.. pp. 13--97.
  48. added 2015-03-19
    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 (...)
  49. added 2015-03-18
    Concepts and Recipes.Pavel Materna - 2009 - Acta Analytica 24 (1):69-90.
    If concepts are explicated as abstract procedures, then we can easily show that each empirical concept is a not an effective procedure. Some, but not all empirical concepts are shown to be of a special kind: they cannot in principle guarantee that the object they identify satisfies the intended conditions.
  50. added 2015-03-17
    The Scope of Turing's Analysis of Effective Procedures.Jeremy Seligman - 2002 - Minds and Machines 12 (2):203-220.
    Turing's (1936) analysis of effective symbolic procedures is a model of conceptual clarity that plays an essential role in the philosophy of mathematics. Yet appeal is often made to the effectiveness of human procedures in other areas of philosophy. This paper addresses the question of whether Turing's analysis can be applied to a broader class of effective human procedures. We use Sieg's (1994) presentation of Turing's Thesis to argue against Cleland's (1995) objections to Turing machines and we evaluate her proposal (...)
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