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  1. 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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  • On Algorithms, Effective Procedures, and Their Definitions.Philippos Papayannopoulos - 2023 - Philosophia Mathematica 31 (3):291-329.
    I examine the classical idea of ‘algorithm’ as a sequential, step-by-step, deterministic procedure (i.e., the idea of ‘algorithm’ that was already in use by the 1930s), with respect to three themes, its relation to the notion of an ‘effective procedure’, its different roles and uses in logic, computer science, and mathematics (focused on numerical analysis), and its different formal definitions proposed by practitioners in these areas. I argue that ‘algorithm’ has been conceptualized and used in contrasting ways in the above (...)
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  • Descriptive Complexity, Computational Tractability, and the Logical and Cognitive Foundations of Mathematics.Markus Pantsar - 2020 - Minds and Machines 31 (1):75-98.
    In computational complexity theory, decision problems are divided into complexity classes based on the amount of computational resources it takes for algorithms to solve them. In theoretical computer science, it is commonly accepted that only functions for solving problems in the complexity class P, solvable by a deterministic Turing machine in polynomial time, are considered to be tractable. In cognitive science and philosophy, this tractability result has been used to argue that only functions in P can feasibly work as computational (...)
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  • Cognitive and Computational Complexity: Considerations from Mathematical Problem Solving.Markus Pantsar - 2019 - Erkenntnis 86 (4):961-997.
    Following Marr’s famous three-level distinction between explanations in cognitive science, it is often accepted that focus on modeling cognitive tasks should be on the computational level rather than the algorithmic level. When it comes to mathematical problem solving, this approach suggests that the complexity of the task of solving a problem can be characterized by the computational complexity of that problem. In this paper, I argue that human cognizers use heuristic and didactic tools and thus engage in cognitive processes that (...)
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  • 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 (...)
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  • The diagonal method and hypercomputation.Toby Ord & Tien D. Kieu - 2005 - British Journal for the Philosophy of Science 56 (1):147-156.
    The diagonal method is often used to show that Turing machines cannot solve their own halting problem. There have been several recent attempts to show that this method also exposes either contradiction or arbitrariness in other theoretical models of computation which claim to be able to solve the halting problem for Turing machines. We show that such arguments are flawed—a contradiction only occurs if a type of machine can compute its own diagonal function. We then demonstrate why such a situation (...)
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  • The Ricean Objection: An Analogue of Rice's Theorem for First-order Theories.Igor Oliveira & Walter Carnielli - 2008 - Logic Journal of the IGPL 16 (6):585-590.
    We propose here an extension of Rice's Theorem to first-order logic, proven by totally elementary means. If P is any property defined over the collection of all first-order theories and P is non-trivial over the set of finitely axiomatizable theories , then P is undecidable. This not only means that the problem of deciding properties of first-order theories is as hard as the problem of deciding properties about languages accepted by Turing machines, but also offers a general setting for proving (...)
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  • Arrow’s impossibility theorem as a special case of Nash equilibrium: a cognitive approach to the theory of collective decision-making.Andrea Oliva & Edgardo Bucciarelli - 2020 - Mind and Society 19 (1):15-41.
    Metalogic is an open-ended cognitive, formal methodology pertaining to semantics and information processing. The language that mathematizes metalogic is known as metalanguage and deals with metafunctions purely by extension on patterns. A metalogical process involves an effective enrichment in knowledge as logical statements, and, since human cognition is an inherently logic–based representation of knowledge, a metalogical process will always be aimed at developing the scope of cognition by exploring possible cognitive implications reflected on successive levels of abstraction. Indeed, it is (...)
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  • Imitation Game: Threshold or Watershed?Eric Neufeld & Sonje Finnestad - 2020 - Minds and Machines 30 (4):637-657.
    Showing remarkable insight into the relationship between language and thought, Alan Turing in 1950 proposed the Imitation Game as a proxy for the question “Can machines think?” and its meaning and practicality have been debated hotly ever since. The Imitation Game has come under criticism within the Computer Science and Artificial Intelligence communities with leading scientists proposing alternatives, revisions, or even that the Game be abandoned entirely. Yet Turing’s imagined conversational fragments between human and machine are rich with complex instances (...)
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  • The notion of computation is fundamental to an autonomous neuroscience.Garrett Neske - 2010 - Complexity 16 (1):10-19.
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  • Feminist Philosophy of Science.Lynn Hankinson Nelson - 2002 - In Peter Machamer & Michael Silberstein (eds.), The Blackwell Guide to the Philosophy of Science. Oxford, UK: Blackwell. pp. 312–331.
    This chapter contains sections titled: Highlights of Past Literature Current Work Future Work.
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  • Connections among connections.R. J. Nelson - 1988 - Behavioral and Brain Sciences 11 (1):45-46.
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  • Practical Intractability: A Critique of the Hypercomputation Movement. [REVIEW]Aran Nayebi - 2014 - Minds and Machines 24 (3):275-305.
    For over a decade, the hypercomputation movement has produced computational models that in theory solve the algorithmically unsolvable, but they are not physically realizable according to currently accepted physical theories. While opponents to the hypercomputation movement provide arguments against the physical realizability of specific models in order to demonstrate this, these arguments lack the generality to be a satisfactory justification against the construction of any information-processing machine that computes beyond the universal Turing machine. To this end, I present a more (...)
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  • Machine intelligence: a chimera.Mihai Nadin - 2019 - AI and Society 34 (2):215-242.
    The notion of computation has changed the world more than any previous expressions of knowledge. However, as know-how in its particular algorithmic embodiment, computation is closed to meaning. Therefore, computer-based data processing can only mimic life’s creative aspects, without being creative itself. AI’s current record of accomplishments shows that it automates tasks associated with intelligence, without being intelligent itself. Mistaking the abstract for the concrete has led to the religion of “everything is an output of computation”—even the humankind that conceived (...)
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  • Recursive Functions and Metamathematics: Problems of Completeness and Decidability, Gödel's Theorems.Rod J. L. Adams & Roman Murawski - 1999 - Dordrecht, Netherland: Springer Verlag.
    Traces the development of recursive functions from their origins in the late nineteenth century to the mid-1930s, with particular emphasis on the work and influence of Kurt Gödel.
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  • Paper machines.Daniele Mundici & Wilfried Seig - 1995 - Philosophia Mathematica 3 (1):5-30.
    Machines were introduced as calculating devices to simulate operations carried out by human computers following fixed algorithms. The mathematical study of (paper) machines is the topic of our essay. The first three sections provide necessary logical background, examine the analyses of effective calculability given in the thirties, and describe results that are central to recursion theory, reinforcing the conceptual analyses. In the final section we pursue our investigation in a quite different way and focus on principles that govern the operations (...)
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  • ¿Qué es un algoritmo? Una respuesta desde la obra de Wittgenstein.Sergio Mota - 2015 - Endoxa 36:317.
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  • La historia y la gramática de la recursión: una precisión desde la obra de Wittgenstein.Sergio Mota - 2014 - Pensamiento y Cultura 17 (1):20-48.
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  • Semantic bounds for everyday language.Marcin Mostowski & Jakub Szymanik - 2012 - Semiotica 2012 (188):363-372.
    We consider the notion of everyday language. We claim that everyday language is semantically bounded by the properties expressible in the existential fragment of second–order logic. Two arguments for this thesis are formulated. Firstly, we show that so–called Barwise's test of negation normality works properly only when assuming our main thesis. Secondly, we discuss the argument from practical computability for finite universes. Everyday language sentences are directly or indirectly verifiable. We show that in both cases they are bounded by second–order (...)
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  • Artificial intelligence and symbols.Chris Moss - 1989 - AI and Society 3 (4):345-356.
    The introduction of massive parallelism and the renewed interest in neural networks gives a new need to evaluate the relationship of symbolic processing and artificial intelligence. The physical symbol hypothesis has encountered many difficulties coping with human concepts and common sense. Expert systems are showing more promise for the early stages of learning than for real expertise. There is a need to evaluate more fully the inherent limitations of symbol systems and the potential for programming compared with training. This can (...)
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  • Towards a Cognitive Neuroscience of Intentionality.Alex Morgan & Gualtiero Piccinini - 2018 - Minds and Machines 28 (1):119-139.
    We situate the debate on intentionality within the rise of cognitive neuroscience and argue that cognitive neuroscience can explain intentionality. We discuss the explanatory significance of ascribing intentionality to representations. At first, we focus on views that attempt to render such ascriptions naturalistic by construing them in a deflationary or merely pragmatic way. We then contrast these views with staunchly realist views that attempt to naturalize intentionality by developing theories of content for representations in terms of information and biological function. (...)
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  • On Equational Completeness Theorems.Tommaso Moraschini - 2022 - Journal of Symbolic Logic 87 (4):1522-1575.
    A logic is said to admit an equational completeness theorem when it can be interpreted into the equational consequence relative to some class of algebras. We characterize logics admitting an equational completeness theorem that are either locally tabular or have some tautology. In particular, it is shown that a protoalgebraic logic admits an equational completeness theorem precisely when it has two distinct logically equivalent formulas. While the problem of determining whether a logic admits an equational completeness theorem is shown to (...)
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  • In defence of neurons.Chris Mortensen - 1988 - Behavioral and Brain Sciences 11 (1):44-45.
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  • Against neuroclassicism: On the perils of armchair neuroscience.Alex Morgan - 2022 - Mind and Language 37 (3):329-355.
    Neuroclassicism is the view that cognition is explained by “classical” computing mechanisms in the nervous system that exhibit a clear demarcation between processing machinery and read–write memory. The psychologist C. R. Gallistel has mounted a sophisticated defense of neuroclassicism by drawing from ethology and computability theory to argue that animal brains necessarily contain read–write memory mechanisms. This argument threatens to undermine the “connectionist” orthodoxy in contemporary neuroscience, which does not seem to recognize any such mechanisms. In this paper I argue (...)
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  • Artificial Abduction: A Cumulative Evolutionary Process.Artemis Moroni, Jônatas Manzolli & Fernando J. Von Zuben - 2005 - Semiotica 2005 (153 - 1/4):343-362.
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  • Criteria of cognitive impenetrability.Robert C. Moore - 1980 - Behavioral and Brain Sciences 3 (1):146-147.
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  • Computational psychiatry.P. Read Montague, Raymond J. Dolan, Karl J. Friston & Peter Dayan - 2012 - Trends in Cognitive Sciences 16 (1):72-80.
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  • Closing the Circle: An Analysis of Emil Post's Early Work.Liesbeth De Mol - 2006 - Bulletin of Symbolic Logic 12 (2):267 - 289.
    In 1931 Kurt Gödel published his incompleteness results, and some years later Church and Turing showed that the decision problem for certain systems of symbolic logic has a negative solution. However, already in 1921 the young logician Emil Post worked on similar problems which resulted in what he called an "anticipation" of these results. For several reasons though he did not submit these results to a journal until 1941. This failure 'to be the first', did not discourage him: his contributions (...)
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  • 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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  • Virtual Machines and Real Implementations.Tyler Millhouse - 2018 - Minds and Machines 28 (3):465-489.
    What does it take to implement a computer? Answers to this question have often focused on what it takes for a physical system to implement an abstract machine. As Joslin observes, this approach neglects cases of software implementation—cases where one machine implements another by running a program. These cases, Joslin argues, highlight serious problems for mapping accounts of computer implementation—accounts that require a mapping between elements of a physical system and elements of an abstract machine. The source of these problems (...)
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  • Cognitive penetrability: let us not forget about memory.James R. Miller - 1980 - Behavioral and Brain Sciences 3 (1):146-146.
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  • Computation, consciousness and cognition.George A. Miller - 1980 - Behavioral and Brain Sciences 3 (1):146-146.
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  • Philosophical Problems of Multi-Agent Systems Modeling.I. F. Mikhailov - 2019 - Russian Journal of Philosophical Sciences 12:56-74.
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  • From Computer Metaphor to Computational Modeling: The Evolution of Computationalism.Marcin Miłkowski - 2018 - Minds and Machines 28 (3):515-541.
    In this paper, I argue that computationalism is a progressive research tradition. Its metaphysical assumptions are that nervous systems are computational, and that information processing is necessary for cognition to occur. First, the primary reasons why information processing should explain cognition are reviewed. Then I argue that early formulations of these reasons are outdated. However, by relying on the mechanistic account of physical computation, they can be recast in a compelling way. Next, I contrast two computational models of working memory (...)
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  • Searle's abstract argument against strong AI.Andrew Melnyk - 1996 - Synthese 108 (3):391-419.
    Discussion of Searle's case against strong AI has usually focused upon his Chinese Room thought-experiment. In this paper, however, I expound and then try to refute what I call his abstract argument against strong AI, an argument which turns upon quite general considerations concerning programs, syntax, and semantics, and which seems not to depend on intuitions about the Chinese Room. I claim that this argument fails, since it assumes one particular account of what a program is. I suggest an alternative (...)
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  • Computably Isometric Spaces.Alexander G. Melnikov - 2013 - Journal of Symbolic Logic 78 (4):1055-1085.
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  • Epistemological challenges for connectionism.John McCarthy - 1988 - Behavioral and Brain Sciences 11 (1):44-44.
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  • Would Leibniz have shared von Neumann's logical physicalism?Witold Marciszewski - 1995 - Logic and Logical Philosophy 3:115-128.
    This paper represents such an amateur approach; hence any comments backed up by professional erudition will be highly appreciated. Let me start from an attempt to sketch a relationship between professionals’ and amateurs’ contributions. The latter may be compared with the letters to the Editor of a journal, written by perceptive readers, while professionals contribute to the very content of the journal in question. Owing to such letters, the Editor and his professional staff can become more aware of the responses (...)
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  • Radical anti-realism, Wittgenstein and the length of proofs.Mathieu Marion - 2009 - Synthese 171 (3):419 - 432.
    After sketching an argument for radical anti-realism that does not appeal to human limitations but polynomial-time computability in its definition of feasibility, I revisit an argument by Wittgenstein on the surveyability of proofs, and then examine the consequences of its application to the notion of canonical proof in contemporary proof-theoretical-semantics.
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  • Does Science Progress Towards Ever Higher Solvability Through Feedbacks Between Insights and Routines?Witold Marciszewski - 2018 - Studia Semiotyczne 32 (2):153-185.
    The affirmative answer to the title question is justified in two ways: logical and empirical. The logical justification is due to Gödel’s discovery that in any axiomatic formalized theory, having at least the expressive power of PA, at any stage of development there must appear unsolvable problems. However, some of them become solvable in a further development of the theory in question, owing to subsequent investigations. These lead to new concepts, expressed with additional axioms or rules. Owing to the so-amplified (...)
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  • Computers as Interactive Machines: Can We Build an Explanatory Abstraction?Alice Martin, Mathieu Magnaudet & Stéphane Conversy - 2023 - Minds and Machines 33 (1):83-112.
    In this paper, we address the question of what current computers are from the point of view of human-computer interaction. In the early days of computing, the Turing machine (TM) has been the cornerstone of the understanding of computers. The TM defines what can be computed and how computation can be carried out. However, in the last decades, computers have evolved and increasingly become interactive systems, reacting in real-time to external events in an ongoing loop. We argue that the TM (...)
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  • Alan Turing and the origins of complexity.Miguel Angel Martin-Delgado - 2013 - Arbor 189 (764):a083.
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  • Governing ignorance through abduction.Lorenzo Magnani - 2021 - Logic Journal of the IGPL 29 (4):409-424.
    I will analyse three fundamental ways of governing ignorance though abduction, which are essential from an eco-cognitive and eco-logical point of view, in which the central role in human cognition of natural and artefactual environment is taken into account. First of all, according to the so-called GW-schema, proposed by Gabbay and Woods, abduction presents an ignorance-preserving or (ignorance-mitigating) character: given the fact that the abduced hypotheses aim at becoming truths, the basic ignorance is neither solved nor left untouched. Second, I (...)
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  • Beyond mind: How brains make up artificial cognitive systems. [REVIEW]Lorenzo Magnani - 2009 - Minds and Machines 19 (4):477-493.
    What I call semiotic brains are brains that make up a series of signs and that are engaged in making or manifesting or reacting to a series of signs: through this semiotic activity they are at the same time engaged in “being minds” and so in thinking intelligently. An important effect of this semiotic activity of brains is a continuous process of disembodiment of mind that exhibits a new cognitive perspective on the mechanisms underling the semiotic emergence of meaning processes. (...)
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  • Transcending Turing computability.B. J. Maclennan - 2003 - Minds and Machines 13 (1):3-22.
    It has been argued that neural networks and other forms of analog computation may transcend the limits of Turing-machine computation; proofs have been offered on both sides, subject to differing assumptions. In this article I argue that the important comparisons between the two models of computation are not so much mathematical as epistemological. The Turing-machine model makes assumptions about information representation and processing that are badly matched to the realities of natural computation (information representation and processing in or inspired by (...)
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  • Forms of knowledge and forms of discussion.Jim Mackenzie - 1998 - Educational Philosophy and Theory 30 (1):27–49.
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  • Alonzo church:his life, his work and some of his miracles.Maía Manzano - 1997 - History and Philosophy of Logic 18 (4):211-232.
    This paper is dedicated to Alonzo Church, who died in August 1995 after a long life devoted to logic. To Church we owe lambda calculus, the thesis bearing his name and the solution to the Entscheidungsproblem.His well-known book Introduction to Mathematical LogicI, defined the subject matter of mathematical logic, the approach to be taken and the basic topics addressed. Church was the creator of the Journal of Symbolic Logicthe best-known journal of the area, which he edited for several decades This (...)
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  • Symbols, subsymbols, neurons.William G. Lycan - 1988 - Behavioral and Brain Sciences 11 (1):43-44.
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  • From Alan Turing to modern AI: practical solutions and an implicit epistemic stance.George F. Luger & Chayan Chakrabarti - 2017 - AI and Society 32 (3):321-338.
    It has been just over 100 years since the birth of Alan Turing and more than 65 years since he published in Mind his seminal paper, Computing Machinery and Intelligence. In the Mind paper, Turing asked a number of questions, including whether computers could ever be said to have the power of “thinking”. Turing also set up a number of criteria—including his imitation game—under which a human could judge whether a computer could be said to be “intelligent”. Turing’s paper, as (...)
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  • Open problems in the philosophy of information.Luciano Floridi - 2004 - Metaphilosophy 35 (4):554-582.
    The philosophy of information (PI) is a new area of research with its own field of investigation and methodology. This article, based on the Herbert A. Simon Lecture of Computing and Philosophy I gave at Carnegie Mellon University in 2001, analyses the eighteen principal open problems in PI. Section 1 introduces the analysis by outlining Herbert Simon's approach to PI. Section 2 discusses some methodological considerations about what counts as a good philosophical problem. The discussion centers on Hilbert's famous analysis (...)
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