Results for 'Numerical computations'

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  1.  11
    Numerical computation of the director field in a twist wall.Robert Turner - 1975 - Philosophical Magazine 31 (3):719-722.
  2.  12
    Formal Signs and Numerical Computation: Between Intuitionism and Formalism. Critique of Computational Reason.Bruno Bachimont - 2008 - In Jan Lazardzig, Ludger Schwarte & Helmar Schramm (eds.), Theatrum Scientiarum - English Edition, Volume 2, Instruments in Art and Science: On the Architectonics of Cultural Boundaries in the 17th Century. De Gruyter. pp. 362-382.
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  3. The downdraft in convective shower-cloud a numerical computation.Takao Takeda - 1965 - In Karl W. Linsenmann (ed.), Proceedings. St. Louis, Lutheran Academy for Scholarship. pp. 45--30.
     
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  4.  4
    Computational Analysis on Numerical Simulation of Internal Flow Physics for Pump as Turbine in Renewable Small Hydro Energy Generation.Daniel du JianguoAdu, Emmanuel Acheaw, Shakir Hafeez & Eric Ofosu Antw - 2020 - Complexity 2020:1-10.
    Energy contributes significantly in almost all aspects of human life as well as economic activities and plays a crucial role in the infrastructural development of a county to alleviate poverty. Generating energy from a renewable source such as small hydropower through the application of pump operating as a turbine mode called Pump as Turbine is one of the best alternatives to provide clean and inexpensive energy. Using Pump as Turbine helps in generating reasonably priced hydroelectric power for communities in underdeveloped (...)
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  5.  7
    What numerical methods are not. The case of multilayered simulations, with several computational models.Thomas Boyer - unknown
  6.  44
    On the computational complexity of the numerically definite syllogistic and related logics.Ian Pratt-Hartmann - 2008 - Bulletin of Symbolic Logic 14 (1):1-28.
    The numerically definite syllogistic is the fragment of English obtained by extending the language of the classical syllogism with numerical quantifiers. The numerically definite relational syllogistic is the fragment of English obtained by extending the numerically definite syllogistic with predicates involving transitive verbs. This paper investigates the computational complexity of the satisfiability problem for these fragments. We show that the satisfiability problem (= finite satisfiability problem) for the numerically definite syllogistic is strongly NP-complete, and that the satisfiability problem (= (...)
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  7.  15
    The dependence of computability on numerical notations.Ethan Brauer - 2021 - Synthese 198 (11):10485-10511.
    Which function is computed by a Turing machine will depend on how the symbols it manipulates are interpreted. Further, by invoking bizarre systems of notation it is easy to define Turing machines that compute textbook examples of uncomputable functions, such as the solution to the decision problem for first-order logic. Thus, the distinction between computable and uncomputable functions depends on the system of notation used. This raises the question: which systems of notation are the relevant ones for determining whether a (...)
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  8.  5
    Recursive Numeral Systems Optimize the Trade‐off Between Lexicon Size and Average Morphosyntactic Complexity.Milica Denić & Jakub Szymanik - 2024 - Cognitive Science 48 (3):e13424.
    Human languages vary in terms of which meanings they lexicalize, but this variation is constrained. It has been argued that languages are under two competing pressures: the pressure to be simple (e.g., to have a small lexicon) and to allow for informative (i.e., precise) communication, and that which meanings get lexicalized may be explained by languages finding a good way to trade off between these two pressures. However, in certain semantic domains, languages can reach very high levels of informativeness even (...)
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  9.  9
    Computability and Randomness.André Nies - 2008 - Oxford, England: Oxford University Press UK.
    The interplay between computability and randomness has been an active area of research in recent years, reflected by ample funding in the USA, numerous workshops, and publications on the subject. The complexity and the randomness aspect of a set of natural numbers are closely related. Traditionally, computability theory is concerned with the complexity aspect. However, computability theoretic tools can also be used to introduce mathematical counterparts for the intuitive notion of randomness of a set. Recent research shows that, conversely, concepts (...)
  10.  73
    A Mechanistic Account of Computational Explanation in Cognitive Science and Computational Neuroscience.Marcin Miłkowski - 2016 - In Vincent C. Müller (ed.), Computing and philosophy: Selected papers from IACAP 2014. Cham: 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.
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  11.  15
    Beyond Numerical and Causal Accuracy: Expanding the Set of Justificational Criteria.Jeffry L. Ramsey - 1990 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1990:485 - 499.
    I argue that numerical and causal accuracy arguments can be successful only if: (1) the theories in use are known to be true, (2) computational difficulties do not exist, and (3) the experimental data are stable and resolved. When any one or more of these assumptions are not satisfied, additional justificational considerations must be invoked. I illustrate the need for range of validity and intelligibility claims with examples drawn from chemical kinetics. My arguments suggest that the realist and anti-realist (...)
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  12.  39
    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 (...)
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  13.  12
    Computational complexity on computable metric spaces.Klaus Weirauch - 2003 - Mathematical Logic Quarterly 49 (1):3-21.
    We introduce a new Turing machine based concept of time complexity for functions on computable metric spaces. It generalizes the ordinary complexity of word functions and the complexity of real functions studied by Ko [19] et al. Although this definition of TIME as the maximum of a generally infinite family of numbers looks straightforward, at first glance, examples for which this maximum exists seem to be very rare. It is the main purpose of this paper to prove that, nevertheless, the (...)
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  14.  20
    Ostrowski Numeration Systems, Addition, and Finite Automata.Philipp Hieronymi & Alonza Terry Jr - 2018 - Notre Dame Journal of Formal Logic 59 (2):215-232.
    We present an elementary three-pass algorithm for computing addition in Ostrowski numeration systems. When a is quadratic, addition in the Ostrowski numeration system based on a is recognizable by a finite automaton. We deduce that a subset of X⊆Nn is definable in, where Va is the function that maps a natural number x to the smallest denominator of a convergent of a that appears in the Ostrowski representation based on a of x with a nonzero coefficient if and only if (...)
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  15.  41
    Temporal, numerical and meta-level dynamics in argumentation networks.H. Barringer, D. M. Gabbay & J. Woods - 2012 - Argument and Computation 3 (2-3):143 - 202.
    This paper studies general numerical networks with support and attack. Our starting point is argumentation networks with the Caminada labelling of three values 1=in, 0=out and ½=undecided. This is generalised to arbitrary values in [01], which enables us to compare with other numerical networks such as predator?prey ecological networks, flow networks, logical modal networks and more. This new point of view allows us to see the place of argumentation networks in the overall landscape of networks and import and (...)
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  16.  8
    Numerical Study on Crack Distributions of the Single-Layer Building under Seismic Waves.Fenghui Dong, Zhipeng Zhong & Jin Cheng - 2018 - Complexity 2018:1-16.
    This paper conducts a numerical simulation of the antiseismic performance for single-layer masonry structures, completes a study on crack distributions and detailed characteristics of masonry structures, and finally verifies the correctness of the numerical model by experimental tests. This paper also provides a reinforced proposal to improve the antiseismic performance of single-layer masonry structures. Results prove that the original model suffers more serious damage than the reinforced model; in particular, longitudinal cracks appear on bottoms of two longitudinal walls (...)
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  17.  82
    Computational Models of Performance Monitoring and Cognitive Control.William H. Alexander & Joshua W. Brown - 2010 - Topics in Cognitive Science 2 (4):658-677.
    The medial prefrontal cortex (mPFC) has been the subject of intense interest as a locus of cognitive control. Several computational models have been proposed to account for a range of effects, including error detection, conflict monitoring, error likelihood prediction, and numerous other effects observed with single-unit neurophysiology, fMRI, and lesion studies. Here, we review the state of computational models of cognitive control and offer a new theoretical synthesis of the mPFC as signaling response–outcome predictions. This new synthesis has two interacting (...)
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  18.  46
    Numerical Methods, Complexity, and Epistemic Hierarchies.Nicolas Fillion & Sorin Bangu - 2015 - Philosophy of Science 82 (5):941-955.
    Modern mathematical sciences are hard to imagine without appeal to efficient computational algorithms. We address several conceptual problems arising from this interaction by outlining rival but complementary perspectives on mathematical tractability. More specifically, we articulate three alternative characterizations of the complexity hierarchy of mathematical problems that are themselves based on different understandings of computational constraints. These distinctions resolve the tension between epistemic contexts in which exact solutions can be found and the ones in which they cannot; however, contrary to a (...)
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  19.  10
    Numerical Magnitude Processing in Deaf Adolescents and Its Contribution to Arithmetical Ability.Lilan Chen, Yan Wang & Hongbo Wen - 2021 - Frontiers in Psychology 12.
    Although most deaf individuals could use sign language or sign/spoken language mix, hearing loss would still affect their language acquisition. Compensatory plasticity holds that the lack of auditory stimulation experienced by deaf individuals, such as congenital deafness, can be met by enhancements in visual cognition. And the studies of hearing individuals have showed that visual form perception is the cognitive mechanism that could explain the association between numerical magnitude processing and arithmetic computation. Therefore, we examined numerical magnitude processing (...)
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  20. The Computational Boundary of a “Self”: Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition.Michael Levin - 2019 - Frontiers in Psychology 10.
    All epistemic agents physically consist of parts that must somehow comprise an integrated cognitive self. Biological individuals consist of subunits (organs, cells, molecular networks) that are themselves complex and competent in their own context. How do coherent biological Individuals result from the activity of smaller sub-agents? To understand the evolution and function of metazoan bodies and minds, it is essential to conceptually explore the origin of multicellularity and the scaling of the basal cognition of individual cells into a coherent larger (...)
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  21.  9
    Beyond Numerical and Causal Accuracy: Expanding the Set of Justificational Criteria.Jeffry L. Ramsey - 1990 - PSA Proceedings of the Biennial Meeting of the Philosophy of Science Association 1990 (1):485-499.
    Until recently, realists and anti-realists alike have assumed that any approximations which appear in explanations and confirmations in the mathematically oriented physical and biological sciences are “mere distractions” (Laymon 1989, p. 353). When approximation techniques must be used, they are typically justified by appeals to their numerical accuracy. However, recent interest in computational complexity in the sciences has revealed that numerical accuracy is not always the only criterion which should be invoked to justify the use of approximations. Cartwright (...)
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  22. Computational Correlates of Consciousness.Axel Cleeremans - 2006 - In Steven Laureys (ed.), The Boundaries of Consciousness: Neurobiology and Neuropathology: Progress in Brain Research. Elsevier.
    Over the past few years numerous proposals have appeared that attempt to characterize consciousness in terms of what could be called its computational correlates: Principles of information processing with which to characterize the differences between conscious and unconscious processing. Proposed computational correlates include architectural specialization (such as the involvement of specific regions of the brain in conscious processing), properties of representations (such as their stability in time or their strength), and properties of specific processes (such as resonance, synchrony, interactivity, or (...)
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  23.  96
    A Computational Modeling Approach on Three‐Digit Number Processing.Stefan Huber, Korbinian Moeller, Hans-Christoph Nuerk & Klaus Willmes - 2013 - Topics in Cognitive Science 5 (2):317-334.
    Recent findings indicate that the constituting digits of multi-digit numbers are processed, decomposed into units, tens, and so on, rather than integrated into one entity. This is suggested by interfering effects of unit digit processing on two-digit number comparison. In the present study, we extended the computational model for two-digit number magnitude comparison of Moeller, Huber, Nuerk, and Willmes (2011a) to the case of three-digit number comparison (e.g., 371_826). In a second step, we evaluated how hundred-decade and hundred-unit compatibility effects (...)
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  24.  33
    Numerical instability and dynamical systems.Vincent Ardourel & Julie Jebeile - 2021 - European Journal for Philosophy of Science 11 (2):1-21.
    In philosophical studies regarding mathematical models of dynamical systems, instability due to sensitive dependence on initial conditions, on the one side, and instability due to sensitive dependence on model structure, on the other, have by now been extensively discussed. Yet there is a third kind of instability, which by contrast has thus far been rather overlooked, that is also a challenge for model predictions about dynamical systems. This is the numerical instability due to the employment of numerical methods (...)
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  25.  7
    Categorizing Numeric Information for Generalization.Michael Lebowitz - 1985 - Cognitive Science 9 (3):285-308.
    Learning programs that generalize from real‐world examples will have to deal with many different kinds of data. Continuous numeric data can cause problems for algorithms that search for examples with identical property values. These problems can be surmounted by categorizing the numeric data. However, this process has problems of its own. In this paper, we look at the need for categorizing numeric data and several methods for doing so. We concentrate on the use of generalization‐based memory, a memory organization where (...)
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  26. Numerical testing of evolution theories.Nils Aall Barricelli - 1962 - Acta Biotheoretica 16 (1):69-98.
    An interpretive system for the IBM 704 computer permitting interpretation of the genetic pattern of a numeric symbioorganism as a game strategy has been developed. Selection for best performance in a simple game has been applied in a preliminary experiment. An objective method to measure the quality of a game played is described. The results presented in the article show a small but significant improvement of game quality during a period of 2300 generations.The general characteristics of the phenomena observed are (...)
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  27.  14
    Numerical solving of equations in the work of José Mariano Vallejo.Carlos-Oswaldo Suárez Alemán, F. Javier Pérez-Fernández & José-Miguel Pacheco Castelao - 2007 - Archive for History of Exact Sciences 61 (5):537-552.
    The progress of Mathematics during the nineteenth century was characterised both by an enormous acquisition of new knowledge and by the attempts to introduce rigour in reasoning patterns and mathematical writing. Cauchy’s presentation of Mathematical Analysis was not immediately accepted, and many writers, though aware of that new style, did not use it in their own mathematical production. This paper is devoted to an episode of this sort that took place in Spain during the first half of the century: It (...)
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  28.  13
    Early Numerical Analysis in Kepler's New Astronomy.Steinar Thorvaldsen - 2010 - Science in Context 23 (1):39-63.
    ArgumentJohannes Kepler published hisAstronomia novain 1609, based upon a huge amount of computations. The aim of this paper is to show that Kepler's new astronomy was grounded on methods from numerical analysis. In his research he applied and improved methods that required iterative calculations, and he developed precompiled mathematical tables to solve the problems, including a transcendental equation. Kepler was aware of the shortcomings of his novel methods, and called for a new Apollonius to offer a formal mathematical (...)
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  29. 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, (...)
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  30.  65
    Copeland and Proudfoot on computability.Michael Rescorla - 2012 - Studies in History and Philosophy of Science Part A 43 (1):199-202.
    Many philosophers contend that Turing’s work provides a conceptual analysis of numerical computability. In (Rescorla, 2007), I dissented. I argued that the problem of deviant notations stymies existing attempts at conceptual analysis. Copeland and Proudfoot respond to my critique. I argue that their putative solution does not succeed. We are still awaiting a genuine conceptual analysis.
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  31.  5
    Numerical Investigation of the Nonlinear Coupled Fractional Massive Thirring Equation Using Two-Scale Approach.Jinxing Liu, Muhammad Nadeem, Mustafa Habib, Shazia Karim & Harun Or Roshid - 2022 - Complexity 2022:1-8.
    In this paper, we investigate the numerical solution of the coupled fractional massive Thirring equation with the aid of He’s fractional complex transform. This study plays a significant aspect in the field of quantum physics, weakly nonlinear thrilling waves, and nonlinear optics. The main advantage of FCT is that it converts the fractional differential equation into its traditional parts and is also capable to handle the fractional order, whereas the homotopy perturbation method is employed to tackle the nonlinear terms (...)
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  32.  27
    Computers as a Source of A Posteriori Knowledge in Mathematics.Mikkel Willum Johansen & Morten Misfeldt - 2016 - International Studies in the Philosophy of Science 30 (2):111-127.
    Electronic computers form an integral part of modern mathematical practice. Several high-profile results have been proven with techniques where computer calculations form an essential part of the proof. In the traditional philosophical literature, such proofs have been taken to constitute a posteriori knowledge. However, this traditional stance has recently been challenged by Mark McEvoy, who claims that computer calculations can constitute a priori mathematical proofs, even in cases where the calculations made by the computer are too numerous to be surveyed (...)
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  33.  54
    Computable chaos.John A. Winnie - 1992 - Philosophy of Science 59 (2):263-275.
    Some irrational numbers are "random" in a sense which implies that no algorithm can compute their decimal expansions to an arbitrarily high degree of accuracy. This feature of (most) irrational numbers has been claimed to be at the heart of the deterministic, but chaotic, behavior exhibited by many nonlinear dynamical systems. In this paper, a number of now classical chaotic systems are shown to remain chaotic when their domains are restricted to the computable real numbers, providing counterexamples to the above (...)
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  34.  82
    Quantum Computing’s Classical Problem, Classical Computing’s Quantum Problem.Rodney Van Meter - 2014 - Foundations of Physics 44 (8):819-828.
    Tasked with the challenge to build better and better computers, quantum computing and classical computing face the same conundrum: the success of classical computing systems. Small quantum computing systems have been demonstrated, and intermediate-scale systems are on the horizon, capable of calculating numeric results or simulating physical systems far beyond what humans can do by hand. However, to be commercially viable, they must surpass what our wildly successful, highly advanced classical computers can already do. At the same time, those classical (...)
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  35.  8
    Why Computers Can’t Feel Pain.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 monograph, “Representation & Reality”, which if correct, has important implications for turing machine functionalism and the (...)
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  36.  19
    Computer vision, human senses, and language of art.Lev Manovich - 2021 - AI and Society 36 (4):1145-1152.
    What is the most important reason for using Computer Vision methods in humanities research? In this article, I argue that the use of numerical representation and data analysis methods offers a new language for describing cultural artifacts, experiences and dynamics. The human languages such as English or Russian that developed rather recently in human evolution are not good at capturing analog properties of human sensorial and cultural experiences. These limitations become particularly worrying if we want to compare thousands, millions (...)
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  37.  4
    Review: A.I. Mal'cev, Polno numerovannye mnozestva (Complete Enumeration of a Set); A. I. Mal'cev, K teorii vycislimyh semejstv obektov (On the Theory of Computable Families of Objects); A. I. Mal'cev, Pozitivnye i negativnye numeracii (Positive and Negative Numerations). [REVIEW]Elliott Mendelson - 1970 - Journal of Symbolic Logic 35 (2):336-337.
  38.  4
    Computational physics: an introduction.Franz Vesely - 2001 - New York: Kluwer Academic/Plenum Publishers.
    Vesely (experimental physics, U. of Vienna, Austria) provides the basic numerical and computational techniques, followed by an explanation of specific problems of computational physics. Appendices address properties of computing machines and an outline of the technique of Fast Fourier Transformation. The first edition, published by Plenum Press, Ne.
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  39.  26
    Computational Models and Virtual Reality. New Perspectives of Research in Chemistry.Klaus Mainzer - 1999 - Hyle 5 (2):135 - 144.
    Molecular models are typical topics of chemical research depending on the technical standards of observation, computation, and representation. Mathematically, molecular structures have been represented by means of graph theory, topology, differential equations, and numerical procedures. With the increasing capabilities of computer networks, computational models and computer-assisted visualization become an essential part of chemical research. Object-oriented programming languages create a virtual reality of chemical structures opening new avenues of exploration and collaboration in chemistry. From an epistemic point of view, virtual (...)
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  40.  18
    Webb Miller. Recursive function theory and numerical analysis. Journal of computer and system sciences vol. 4 , pp. 465–472. [REVIEW]J. P. Cleave - 1974 - Journal of Symbolic Logic 39 (2):346.
  41.  6
    Computer Simulations.Paul Humphreys - 1990 - PSA Proceedings of the Biennial Meeting of the Philosophy of Science Association 1990 (2):496-506.
    A great deal of attention has been paid by philosophers to the use of computers in the modelling of human cognitive capacities and in the construction of intelligent artifacts. This emphasis has tended to obscure the fact that most of the high-level computing power in science is deployed in what appears to be a much less exciting activity: solving equations. This apparently mundane set of applications reflects the historical origins of modem computing, in the sense that most of the early (...)
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  42.  45
    Scientific Discovery: Computational Explorations of the Creative Processes.Malcolm R. Forster - 1987 - MIT Press (MA).
    Scientific discovery is often regarded as romantic and creative - and hence unanalyzable - whereas the everyday process of verifying discoveries is sober and more suited to analysis. Yet this fascinating exploration of how scientific work proceeds argues that however sudden the moment of discovery may seem, the discovery process can be described and modeled. Using the methods and concepts of contemporary information-processing psychology (or cognitive science) the authors develop a series of artificial-intelligence programs that can simulate the human thought (...)
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  43.  7
    On numerical characterizations of the topological reduction of incomplete information systems based on evidence theory.Yanlan Zhang & Changqing Li - 2023 - Journal of Intelligent Systems 32 (1).
    Knowledge reduction of information systems is one of the most important parts of rough set theory in real-world applications. Based on the connections between the rough set theory and the theory of topology, a kind of topological reduction of incomplete information systems is discussed. In this study, the topological reduction of incomplete information systems is characterized by belief and plausibility functions from evidence theory. First, we present that a topological space induced by a pair of approximation operators in an incomplete (...)
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  44. A natural axiomatization of computability and proof of Church’s thesis.Nachum Dershowitz & Yuri Gurevich - 2008 - Bulletin of Symbolic Logic 14 (3):299-350.
    Church's Thesis asserts that the only numeric functions that can be calculated by effective means are the recursive ones, which are the same, extensionally, as the Turing-computable numeric functions. The Abstract State Machine Theorem states that every classical algorithm is behaviorally equivalent to an abstract state machine. This theorem presupposes three natural postulates about algorithmic computation. Here, we show that augmenting those postulates with an additional requirement regarding basic operations gives a natural axiomatization of computability and a proof of Church's (...)
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  45.  25
    Numeric Tessituras.Tania Fraga - 2010 - Technoetic Arts 8 (2):243-250.
    This article presents research on assemblages among humans and computational systems in which physical and virtual autonomous processes occur in order to create artworks allowing the emergence of mixed sensory set-ups. It begins with triadic relationships computer, physical objects and participants aimed at co-relations among bands of bots (virtual and physical) with groups of humans (interactors). The bots have a representation of the virtual world: physical bots live on a flat surface (Abbot 1991), a projection of the 3D environment where (...)
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  46.  37
    Computable and continuous partial homomorphisms on metric partial algebras.Viggo Stoltenberg-Hansen & John V. Tucker - 2003 - Bulletin of Symbolic Logic 9 (3):299-334.
    We analyse the connection between the computability and continuity of functions in the case of homomorphisms between topological algebraic structures. Inspired by the Pour-El and Richards equivalence theorem between computability and boundedness for closed linear operators on Banach spaces, we study the rather general situation of partial homomorphisms between metric partial universal algebras. First, we develop a set of basic notions and results that reveal some of the delicate algebraic, topological and effective properties of partial algebras. Our main computability concepts (...)
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  47.  6
    Computable and Continuous Partial Homomorphisms on Metric Partial Algebras.Viggo Stoltenberg-Hansen & John V. Tucker - 2003 - Bulletin of Symbolic Logic 9 (3):299-334.
    We analyse the connection between the computability and continuity of functions in the case of homomorphisms between topological algebraic structures. Inspired by the Pour-El and Richards equivalence theorem between computability and boundedness for closed linear operators on Banach spaces, we study the rather general situation of partial homomorphisms between metric partial universal algebras. First, we develop a set of basic notions and results that reveal some of the delicate algebraic, topological and effective properties of partial algebras. Our main computability concepts (...)
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  48.  3
    Interactive Computer Graphics: The Arms Race.David Hafemeister - 1984 - Bulletin of Science, Technology and Society 4 (5):471-488.
    By using interactive computer graphics (ICG), it is possible to discuss the numerical aspects of some arms race issues with more specificity and in a visual way. The number of variables involved in these issues can be quite large; computers operated in the interactive, graphical mode, can allow exploration of the variables, leading to a greater understanding of the issues. This paper will examine some examples of interactive computer graphics: (1) The relationship between silo hardening and the accuracy, yield, (...)
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  49.  22
    Numerically solving physiological models based on a polynomial approach.F. Tudoret, A. Bardou & G. Carrault - 2001 - Acta Biotheoretica 49 (4):247-260.
    Much research effort has been directed in different physiological contexts towards describing realistic behaviors with differential equations. One observes obviously that more state-variables give the model more accuracy. Unfortunately, the computational cost involved is higher. A new algorithm is presented for simulating a model described by a system of differential equations in which efficiency may not be altered by its size. In order to do this, the method is based on a polynomial description of the state-variables' evolution and on a (...)
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  50. Church's Thesis and the Conceptual Analysis of Computability.Michael Rescorla - 2007 - Notre Dame Journal of Formal Logic 48 (2):253-280.
    Church's thesis asserts that a number-theoretic function is intuitively computable if and only if it is recursive. A related thesis asserts that Turing's work yields a conceptual analysis of the intuitive notion of numerical computability. I endorse Church's thesis, but I argue against the related thesis. I argue that purported conceptual analyses based upon Turing's work involve a subtle but persistent circularity. Turing machines manipulate syntactic entities. To specify which number-theoretic function a Turing machine computes, we must correlate these (...)
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