Results for 'Computing'

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  1. Randomness and Recursive Enumerability.Siam J. Comput - unknown
    One recursively enumerable real α dominates another one β if there are nondecreasing recursive sequences of rational numbers (a[n] : n ∈ ω) approximating α and (b[n] : n ∈ ω) approximating β and a positive constant C such that for all n, C(α − a[n]) ≥ (β − b[n]). See [R. M. Solovay, Draft of a Paper (or Series of Papers) on Chaitin’s Work, manuscript, IBM Thomas J. Watson Research Center, Yorktown Heights, NY, 1974, p. 215] and [G. J. (...)
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  2.  10
    Computer Science Logic: 11th International Workshop, CSL'97, Annual Conference of the EACSL, Aarhus, Denmark, August 23-29, 1997, Selected Papers.M. Nielsen, Wolfgang Thomas & European Association for Computer Science Logic - 1998 - Springer Verlag.
    This book constitutes the strictly refereed post-workshop proceedings of the 11th International Workshop on Computer Science Logic, CSL '97, held as the 1997 Annual Conference of the European Association on Computer Science Logic, EACSL, in Aarhus, Denmark, in August 1997. The volume presents 26 revised full papers selected after two rounds of refereeing from initially 92 submissions; also included are four invited papers. The book addresses all current aspects of computer science logics and its applications and thus presents the state (...)
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  3. Computing mechanisms.Gualtiero Piccinini - 2007 - Philosophy of Science 74 (4):501-526.
    This paper offers an account of what it is for a physical system to be a computing mechanism—a system that performs computations. A computing mechanism is a mechanism whose function is to generate output strings from input strings and (possibly) internal states, in accordance with a general rule that applies to all relevant strings and depends on the input strings and (possibly) internal states for its application. This account is motivated by reasons endogenous to the philosophy of (...), namely, doing justice to the practices of computer scientists and computability theorists. It is also an application of recent literature on mechanisms, because it assimilates computational explanation to mechanistic explanation. The account can be used to individuate computing mechanisms and the functions they compute and to taxonomize computing mechanisms based on their computing power. (shrink)
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  4.  34
    Computing ideal sceptical argumentation.P. M. Dung, P. Mancarella & F. Toni - 2007 - Artificial Intelligence 171 (10-15):642-674.
  5. Computing applications for the engineering design of nuclear fuel cycle facilities.P. C. Cuchieratto, A. Braganga Jr, L. Salgado & R. Bretzel - 1991 - Ai 1991 Frontiers in Innovative Computing for the Nuclear Industry Topical Meeting, Jackson Lake, Wy, Sept. 15-18, 1991 1.
     
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  6. Computing Exact Power for Multivariate Repeated Measurements Design.Jimmy Thomas Efird & Kavitha Alimineti - 2005 - In Alan F. Blackwell & David MacKay (eds.), Power. New York: Cambridge University Press. pp. 1.
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  7. The fortieth annual lecture series 1999-2000.Brain Computations & an Inevitable Conflict - 2000 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 31:199-200.
  8.  20
    Computing with Mathematical Arguments.Jesse Alama & Reinhard Kahle - 2013 - In Hanne Andersen, Dennis Dieks, Wenceslao J. Gonzalez, Thomas Uebel & Gregory Wheeler (eds.), New Challenges to Philosophy of Science. Springer Verlag. pp. 9--22.
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  9. Computing a longest increasing subsequence of length $ k $ in time $ O (n\ log\ log k) $.Maxime Crochemore & Ely Porat - 2008 - In Erol Gelenbe, Samson Abramsky & Vladimiro Sassone (eds.), Visions of Computer Science. British Computer Society. pp. 69--74.
     
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  10.  36
    Computing the Meanings of Words in Reading: Cooperative Division of Labor Between Visual and Phonological Processes.Michael W. Harm & Mark S. Seidenberg - 2004 - Psychological Review 111 (3):662-720.
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  11. On the Foundations of Computing.Giuseppe Primiero - 2019 - Oxford University Press.
    Computing, today more than ever before, is a multi-faceted discipline which collates several methodologies, areas of interest, and approaches: mathematics, engineering, programming, and applications. Given its enormous impact on everyday life, it is essential that its debated origins are understood, and that its different foundations are explained. On the Foundations of Computing offers a comprehensive and critical overview of the birth and evolution of computing, and it presents some of the most important technical results and philosophical problems (...)
  12.  46
    Pitfalls in biological computing: Canonical and idiosyncratic dysfunction of conscious machines.Rodrick Wallace - 2006 - Mind and Matter 4 (1):91-113.
    The central paradigm of arti?cial intelligence is rapidly shifting toward biological models for both robotic devices and systems performing such critical tasks as network management, vehicle navigation, and process control. Here we use a recent mathematical analysis of the necessary conditions for consciousness in humans to explore likely failure modes inherent to a broad class of biologically inspired computing machines. Analogs to developmental psychopathology, in which regulatory mechanisms for consciousness fail progressively and subtly understress, and toinattentional blindness, where a (...)
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  13.  53
    A Computing Procedure for Quantification Theory.Martin Davis & Hilary Putnam - 1966 - Journal of Symbolic Logic 31 (1):125-126.
  14.  85
    Computing Mechanisms Without Proper Functions.Joe Dewhurst - 2018 - Minds and Machines 28 (3):569-588.
    The aim of this paper is to begin developing a version of Gualtiero Piccinini’s mechanistic account of computation that does not need to appeal to any notion of proper (or teleological) functions. The motivation for doing so is a general concern about the role played by proper functions in Piccinini’s account, which will be evaluated in the first part of the paper. I will then propose a potential alternative approach, where computing mechanisms are understood in terms of Carl Craver’s (...)
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  15.  26
    ASSAT: computing answer sets of a logic program by SAT solvers.Fangzhen Lin & Yuting Zhao - 2004 - Artificial Intelligence 157 (1-2):115-137.
  16.  17
    Computing cooperative solution concepts in coalitional skill games.Yoram Bachrach, David C. Parkes & Jeffrey S. Rosenschein - 2013 - Artificial Intelligence 204 (C):1-21.
  17. Computing and moral responsibility.Merel Noorman - forthcoming - Stanford Encyclopedia of Philosophy.
  18.  6
    A Model for Proustian Decay.Computer Lars - 2024 - Nordic Journal of Aesthetics 33 (67).
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  19.  37
    Computing as Empirical Science- Evolution as a Concept.Paweł Polak - 2016 - Studies in Logic, Grammar and Rhetoric 48 (1):49-69.
    This article presents the evolution of philosophical and methodological considerations concerning empiricism in computer/computing science. In this study, we trace the most important current events in the history of reflection on computing. The forerunners of Artificial Intelligence H.A. Simon and A. Newell in their paper Computer Science As Empirical Inquiry started these considerations. Later the concept of empirical computer science was developed by S.S. Shapiro, P. Wegner, A.H. Eden and P.J. Denning. They showed various empirical aspects of (...). This led to a view of the science of computing - the science of general scope. Some interesting contemporary ways towards a generalized perspective on computations were also shown. (shrink)
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  20.  10
    Computing a small agreeable set of indivisible items.Pasin Manurangsi & Warut Suksompong - 2019 - Artificial Intelligence 268 (C):96-114.
  21.  9
    Computing optimal hypertree decompositions with SAT.André Schidler & Stefan Szeider - 2023 - Artificial Intelligence 325 (C):104015.
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  22. (1 other version)Computing machinery and intelligence.Alan Turing - 1950 - Mind 59 (236):433-60.
    I propose to consider the question, "Can machines think?" This should begin with definitions of the meaning of the terms "machine" and "think." The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous, If the meaning of the words "machine" and "think" are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to (...)
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  23.  35
    Computing the Number of Types of Infinite Length.Will Boney - 2017 - Notre Dame Journal of Formal Logic 58 (1):133-154.
    We show that the number of types of sequences of tuples of a fixed length can be calculated from the number of 1-types and the length of the sequences. Specifically, if κ≤λ, then sup ‖M‖=λ|Sκ|=|)κ. We show that this holds for any abstract elementary class with λ-amalgamation. No such calculation is possible for nonalgebraic types. However, we introduce a subclass of nonalgebraic types for which the same upper bound holds.
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  24. Philosophy of computing and information: 5 Questions.Luciano Floridi - 2008 - Copenhagen, Denmark: Automatic Press/VIP.
    Computing and information, and their philosophy in the broad sense, play a most important scientific, technological and conceptual role in our world. This book collects together, for the first time, the views and experiences of some of the visionary pioneers and most influential thinkers in such a fundamental area of our intellectual development.
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  25. Computing, Modelling, and Scientific Practice: Foundational Analyses and Limitations.Philippos Papayannopoulos - 2018 - Dissertation,
    This dissertation examines aspects of the interplay between computing and scientific practice. The appropriate foundational framework for such an endeavour is rather real computability than the classical computability theory. This is so because physical sciences, engineering, and applied mathematics mostly employ functions defined in continuous domains. But, contrary to the case of computation over natural numbers, there is no universally accepted framework for real computation; rather, there are two incompatible approaches --computable analysis and BSS model--, both claiming to formalise (...)
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  26.  50
    Routine Computing Tasks: Planning as Understanding.Suzanne M. Mannes & Walter Kintsch - 1991 - Cognitive Science 15 (3):305-342.
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  27.  35
    Reading Emotion From Mouse Cursor Motions: Affective Computing Approach.Takashi Yamauchi & Kunchen Xiao - 2018 - Cognitive Science 42 (3):771-819.
    Affective computing research has advanced emotion recognition systems using facial expressions, voices, gaits, and physiological signals, yet these methods are often impractical. This study integrates mouse cursor motion analysis into affective computing and investigates the idea that movements of the computer cursor can provide information about emotion of the computer user. We extracted 16–26 trajectory features during a choice-reaching task and examined the link between emotion and cursor motions. Participants were induced for positive or negative emotions by music, (...)
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  28.  22
    Hector freytes, Antonio ledda, Giuseppe sergioli and.Roberto Giuntini & Probabilistic Logics in Quantum Computation - 2013 - In Hanne Andersen, Dennis Dieks, Wenceslao J. Gonzalez, Thomas Uebel & Gregory Wheeler (eds.), New Challenges to Philosophy of Science. Springer Verlag. pp. 49.
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  29. Computing Machinery and Sexual Difference: The Sexed Presuppositions Underlying the Turing Test.Amy Kind - 2022 - In Keya Maitra & Jennifer McWeeny (eds.), Feminist Philosophy of Mind. New York, NY, United States of America: Oxford University Press, Usa.
    In his 1950 paper “Computing Machinery and Intelligence,” Alan Turing proposed that we can determine whether a machine thinks by considering whether it can win at a simple imitation game. A neutral questioner communicates with two different systems – one a machine and a human being – without knowing which is which. If after some reasonable amount of time the machine is able to fool the questioner into identifying it as the human, the machine wins the game, and we (...)
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  30.  44
    Quantum Computing since Democritus.Reviel Netz - 2014 - Common Knowledge 20 (3):490-491.
  31.  94
    Augmented reality and ubiquitous computing: the hidden potentialities of augmented reality.Nicola Liberati - 2016 - AI and Society 31 (1):17-28.
  32. Computing and cognitive science.Zenon W. Pylyshyn - 1989 - In Michael I. Posner (ed.), Foundations of Cognitive Science. MIT Press.
    influence. One of the principal characteristics that distinguishes Cognitive Science from more traditional studies of cognition within Psychology, is the extent to which it has been influenced by both the ideas and the techniques of computing. It may come as a surprise to the outsider, then, to discover that there is no unanimity within the discipline on either (a) the nature (and in some cases the desireabilty) of the influence and (b) what computing is –- or at least (...)
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  33.  22
    Computing the least common subsumer w.r.t. a background terminology.Franz Baader, Baris Sertkaya & Anni-Yasmin Turhan - 2007 - Journal of Applied Logic 5 (3):392-420.
  34. Computing Verisimilitude.Katarina Britz & Chris Brink - 1995 - Notre Dame Journal of Formal Logic 36 (1):30-43.
    This paper continues the power ordering approach to verisimilitude. We define a parameterized verisimilar ordering of theories in the finite propositional case, both semantically and syntactically. The syntactic definition leads to an algorithm for computing verisimilitude. Since the power ordering approach to verisimilitude can be translated into a standard notion of belief revision, the algorithm thereby also allows the computation of membership of a belief-revised theory.
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  35.  7
    Computing, genetics, and policy: theoretical and practical considerations.Ruth Chadwick - unknown
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  36.  60
    Computing, Modelling, and Scientific Practice: Foundational Analyses and Limitations.Filippos A. Papagiannopoulos - 2018 - Dissertation, University of Western Ontario
    This dissertation examines aspects of the interplay between computing and scientific practice. The appropriate foundational framework for such an endeavour is rather real computability than the classical computability theory. This is so because physical sciences, engineering, and applied mathematics mostly employ functions defined in continuous domains. But, contrary to the case of computation over natural numbers, there is no universally accepted framework for real computation; rather, there are two incompatible approaches --computable analysis and BSS model--, both claiming to formalise (...)
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  37.  39
    Computing definite logic programs by partial instantiation.Vadim Kagan, Anil Nerode & V. S. Subrahmanian - 1994 - Annals of Pure and Applied Logic 67 (1-3):161-182.
    Query processing in ground definite deductive is known to correspond precisely to a linear programming problem. However, the “groundedness” requirement is a huge drawback to using linear programming techniques for logic program computations because the ground version of a logic program can be very large when compared to the original program. Furthermore, when we move from propositional logic programs to first-order logic programs, this effectively means that functions symbols may not occur in clauses. In this paper, we develop a theory (...)
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  38.  18
    Computing finite models by reduction to function-free clause logic.Peter Baumgartner, Alexander Fuchs, Hans de Nivelle & Cesare Tinelli - 2009 - Journal of Applied Logic 7 (1):58-74.
  39. Paul M. kjeldergaard.Pittsburgh Computations Centers - 1968 - In T. Dixon & Deryck Horton (eds.), Verbal Behavior and General Behavior Theory. Prentice-Hall.
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  40.  27
    Computing strength of structures related to the field of real numbers.Gregory Igusa, Julia F. Knight & Noah David Schweber - 2017 - Journal of Symbolic Logic 82 (1):137-150.
    In [8], the third author defined a reducibility$\le _w^{\rm{*}}$that lets us compare the computing power of structures of any cardinality. In [6], the first two authors showed that the ordered field of reals${\cal R}$lies strictly above certain related structures. In the present paper, we show that$\left \equiv _w^{\rm{*}}{\cal R}$. More generally, for the weak-looking structure${\cal R}$ℚconsisting of the real numbers with just the ordering and constants naming the rationals, allo-minimal expansions of${\cal R}$ℚare equivalent to${\cal R}$. Using this, we show (...)
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  41.  94
    Computing Ledgers and the Political Ontology of the Blockchain.Pablo R. Velasco - 2017 - Metaphilosophy 48 (5):712-726.
    This paper investigates ontological dimensions of the blockchain by asking what kind of socio-technical object bitcoin is. It discusses both blockchain's political qualities and the political forms enabled by its emergence. It first observes recent approaches to the ontology of money and the political qualities of the ledgers used by the current fractional reserve banking model. It then directs the same questions at blockchain technology. The paper discusses an ontology proposed by Ole Bjerg and argues in favour of a mixed-ontology (...)
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  42. Computing with Connections In Visual Recognition of Origami Objects.Daniel Sabbah - 1985 - Cognitive Science 9 (1):25-50.
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  43.  12
    Computing.Leslie Burkholder - 2000 - In W. Newton-Smith (ed.), A companion to the philosophy of science. Malden, Mass.: Blackwell. pp. 44–52.
    Computing as a science is the study of computers, both the hardware and their programs, and all that goes with them (Newell and Simon 1976). The philosophy of computer science is concerned with problems of a philosophical kind raised by the discipline's goals, fundamental ideas, techniques or methods, and findings. It parallels other parts of philosophy ‐ for example, the philosophy of economics or linguistics or biology ‐ in primarily considering problems raised by one discipline, rather than issues raised (...)
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  44.  23
    A Literature Review of EEG-Based Affective Computing in Marketing.Guanxiong Pei & Taihao Li - 2021 - Frontiers in Psychology 12:602843.
    Affect plays an important role in the consumer decision-making process and there is growing interest in the development of new technologies and computational approaches that can interpret and recognize the affects of consumers, with benefits for marketing described in relation to both academia and industry. From an interdisciplinary perspective, this paper aims to review past studies focused on electroencephalography (EEG)-based affective computing (AC) in marketing, which provides a promising avenue for studying the mechanisms underlying affective states and developing recognition (...)
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  45.  45
    Exploring a Mechanistic Approach to Experimentation in Computing.Eric Hatleback & Jonathan M. Spring - 2014 - Philosophy and Technology 27 (3):441-459.
    The mechanistic approach in philosophy of science contributes to our understanding of experimental design. Applying the mechanistic approach to experimentation in computing is beneficial for two reasons. It connects the methodology of experimentation in computing with the methodology of experimentation in established sciences, thereby strengthening the scientific reputability of computing and the quality of experimental design therein. Furthermore, it pinpoints the idiosyncrasies of experimentation in computing: computing deals closely with both natural and engineered mechanisms. Better (...)
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  46.  32
    On the Foundations of Computing: Limits and Open Issues.Giuseppe Primiero - 2023 - Axiomathes 33 (4):1-16.
    Any attempt to conceptualize, categorize and constraint foundational issues in a living science, such as Computing, is bound to show its limitations and leave a number of open issues. Taking stock with some critical reviews of Primiero (On the foundations of computing, Oxford University Press, Oxford, 2019) published in this Journal, I overview potential new problems to be investigated by a foundational analysis of the science of computing.
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  47.  72
    Computing and moral responsibility.Kari Gwen Coleman - 2008 - Stanford Encyclopedia of Philosophy.
  48. For computing is our duty" : algorithmic workers, servants, and women at the Harvard Observatory.Andrew Fiss - 2022 - In Morgan G. Ames & Massimo Mazzotti (eds.), Algorithmic modernity: mechanizing thought and action, 1500-2000. New York, NY: Oxford University Press.
     
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  49.  8
    Computing the minimal relations in point-based qualitative temporal reasoning through metagraph closure.Alfonso E. Gerevini & Alessandro Saetti - 2011 - Artificial Intelligence 175 (2):556-585.
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  50.  72
    Computing machinery and morality.Blay Whitby - 2008 - AI and Society 22 (4):551-563.
    Artificial Intelligence (AI) is a technology widely used to support human decision-making. Current areas of application include financial services, engineering, and management. A number of attempts to introduce AI decision support systems into areas which more obviously include moral judgement have been made. These include systems that give advice on patient care, on social benefit entitlement, and even ethical advice for medical professionals. Responding to these developments raises a complex set of moral questions. This paper proposes a clearer replacement question (...)
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