Results for ' verification'

951 found
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  1. Philosophy and computer science: Reflections on the program.Verification Debate - 1998 - In Terrell Ward Bynum & James Moor (eds.), The Digital Phoenix: How Computers are Changing Philosophy. Cambridge: Blackwell. pp. 253.
     
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  2. Roland fraïssé.Et Sa Vérification Dans Certaines - 1968 - In Jean-Louis Destouches & Evert Willem Beth (eds.), Logic and foundations of science. Dordrecht,: D. Reidel.
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  3.  65
    Program verification, defeasible reasoning, and two views of computer science.Timothy R. Colburn - 1991 - Minds and Machines 1 (1):97-116.
    In this paper I attempt to cast the current program verification debate within a more general perspective on the methodologies and goals of computer science. I show, first, how any method involved in demonstrating the correctness of a physically executing computer program, whether by testing or formal verification, involves reasoning that is defeasible in nature. Then, through a delineation of the senses in which programs can be run as tests, I show that the activities of testing and formal (...)
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  4.  54
    Compositional verification of multi-agent systems in temporal multi-epistemic logic.Joeri Engelfriet, Catholijn M. Jonker & Jan Treur - 2002 - Journal of Logic, Language and Information 11 (2):195-225.
    Compositional verification aims at managing the complexity of theverification process by exploiting compositionality of the systemarchitecture. In this paper we explore the use of a temporal epistemiclogic to formalize the process of verification of compositionalmulti-agent systems. The specification of a system, its properties andtheir proofs are of a compositional nature, and are formalized within acompositional temporal logic: Temporal Multi-Epistemic Logic. It isshown that compositional proofs are valid under certain conditions.Moreover, the possibility of incorporating default persistence ofinformation in a (...)
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  5. Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences.Naomi Oreskes, Kristin Shrader-Frechette & Kenneth Belitz - 1994 - Science 263 (5147):641-646.
    Verification and validation of numerical models of natural systems is impossible. This is because natural systems are never closed and because model results are always nonunique. Models can be confirmed by the demonstration of agreement between observation and prediction, but confirmation is inherently partial. Complete confirmation is logically precluded by the fallacy of affirming the consequent and by incomplete access to natural phenomena. Models can only be evaluated in relative terms, and their predictive value is always open to question. (...)
     
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  6. Verification: The Hysteron Proteron Argument.Francis Jeffry Pelletier & Bernard Linsky - 2018 - Journal for the History of Analytical Philosophy 6 (6).
    This paper investigates the strange case of an argument that was directed against a positivist verification principle. We find an early occurrence of the argument in a talk by the phenomenologist Roman Ingarden at the 1934 International Congress of Philosophy in Prague, where Carnap and Neurath were present and contributed short rejoinders. We discuss the underlying presuppositons of the argument, and we evaluate whether the attempts by Carnap (especially) actually succeed in answering this argument. We think they don’t, and (...)
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  7. Program verification: the very idea.James H. Fetzer - 1988 - Communications of the Acm 31 (9):1048--1063.
    The notion of program verification appears to trade upon an equivocation. Algorithms, as logical structures, are appropriate subjects for deductive verification. Programs, as causal models of those structures, are not. The success of program verification as a generally applicable and completely reliable method for guaranteeing program performance is not even a theoretical possibility.
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  8.  31
    (1 other version)Formal verification, scientific code, and the epistemological heterogeneity of computational science.Cyrille Imbert & Vincent Ardourel - 2022 - Philosophy of Science:1-40.
    Various errors can affect scientific code and detecting them is a central concern within computational science. Could formal verification methods, which are now available tools, be widely adopted to guarantee the general reliability of scientific code? After discussing their benefits and drawbacks, we claim that, absent significant changes as regards features like their user-friendliness and versatility, these methods are unlikely to be adopted throughout computational science, beyond certain specific contexts for which they are well-suited. This issue exemplifies the epistemological (...)
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  9. SOCIAL VERIFICATION – HUMAN DIMENSONS OF THEORETICAL SCIENCE AND HIGH-TECH (CASUS BIOETHICS). Part Three. DYNAMICS OF GROWTH OF NEW KNOWLEDGE IN POSTACADEMICAL SCIENCE.Valentin Cheshko & Yulia Kosova - 2012 - Practical Philosophy 1:59-69.
    The new phase of science evolution is characterized by totality of subject and object of cognition and technology (high-hume). As a result, forming of network structure in a disciplinary matrix modern are «human dimensional» natural sciences and two paradigmal «nuclei» (attraktors). As a result, the complication of structure of disciplinary matrix and forming a few paradigm nuclei in modern «human dimensional» natural sciences are observed. In the process of social verification integration of scientific theories into the existent system of (...)
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  10.  20
    Verification and trust in healthcare.Edwin Jesudason - 2023 - Journal of Medical Ethics 49 (3):223-224.
    ‘Trust but verify’ is a translation of a Russian proverb made famous by former US President Ronald Reagan. In their paper, Grahamet alappear to take an alternate view that might be summarised astrust or verify. The contrast highlights a general question: how do we come to trust in authorities? More specifically, Grahamet alclaim: (1) that UK Trusted Research Environments (TREs) are misnamed as future custodians for big health data because their promised verification systems actually negate the uncertainty that trust (...)
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  11. SOCIAL VERIFICATION – HUMAN DIMENSONS OF THEORETICAL SCIENCE AND HIGH-TECH (CASUS BIOETHICS). Part One.Valentin Cheshko & Yulia Kosova - 2011 - Practical Philosophy 1:94-100.
    The new phase of science evolution is characterized by totality of subject and object of cognition and technology (high-hume). As a result, forming of network structure in a disciplinary matrix modern are «human dimensional» natural sciences and two paradigmal «nuclei» (attraktors). As a result, the complication of structure of disciplinary matrix and forming a few paradigm nuclei in modern «human dimensional» natural sciences are observed. In the process of social verification integration of scientific theories into the existent system of (...)
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  12.  68
    Verification, falsification, and the logic of enquiry.Peter Milne - 1991 - Erkenntnis 34 (1):23 - 54.
    Our starting point is Michael Luntley's falsificationist semantics for the logical connectives and quantifiers: the details of his account are criticised but we provide an alternative falsificationist semantics that yields intuitionist logic, as Luntley surmises such a semantics ought. Next an account of the logical connectives and quantifiers that combines verificationist and falsificationist perspectives is proposed and evaluated. While the logic is again intuitionist there is, somewhat surprisingly, an unavoidable asymmetry between the verification and falsification conditions for negation, the (...)
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  13.  13
    Verification of Beliefs.Henry Sidgwick - 2000 - In Marcus G. Singer (ed.), Essays on Ethics and Method. Oxford, GB: Clarendon Press.
    Sidgwick offers an account of how to verify our beliefs, both factual and normative. He maintains that, although utter scepticism cannot be confuted, it also cannot be defended because, as soon as the sceptic tries to justify himself, he invariably limits himself by assuming the truth of certain premises and the validity of a particular method of inference. If it is possible to establish a criterion of truth for a given domain, then within that domain we may possess a set (...)
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  14. Verification (Bewahrung) in Martin Buber.Martin Kavka - 2012 - Journal of Jewish Thought and Philosophy 20 (1):71-98.
    Abstract The work of Martin Buber oscillates between talk in which transcendence is experienced and talk in which transcendence is merely postulated. In order to show and mend this incoherence in Buber's thought, this essay attends to the rhetoric of verification ( Bewährung ), primarily but not solely in I and Thou (1923), both in order to show how it is a symptom of this incoherence, and also to show a broad pragmatic strain in Buber's thought. Given this pragmatic (...)
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  15.  20
    Verification Principle and Testability Principle.Lev D. Lamberov - 2024 - Epistemology and Philosophy of Science 61 (1):152-168.
    The paper deals with the conception of logical empiricism developed by Eino Kaila. Eino Kaila, being a thinker close to the Vienna Circle, departs from some of the central ideas of logical positivism. He identifies a limited number of problems in metaphysics that are meaningful and need to be solved, but he declares the rest of metaphysics to be a logical fallacy. For Eino Kaila, it is not the principle of verification (as a criterion of meaning) but the principle (...)
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  16.  32
    Verification and Validation of Simulations Against Holism.Julie Jebeile & Vincent Ardourel - 2019 - Minds and Machines 29 (1):149-168.
    It has been argued that the Duhem problem is renewed with computational models since model assumptions having a representational aim and computational assumptions cannot be tested in isolation. In particular, while the Verification and Validation methodology is supposed to prevent such holism, Winsberg argues that verification and validation cannot be separated in practice. Morrison replies that Winsberg overstates the entanglement between the steps. The paper aims at arbitrating these two positions, by stressing their respective validity in relation to (...)
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  17. Handwritten Signature Verification using Deep Learning. [REVIEW]Eman Alajrami, Belal A. M. Ashqar, Bassem S. Abu-Nasser, Ahmed J. Khalil, Musleh M. Musleh, Alaa M. Barhoom & Samy S. Abu-Naser - manuscript
    Every person has his/her own unique signature that is used mainly for the purposes of personal identification and verification of important documents or legal transactions. There are two kinds of signature verification: static and dynamic. Static(off-line) verification is the process of verifying an electronic or document signature after it has been made, while dynamic(on-line) verification takes place as a person creates his/her signature on a digital tablet or a similar device. Offline signature verification is not (...)
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  18.  30
    Progression and Verification of Situation Calculus Agents with Bounded Beliefs.Giuseppe De Giacomo, Yves Lespérance, Fabio Patrizi & Stavros Vassos - 2016 - Studia Logica 104 (4):705-739.
    We investigate agents that have incomplete information and make decisions based on their beliefs expressed as situation calculus bounded action theories. Such theories have an infinite object domain, but the number of objects that belong to fluents at each time point is bounded by a given constant. Recently, it has been shown that verifying temporal properties over such theories is decidable. We take a first-person view and use the theory to capture what the agent believes about the domain of interest (...)
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  19. Experimental verification of an Aharonov-Bohm effect in rotating reference frames.Mark D. Semon - 1982 - Foundations of Physics 12 (1):49-57.
    A thought experiment is reviewed which shows two things. First, in a region of a rotating frame that is not simply connected, the inertial forces can be canceled without completely canceling the inertial vector potential (whose curl determines the Coriolis force); second, the presence of this uncanceled potential can be detected in a quantum interference experiment. It is then argued that the thought experiment was realized in an earlier experiment involving a rotating superconductor, and that the experimental results confirm the (...)
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  20.  19
    Source Domain Verification Using Corpus-based Tools.Kathleen Ahrens & Menghan Jiang - 2020 - Metaphor and Symbol 35 (1):43-55.
    Source domain verification has not received as much attention as criteria for metaphor identification in the study of conceptual metaphor. In this paper, we provide a replicable approach to source...
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  21.  88
    Analogy, verification, and other minds.J. W. Meiland - 1966 - Mind 75 (October):564-568.
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  22. Constructive Verification, Empirical Induction, and Falibilist Deduction: A Threefold Contrast.Julio Michael Stern - 2011 - Information 2 (4):635-650.
    This article explores some open questions related to the problem of verification of theories in the context of empirical sciences by contrasting three epistemological frameworks. Each of these epistemological frameworks is based on a corresponding central metaphor, namely: (a) Neo-empiricism and the gambling metaphor; (b) Popperian falsificationism and the scientific tribunal metaphor; (c) Cognitive constructivism and the object as eigen-solution metaphor. Each of one of these epistemological frameworks has also historically co-evolved with a certain statistical theory and method for (...)
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  23.  21
    Verification logic: An arithmetical interpretation for negative introspection.Juan Pablo Aguilera & David Fernández-Duque - 2016 - In Lev Beklemishev, Stéphane Demri & András Máté (eds.), Advances in Modal Logic, Volume 11. CSLI Publications. pp. 1-20.
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  24. Program verification within and without logic.Hajnal Andreka, Istvan Nemeti & Ildiko Sain - 1979 - Bulletin of the Section of Logic 8 (3):124-128.
    Theorem 1 states a negative result about the classical semantics j= ! of program schemes. Theorem 2 investigates the reason for this. We conclude that Theorem 2 justies the Henkin-type semantics j= for which the opposite of the present Theorem 1 was proved in [1]{[3] and also in a dierent form in part III of [5]. The strongest positive result on j= is Corollary 6 in [3].
     
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  25. SOCIAL VERIFICATION – HUMAN DIMENSONS OF THEORETICAL SCIENCE AND HIGH-TECH (CASUS BIOETHICS). Part Two.Valentin Cheshko & Yulia Kosova - 2011 - Practical Philosophy 2:46-55.
    The new phase of science evolution is characterized by totality of subject and object of cognition and technology (high-hume). As a result, forming of network structure in a disciplinary matrix modern are «human dimensional» natural sciences and two paradigmal «nuclei» (attraktors). As a result, the complication of structure of disciplinary matrix and forming a few paradigm nuclei in modern «human dimensional» natural sciences are observed.
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  26.  56
    Verification and Variation: Patterns of Experimentation in Investigations of Galvanism in Germany, 1790–1800.Maria Trumpler - 1997 - Philosophy of Science 64 (4):84.
    Based on the historical case of galvanic experimentation in Germany, I identify five types of experimentation which explored and shaped the new phenomenon rather than tested theoretical predictions. Verification evaluated initial reports of Galvani's phenomenon. Simplification reduced the experimental protocol to the fewest and most basic steps. Optimization found experimental conditions that magnified the observed effect. Exploration tested a wide variety of metals, animals or configurations. Application modified the experiment to address unresolved related problems. Attempts to derive laws of (...)
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  27. Computer verification for historians of philosophy.Landon D. C. Elkind - 2022 - Synthese 200 (3):1-28.
    Interactive theorem provers might seem particularly impractical in the history of philosophy. Journal articles in this discipline are generally not formalized. Interactive theorem provers involve a learning curve for which the payoffs might seem minimal. In this article I argue that interactive theorem provers have already demonstrated their potential as a useful tool for historians of philosophy; I do this by highlighting examples of work where this has already been done. Further, I argue that interactive theorem provers can continue to (...)
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  28.  1
    Indirect Verification and Historical Inquiry as a Parasitic Epistemic Practice.Jong–pil Yoon - 2024 - Contemporary Pragmatism 21 (4):357-380.
    This paper explores indirect verification in pragmatism and its impact on historical inquiry. Indirect verification, as articulated by William James and John Dewey, addresses the challenge of historical knowledge within pragmatism by confirming ideas about past events based on the consistency among their present effects, the ideas themselves, and anticipated future consequences. The paper identifies and discusses key challenges related to indirect verification, such as the ‘coherence verification fallacy,’ the ‘dilemma of interpreting historical consequences,’ and the (...)
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  29.  35
    Proof verification and proof discovery for relativity.Naveen Sundar Govindarajalulu, Selmer Bringsjord & Joshua Taylor - 2015 - Synthese 192 (7):2077-2094.
    The vision of machines autonomously carrying out substantive conjecture generation, theorem discovery, proof discovery, and proof verification in mathematics and the natural sciences has a long history that reaches back before the development of automatic systems designed for such processes. While there has been considerable progress in proof verification in the formal sciences, for instance the Mizar project’ and the four-color theorem, now machine verified, there has been scant such work carried out in the realm of the natural (...)
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  30.  42
    Verification of concurrent programs: the automata-theoretic framework.Moshe Y. Vardi - 1991 - Annals of Pure and Applied Logic 51 (1-2):79-98.
    Vardi, M.Y., Verification of concurrent programs: the automata-theoretic framework, Annals of Pure and Applied Logic 51 79–98. We present an automata-theoretic framework to the verification of concurrent and nondeterministic programs. The basic idea is that to verify that a program P is correct one writes a program A that receives the computation of P as input and diverges only on incorrect computations of P. Now P is correct if and only if a program PA, obtained by combining P (...)
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  31.  79
    Verification, falsification, and cancellation in ${\rm KT}$.Timothy Williamson - 1990 - Notre Dame Journal of Formal Logic 31 (2):286-290.
    The main result of this paper is that KT is closed under a cancellation principle. This result extends to KTG1, but it does not extend to modal systems associated with the provability interpretation of L, such as KW and KT4Grz. Following Williamson, these results are applied to philosophical concerns about the proper form for theories of meaning, via the interpretation of L as some kind of veriflability. The cancellation principle can then be read as saying that verifilability conditions and falsiflability (...)
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  32.  43
    B. “verification” of statements in psychiatry.P. H. Esser - 1956 - Synthese 10 (1):373-377.
    (1) It remains to be seen if in the field of Psychiatry just as in that of Psychology the verbal output of a subject can be submitted to verification. Many statements of a highly emotional character being merely symptoms of certain dispositions have no direct communicative sense at all.(2) It being one of the characteristics of the mentally ill to loose contact and exchange of ideas with other people, the question naturally suggests itself if this symptom may be at (...)
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  33.  7
    Verification of a model for in-reactor creep transients in zirconium.S. R. Macewen & V. Fidleris - 1975 - Philosophical Magazine 31 (5):1149-1157.
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  34.  46
    Deductive program verification (a practitioner's commentary).David A. Nelson - 1992 - Minds and Machines 2 (3):283-307.
    A proof of ‘correctness’ for a mathematical algorithm cannot be relevant to executions of a program based on that algorithm because both the algorithm and the proof are based on assumptions that do not hold for computations carried out by real-world computers. Thus, proving the ‘correctness’ of an algorithm cannot establish the trustworthiness of programs based on that algorithm. Despite the (deceptive) sameness of the notations used to represent them, the transformation of an algorithm into an executable program is a (...)
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  35.  18
    Speaker Verification Under Degraded Conditions Using Empirical Mode Decomposition Based Voice Activity Detection Algorithm.R. Kumaraswamy, V. Kamakshi Prasad & M. S. Rudramurthy - 2014 - Journal of Intelligent Systems 23 (4):359-378.
    The performance of most of the state-of-the-art speaker recognition systems deteriorates under degraded conditions, owing to mismatch between the training and testing sessions. This study focuses on the front end of the speaker verification system to reduce the mismatch between training and testing. An adaptive voice activity detection algorithm using zero-frequency filter assisted peaking resonator was integrated into the front end of the SV system. The performance of this proposed SV system was studied under degraded conditions with 50 selected (...)
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  36.  96
    Program Verification and Functioning of Operative Computing Revisited: How about Mathematics Engineering? [REVIEW]Uri Pincas - 2011 - Minds and Machines 21 (2):337-359.
    The issue of proper functioning of operative computing and the utility of program verification, both in general and of specific methods, has been discussed a lot. In many of those discussions, attempts have been made to take mathematics as a model of knowledge and certitude achieving, and accordingly infer about the suitable ways to handle computing. I shortly review three approaches to the subject, and then take a stance by considering social factors which affect the epistemic status of both (...)
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  37.  68
    Eschatological verification and personal identity.Robert Audi - 1976 - International Journal for Philosophy of Religion 7 (4):391 - 408.
  38.  56
    Verification of face identities from images captured on video.Vicki Bruce, Zoë Henderson, Karen Greenwood, Peter J. B. Hancock, A. Mike Burton & Paul Miller - 1999 - Journal of Experimental Psychology: Applied 5 (4):339.
  39.  74
    On verification of the expressions of many-valued sentential calculi. I.Edward Baŀuka - 1965 - Studia Logica 17 (1):53 - 73.
  40. La vérification.Gilles-Gaston Granger - 1993 - Revue Philosophique de la France Et de l'Etranger 183 (3):633-636.
     
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  41.  13
    The verification of standards of value.Thomas Munro - 1922 - Journal of Philosophy 19 (11):294-301.
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  42.  12
    Verification in incomplete argumentation frameworks.Dorothea Baumeister, Daniel Neugebauer, Jörg Rothe & Hilmar Schadrack - 2018 - Artificial Intelligence 264 (C):1-26.
  43.  22
    Probabilistic verification and approximation.Richard Lassaigne & Sylvain Peyronnet - 2008 - Annals of Pure and Applied Logic 152 (1):122-131.
    We study the existence of efficient approximation methods to verify quantitative specifications of probabilistic systems. Models of such systems are labelled discrete time Markov chains and checking specifications consists of computing satisfaction probabilities of linear temporal logic formulas. We prove that, in general, there is no polynomial time randomized approximation scheme with relative error for probabilistic verification. However, in many applications, specifications can be expressed by monotone formulas or negation of monotone formulas and randomized approximation schemes with absolute error (...)
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  44.  59
    Verification and Inferentialism in Wittgenstein's Philosophy.José Medina - 2001 - Philosophical Investigations 24 (4):304-313.
  45.  26
    Should Validation and Verification be Separated Strictly?Claus Beisbart - 2019 - In Claus Beisbart & Nicole J. Saam (eds.), Computer Simulation Validation: Fundamental Concepts, Methodological Frameworks, and Philosophical Perspectives. Springer Verlag. pp. 1005-1028.
    Verification and validation are methods with which computer simulations are tested. While many practitioners draw a clear line between verification and validation and demand that the former precedes the latter, some philosophers have suggested that the distinction has been over-exaggerated. This chapter clarifies the relationship between verification and validation. Regarding the latter, validation of the conceptual and of the computational modelComputational model are distinguished. I argue that, as a method, verification is clearly different from validation of (...)
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  46. Theistic Verification'in 77k.David A. Pailin - 1971 - In Dow Kirkpatrick (ed.), The living God. Nashville,: Abingdon Press.
  47. Epistemic verification of anonymity.Jan van Eijck - unknown
    Model checking techniques for communication protocols usually are phrased in terms of processes, basically labelled arcs in a labelled transition system. We propose to lift checking for such protocols to a more abstract level by analysing the protocols as composite communicative actions, with a communicative action viewed as a mapping on an appropriate class of epistemic models. As an example, we analyse an anonymous broadcast protocol (Chaum’s well-known dining cryptographers protocol) and an electronic voting protocol.
     
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  48.  12
    Verification of knowledge bases based on containment checking.Alon Y. Levy & Marie-Christine Rousset - 1998 - Artificial Intelligence 101 (1-2):227-250.
  49.  35
    Verification: Validity or Understanding.Kenneth J. Shapiro - 1986 - Journal of Phenomenological Psychology 17 (2):167-179.
  50. Verification and Falsification of Modellings Towards an Understanding of Auditive Sensomotorics.Hans J. Gerhardt - 1995 - In Heinz Lübbig (ed.), The Inverse Problem: Symposium Ad Memoriam Hermann von Helmholtz. Wiley-Vch. pp. 143.
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