Results for 'verification'

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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. Blackwell. pp. 253.
     
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  2. Roland fraïssé.Et Sa Vérification Dans Certaines - 1968 - In Jean-Louis Destouches, Evert Willem Beth & Institut Henri Poincaré (eds.), Logic and foundations of science. Dordrecht,: D. Reidel.
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  3. 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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  4. 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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  5. 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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  6. 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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  7.  57
    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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  8.  44
    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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  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.  86
    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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  11.  15
    Formal verification, scientific code, and the epistemological heterogeneity of computational science.Cyrille Imbert & Vincent Ardourel - unknown
    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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  12. 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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  13.  7
    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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  14.  70
    Analogy, verification, and other minds.J. W. Meiland - 1966 - Mind 75 (October):564-568.
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  15.  16
    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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  16.  42
    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.
  17. The verification principle: Another puncture--another patch.Crispin Wright - 1989 - Mind 98 (392):611-622.
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  18.  26
    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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  19. 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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  20.  24
    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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  21. 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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  22.  4
    Verification in incomplete argumentation frameworks.Dorothea Baumeister, Daniel Neugebauer, Jörg Rothe & Hilmar Schadrack - 2018 - Artificial Intelligence 264 (C):1-26.
  23.  29
    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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  24.  24
    Verification and Strategy Synthesis for Coalition Announcement Logic.Natasha Alechina, Hans van Ditmarsch, Rustam Galimullin & Tuo Wang - 2021 - Journal of Logic, Language and Information 30 (4):671-700.
    Coalition announcement logic is one of the family of the logics of quantified announcements. It allows us to reason about what a coalition of agents can achieve by making announcements in the setting where the anti-coalition may have an announcement of their own to preclude the former from reaching its epistemic goals. In this paper, we describe a PSPACE-complete model checking algorithm for CAL that produces winning strategies for coalitions. The algorithm is implemented in a proof-of-concept model checker.
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  25.  25
    Model Verification and the Likelihood Principle.Samuel C. Fletcher - unknown
    The likelihood principle is typically understood as a constraint on any measure of evidence arising from a statistical experiment. It is not sufficiently often noted, however, that the LP assumes that the probability model giving rise to a particular concrete data set must be statistically adequate—it must “fit” the data sufficiently. In practice, though, scientists must make modeling assumptions whose adequacy can nevertheless then be verified using statistical tests. My present concern is to consider whether the LP applies to these (...)
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  26.  71
    Eschatological Verification Reconsidered.John Hick - 1977 - Religious Studies 13 (2):189 - 202.
    The world in which we find ourselves is religiously ambiguous. It is possible for different people to experience it both religiously and non-religiously; and to hold beliefs which arise from and feed into each of these ways of experiencing. A religious man may report that in moments of prayer he is conscious of existing in the unseen presence of God, and is aware - sometimes at least - that his whole life and the entire history of the world is taking (...)
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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. Self-verification: The search for coherence.William B. Swann Jr, Peter J. Rentfrow & Jennifer S. Guinn - 2003 - In Mark R. Leary & June Price Tangney (eds.), Handbook of Self and Identity. Guilford Press. pp. 367.
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  29.  44
    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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  30.  48
    Verification and Inferentialism in Wittgenstein's Philosophy.José Medina - 2001 - Philosophical Investigations 24 (4):304-313.
  31.  57
    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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  32.  6
    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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    Gender verification issues in women’s competitive sports: An ethical critique of the iaaf dsd regulation.Mizuho Takemura - 2020 - Sport, Ethics and Philosophy 14 (4):449-460.
    In 2018 the World Heath Organization decided to re-examine the classification of gender identity disorder and exclude it from being defined as a mental illness. This re-examination means that sex a...
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  34. The verification of historical theses.Alan Donagan - 1956 - Philosophical Quarterly 6 (24):193-208.
  35.  10
    Statement verification: A stochastic model of judgment and response.Thomas S. Wallsten & Claudia González-Vallejo - 1994 - Psychological Review 101 (3):490-504.
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  36.  57
    Verification.I. Berlin - 1939 - Proceedings of the Aristotelian Society 39:225 - 248.
  37.  38
    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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  38.  13
    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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  39.  8
    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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  40.  9
    Parameterised verification for multi-agent systems.Panagiotis Kouvaros & Alessio Lomuscio - 2016 - Artificial Intelligence 234 (C):152-189.
  41.  56
    VIII.—Verification and Understanding.Margaret MacDonald - 1934 - Proceedings of the Aristotelian Society 34 (1):143-156.
  42.  68
    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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  43. The Verification Principle.Gilbert Ryle - 1951 - Revue Internationale de Philosophie 5 (3/4=17/18):243.
  44.  12
    Automatic verification of multi-agent systems by model checking via ordered binary decision diagrams.Franco Raimondi & Alessio Lomuscio - 2007 - Journal of Applied Logic 5 (2):235-251.
  45. 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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  46.  13
    Experimental Verification of Optimized Multiscroll Chaotic Oscillators Based on Irregular Saturated Functions.J. M. Muñoz-Pacheco, D. K. Guevara-Flores, O. G. Félix-Beltrán, E. Tlelo-Cuautle, J. E. Barradas-Guevara & C. K. Volos - 2018 - Complexity 2018:1-17.
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  47.  34
    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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  48.  9
    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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  49.  15
    A verification framework for agent programming with declarative goals.F. S. de Boer, K. V. Hindriks, W. van der Hoek & J. -J. Ch Meyer - 2007 - Journal of Applied Logic 5 (2):277-302.
  50.  8
    Approximate verification of strategic abilities under imperfect information.Wojciech Jamroga, Michał Knapik, Damian Kurpiewski & Łukasz Mikulski - 2019 - Artificial Intelligence 277 (C):103172.
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