Results for ' Automated Reasoning'

972 found
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  1.  23
    Automated reasoning in normative detachment structures with ideal conditions.Tomer Libal & Matteo Pascucci - 2019 - In Tomer Libal & Matteo Pascucci (eds.), ICAIL: International Conference on Artificial Intelligence and Law. ACM. pp. 63-72.
    In this article we introduce a logical structure for normative reasoning, called Normative Detachment Structure with Ideal Conditions, that can be used to represent the content of certain legal texts in a normalized way. The structure exploits the deductive properties of a system of bimodal logic able to distinguish between ideal and actual normative statements, as well as a novel formalization of conditional normative statements able to capture interesting cases of contrary-to-duty reasoning and to avoid deontic paradoxes. Furthermore, (...)
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  2. Automated Reasoning with Analytic Tableaux and Related Methods: TABLEAUX 2021.Anupam Das & Sara Negri (eds.) - 2021
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  3.  41
    Automated reasoning in modal logics: A framework with applications.Branden Fitelson - manuscript
    The principle that every truth is possibly necessary can now be shown to entail that every truth is necessary by a chain of elementary inferences in a perspicuous notation unavailable to Hegel. —Williamson [5, p.
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  4.  31
    Towards the use of automated reasoning in discourse disambiguation.Claire Gardent & Bonnie Webber - 2001 - Journal of Logic, Language and Information 10 (4):487-509.
    In this paper, we claim that the disambiguation ofreferring expressions in discourse can be formulated in terms automatedreasoners can address. Specifically, we show that consistency,informativity and minimality are criteria which (i) can be implementedusing automated reasoning tools and (ii) can be used to disambiguatenoun-noun compounds, metonymy and definite descriptions.
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  5.  36
    Automated Reasoning for Conditional Logics: the Theorem Prover Condlean 3.1.Nicola Olivetti & Gian Luca Pozzato - 2007 - In Jean-Yves Béziau & Alexandre Costa-Leite (eds.), Perspectives on Universal Logic. Milan, Italy: Polimetrica.
  6.  27
    Automated Reasoning with Complex Ethical Theories--A Case Study Towards Responsible AI.David Fuenmayor & Christoph Benzmüller - unknown
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  7.  88
    Finding missing proofs with automated reasoning.Branden Fitelson & Larry Wos - 2001 - Studia Logica 68 (3):329-356.
    This article features long-sought proofs with intriguing properties (such as the absence of double negation and the avoidance of lemmas that appeared to be indispensable), and it features the automated methods for finding them. The theorems of concern are taken from various areas of logic that include two-valued sentential (or propositional) calculus and infinite-valued sentential calculus. Many of the proofs (in effect) answer questions that had remained open for decades, questions focusing on axiomatic proofs. The approaches we take are (...)
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  8.  15
    Automated reasoning about machines.Andrew Gelsey - 1995 - Artificial Intelligence 74 (1):1-53.
  9. Resolution Modal logics-Automated reasoning in nonclassical logic.L. Farifias del Cerro - forthcoming - Logique Et Analyse.
  10. Automated Reasoning-The Representation of Multiplication Operation on Fuzzy Numbers and Application to Solving Fuzzy Multiple Criteria Decision Making Problems.Chien-Chang Chou - 2006 - In O. Stock & M. Schaerf (eds.), Lecture Notes In Computer Science. Springer Verlag. pp. 4099--161.
     
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  11. Automating Reasoning with Standpoint Logic via Nested Sequents.Tim Lyon & Lucía Gómez Álvarez - 2018 - In Michael Thielscher, Francesca Toni & Frank Wolter (eds.), Proceedings of the Sixteenth International Conference on Principles of Knowledge Representation and Reasoning (KR2018). pp. 257-266.
    Standpoint logic is a recently proposed formalism in the context of knowledge integration, which advocates a multi-perspective approach permitting reasoning with a selection of diverse and possibly conflicting standpoints rather than forcing their unification. In this paper, we introduce nested sequent calculi for propositional standpoint logics---proof systems that manipulate trees whose nodes are multisets of formulae---and show how to automate standpoint reasoning by means of non-deterministic proof-search algorithms. To obtain worst-case complexity-optimal proof-search, we introduce a novel technique in (...)
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  12.  39
    Axiomatic proofs through automated reasoning.Branden Fitelson & Larry Wos - 2000 - Bulletin of the Section of Logic 29 (3):125-36.
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  13. International Joint Conference on Automated Reasoning (IJCAR'2001), June 18-23, 2001, Siena, Italy.F. Massacci - 1999 - In P. Brezillon & P. Bouquet (eds.), Lecture Notes in Artificial Intelligence. Springer.
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  14.  44
    A survey of requirements for automated reasoning services for bio-ontologies in OWL.M. Scott Marshall, C. Maria Keet & Marco Roos - unknown
    There are few successful applications of automated reasoning over OWL-formalised bio-ontologies, and requirements are often unclearly formulated. Of what is available, usage and prospective scenarios of automated reasoning is often different from the straightforward classification and satisfiability. We list nine types of scenarios and specify the requirements in more detail. Several of these requirements are already possible in practice or at least in theory, others are in need of further research, in particular regarding the linking of (...)
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  15.  73
    Non-standard logics for automated reasoning.Philippe Smets (ed.) - 1988 - San Diego: Academic Press.
    Although there are a few books available that give brief surveys of a variety of nonstandard logics, there is a growing need for a critical presentation providing both a greater depth and breadth of insight into these logics. This book assembles a wider and deeper view of the many potentially applicable logics. Three appendixes provide short tutorials on classical logic and modal logics, and give a brief introduction to the existing literature on the logical aspects of probability theory. These tutorials (...)
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  16. Short Papers Part-Automated Reasoning-Context-Aware Product Bundling Architecture in Ubiquitous Computing Environments.Hyun Jung Lee & Mye M. Sohn - 2006 - In O. Stock & M. Schaerf (eds.), Lecture Notes In Computer Science. Springer Verlag. pp. 901-906.
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  17.  9
    A new use of an automated reasoning assistant: Open questions in equivalential calculus and the study of infinite domains.L. Wos, S. Winker, B. Smith, R. Veroff & L. Henschen - 1984 - Artificial Intelligence 22 (3):303-356.
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  18.  55
    Review: John Arnold Kalman, Automated Reasoning with Otter. [REVIEW]Dale Myers - 2002 - Bulletin of Symbolic Logic 8 (3):428-429.
  19.  50
    (1 other version)The Automation of Sound Reasoning and Successful Proof Finding.Larry Wos & Branden Fitelson - 2002 - In Dale Jacquette (ed.), A Companion to Philosophical Logic. Malden, MA, USA: Wiley-Blackwell. pp. 707–723.
    This chapter contains sections titled: The Cutting Edge Automated Reasoning, Principles and Elements Significant Successes Myths, Mechanization, and Mystique.
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  20.  26
    Wos Larry. Automated reasoning: 33 basic research problems. Prentice Hall, Englewood Cliffs, N.J., 1988, xiii + 319 pp. [REVIEW]William M. Farmer - 1988 - Journal of Symbolic Logic 53 (4):1258-1259.
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  21.  15
    The scope and limits of simulation in automated reasoning.Ernest Davis & Gary Marcus - 2016 - Artificial Intelligence 233 (C):60-72.
  22.  79
    Non-standard logics for automated reasoning, edited by Philippe Smets, Abe Mamdani, Didier Dubois, and Henri Prade, Academic Press, London etc. 1988, x + 334 pp. [REVIEW]Charles G. Morgan - 1992 - Journal of Symbolic Logic 57 (1):277-281.
  23.  9
    Clause trees: a tool for understanding and implementing resolution in automated reasoning.J. D. Horton & Bruce Spencer - 1997 - Artificial Intelligence 92 (1-2):25-89.
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  24. Handbook of practical logic and automated reasoning.John Harrison - 2010 - Bulletin of Symbolic Logic 16 (2):279-281.
     
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  25.  27
    Larry Wos and Gail W. Pieper. A fascinating country in the world of computing—your guide to automated reasoning. World Scientific, Singapore, New Jersey, London, Hong Kong, 1999, 608 pp.L. Wos, G. W. Pieper & Robert K. Meyer - 2007 - Bulletin of Symbolic Logic 13 (3):359-361.
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  26.  33
    Combined reasoning by automated cooperation.Christoph Benzmüller, Volker Sorge, Mateja Jamnik & Manfred Kerber - 2008 - Journal of Applied Logic 6 (3):318-342.
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  27. Automating Agential Reasoning: Proof-Calculi and Syntactic Decidability for STIT Logics.Tim Lyon & Kees van Berkel - 2019 - In M. Baldoni, M. Dastani, B. Liao, Y. Sakurai & R. Zalila Wenkstern (eds.), PRIMA 2019: Principles and Practice of Multi-Agent Systems. Springer. pp. 202-218.
    This work provides proof-search algorithms and automated counter-model extraction for a class of STIT logics. With this, we answer an open problem concerning syntactic decision procedures and cut-free calculi for STIT logics. A new class of cut-free complete labelled sequent calculi G3LdmL^m_n, for multi-agent STIT with at most n-many choices, is introduced. We refine the calculi G3LdmL^m_n through the use of propagation rules and demonstrate the admissibility of their structural rules, resulting in auxiliary calculi Ldm^m_nL. In the single-agent case, (...)
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  28.  9
    John Harrison. Handbook of practical logic and automated reasoning. Cambridge University Press, Cambridge, UK, 2009, xix + 681 pp. [REVIEW]Alwen Tiu - 2010 - Bulletin of Symbolic Logic 16 (2):279-281.
  29.  3
    Thomas Piecha and Peter Schroeder-Heister. Incompleteness of Intuitionistic Propositional Logic with Respect to Proof-Theoretic Semantics. Studia Logica , vol. 107 (2019), no. 1, pp. 233–246. - Alexander V. Gheorghiu, Tao Gu and David J. Pym. Proof-Theoretic Semantics for Intuitionistic Multiplicative Linear Logic. Automated Reasoning with Analytic Tableaux and Related Methods, Revantha Ramanayake and Josef Urban, Lecture Notes in Computer Science, vol. 14278, Springer, Cham, pp. 367–385. - Hermógenes Oliveira. On Dummett’s Pragmatist Justification Procedure. Erkenntnis , vol. 86 (2021), no. 2, pp. 429–455. [REVIEW]Will Stafford - 2024 - Bulletin of Symbolic Logic 30 (3):427-431.
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  30.  44
    Larry Wos, Ross Overbeek, Ewing Lusk, and Jim Boyle. Automated reasoning. Introduction and applications. Second edition of LI 464. McGraw-Hill, New York etc. 1992, xvi + 656 pp. + disk. [REVIEW]Natarajan Shankar - 1994 - Journal of Symbolic Logic 59 (4):1437-1439.
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  31.  53
    Larry Wos, Ross Overbeek, Ewing Lusk, and Jim Boyle. Automated reasoning. Introduction and applications. Prentice-Hall, Inc., Englewood Cliffs, N.J., 1984, xiv + 482 pp. [REVIEW]Michael J. Beeson - 1986 - Journal of Symbolic Logic 51 (2):464-465.
  32.  38
    Model-based abductive reasoning in automated software testing.N. Angius - 2013 - Logic Journal of the IGPL 21 (6):931-942.
    Automated Software Testing (AST) using Model Checking is in this article epistemologically analysed in order to argue in favour of a model-based reasoning paradigm in computer science. Preliminarily, it is shown how both deductive and inductive reasoning are insufficient to determine whether a given piece of software is correct with respect to specified behavioural properties. Models algorithmically checked in Model Checking to select executions to be observed in Software Testing are acknowledged as analogical models which establish isomorphic (...)
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  33.  48
    Automated legal reasoning with discretion to act using s(LAW).Joaquín Arias, Mar Moreno-Rebato, Jose A. Rodriguez-García & Sascha Ossowski - 2024 - Artificial Intelligence and Law 32 (4):1141-1164.
    Automated legal reasoning and its application in smart contracts and automated decisions are increasingly attracting interest. In this context, ethical and legal concerns make it necessary for automated reasoners to justify in human-understandable terms the advice given. Logic Programming, specially Answer Set Programming, has a rich semantics and has been used to very concisely express complex knowledge. However, modelling discretionality to act and other vague concepts such as ambiguity cannot be expressed in top-down execution models based (...)
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  34.  43
    POLITICS: Automated Ideological Reasoning.Jaime G. Carbonell - 1978 - Cognitive Science 2 (1):27-51.
    POLITICS is a system of computer programs which simulates humans in comprehending and responding to world events from a given political or ideological perspective. The primary theoretical motivations were: (1) the implemention of a functional system which applies the knowledge structures of Schank and Abelson (1977) to the domain of simulating political belief systems; (2) the development of a tentative theory of intentional goal conflicts and counterplanning. Secondary goals of the POLITICS project include developing a representation for belief systems, investigating (...)
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  35.  10
    Automated model selection for simulation based on relevance reasoning.Alon Y. Levy, Yumi Iwasaki & Richard Fikes - 1997 - Artificial Intelligence 96 (2):351-394.
  36.  50
    On automating diagrammatic proofs of arithmetic arguments.Mateja Jamnik, Alan Bundy & Ian Green - 1999 - Journal of Logic, Language and Information 8 (3):297-321.
    Theorems in automated theorem proving are usually proved by formal logical proofs. However, there is a subset of problems which humans can prove by the use of geometric operations on diagrams, so called diagrammatic proofs. Insight is often more clearly perceived in these proofs than in the corresponding algebraic proofs; they capture an intuitive notion of truthfulness that humans find easy to see and understand. We are investigating and automating such diagrammatic reasoning about mathematical theorems. Concrete, rather than (...)
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  37. Automating Leibniz's Theory of Concepts.Paul Edward Oppenheimer, Jesse Alama & Edward N. Zalta - 2015 - In Felty Amy P. & Middeldorp Aart (eds.), Automated Deduction – CADE 25: Proceedings of the 25th International Conference on Automated Deduction (Lecture Notes in Artificial Intelligence: Volume 9195), Berlin: Springer. Springer. pp. 73-97.
    Our computational metaphysics group describes its use of automated reasoning tools to study Leibniz’s theory of concepts. We start with a reconstruction of Leibniz’s theory within the theory of abstract objects (henceforth ‘object theory’). Leibniz’s theory of concepts, under this reconstruction, has a non-modal algebra of concepts, a concept-containment theory of truth, and a modal metaphysics of complete individual concepts. We show how the object-theoretic reconstruction of these components of Leibniz’s theory can be represented for investigation by means (...)
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  38. Automating Leibniz's Theory of Concepts.Jesse Alama, Paul Edward Oppenheimer & Edward Zalta - 2015 - In Felty Amy P. & Middeldorp Aart (eds.), Automated Deduction – CADE 25: Proceedings of the 25th International Conference on Automated Deduction (Lecture Notes in Artificial Intelligence: Volume 9195), Berlin: Springer. Springer. pp. 73-97.
    Our computational metaphysics group describes its use of automated reasoning tools to study Leibniz’s theory of concepts. We start with a reconstruction of Leibniz’s theory within the theory of abstract objects (henceforth ‘object theory’). Leibniz’s theory of concepts, under this reconstruction, has a non-modal algebra of concepts, a concept-containment theory of truth, and a modal metaphysics of complete individual concepts. We show how the object-theoretic reconstruction of these components of Leibniz’s theory can be represented for investigation by means (...)
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  39.  68
    Automation of Legal Reasoning: A Study on Artificial Intelligence and Law.Peter Wahlgren - 1992 - Kluwer Law and Taxation Publishers.
    This book provides an analysis of the development which has lead up to the formation of a joint field of artificial intelligence and law. It discusses the basic foundations and also addresses the future prospects of the discipline. The author formulates a design approach for advanced Artificial Intelligence systems for law, and concludes with a discussion about the potentialities and the consequences of future development.
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  40. Automating and computing paraconsistent reasoning: contraction-free, resolution and type systems.Norihiro Kamide - 2010 - Reports on Mathematical Logic:3-21.
     
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  41.  8
    POLITICS: Automated ideological reasoning.J. CarbonellJr - 1978 - Cognitive Science 2 (1):27-51.
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  42.  76
    A hybrid rule – neural approach for the automation of legal reasoning in the discretionary domain of family law in australia.Andrew Stranieri, John Zeleznikow, Mark Gawler & Bryn Lewis - 1999 - Artificial Intelligence and Law 7 (2-3):153-183.
    Few automated legal reasoning systems have been developed in domains of law in which a judicial decision maker has extensive discretion in the exercise of his or her powers. Discretionary domains challenge existing artificial intelligence paradigms because models of judicial reasoning are difficult, if not impossible to specify. We argue that judicial discretion adds to the characterisation of law as open textured in a way which has not been addressed by artificial intelligence and law researchers in depth. (...)
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  43.  23
    Embedding and Automating Conditional Logics in Classical Higher-Order Logic.Christoph Benzmüller, Dov Gabbay, Valerio Genovese & Daniele Rispoli - 2012 - Annals of Mathematics and Artificial Intelligence 66 (1-4):257-271.
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  44. Automated Influence and Value Collapse: Resisting the Control Argument.Dylan J. White - forthcoming - American Philosophical Quarterly.
    Automated influence is one of the most pervasive applications of artificial intelligence in our day-to-day lives, yet a thoroughgoing account of its associated individual and societal harms is lacking. By far the most widespread, compelling, and intuitive account of the harms associated with automated influence follows what I call the control argument. This argument suggests that users are persuaded, manipulated, and influenced by automated influence in a way that they have little or no control over. Based on (...)
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  45.  55
    Human-oriented and machine-oriented reasoning: Remarks on some problems in the history of Automated Theorem Proving. [REVIEW]Furio Di Paola - 1988 - AI and Society 2 (2):121-131.
    Examples in the history of Automated Theorem Proving are given, in order to show that even a seemingly ‘mechanical’ activity, such as deductive inference drawing, involves special cultural features and tacit knowledge. Mechanisation of reasoning is thus regarded as a complex undertaking in ‘cultural pruning’ of human-oriented reasoning. Sociological counterparts of this passage from human- to machine-oriented reasoning are discussed, by focusing on problems of man-machine interaction in the area of computer-assisted proof processing.
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  46.  32
    Automated inference in active logics.Michael Miller & Donald Perlis - 1996 - Journal of Applied Non-Classical Logics 6 (1):9-27.
    ABSTRACT Certain problems in commonsense reasoning lend themselves to the use of non-standard formalisms which we call active logics. Among these are problems of objects misidentification. In this paper we describe some technical issues connected with automated inference in active logics, using particular object misidentification problems as illustrations. Control of exponential growth of inferences is a key issue. To control this growth attention is paid to a limited version of an inference rule for negative introspection. We also present (...)
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  47.  58
    Automated deduction in a graphical temporal logic.L. E. Moser, P. M. Melliar-Smith, Y. S. Ramakrishna, G. Kutty & L. K. Dillon - 1996 - Journal of Applied Non-Classical Logics 6 (1):29-47.
    ABSTRACT Real-time graphical interval logic is a modal logic for reasoning about time in which the basic modality is the interval. The logic differs from other logics in that it has a natural intuitive graphical representation that resembles the timing diagrams drawn by system designers. We have developed an automted deduction system for the logic, which includes a theorem prover and a user interface. The theorem prover checks the validity of proofs in the logic and produces counterexamples to invalid (...)
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  48. Automated abduction in scientific discovery.Oliver Ray - 2007 - In L. Magnani & P. Li (eds.), Model-Based Reasoning in Science, Technology, and Medicine. Springer. pp. 103--116.
  49. Representing and reasoning over a taxonomy of part–whole relations.C. Maria Keet & Alessandro Artale - 2008 - Applied ontology 3 (1-2):91-110.
    Many types of part-whole relations have been proposed in the literature to aid the conceptual modeller to choose the most appropriate type, but many of those relations lack a formal specification to give clear and unambiguous semantics to them. To remedy this, a formal taxonomy of types of mereological and meronymic part-whole relations is presented that distinguishes between transitive and intransitive relations and the kind of entity types that are related. The demand to use it effectively brings afore new requirements (...)
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  50. Automated Influence and Value Collapse.Dylan J. White - 2024 - American Philosophical Quarterly 61 (4):369-386.
    Automated influence is one of the most pervasive applications of artificial intelligence in our day-to-day lives, yet a thoroughgoing account of its associated individual and societal harms is lacking. By far the most widespread, compelling, and intuitive account of the harms associated with automated influence follows what I call the control argument. This argument suggests that users are persuaded, manipulated, and influenced by automated influence in a way that they have little or no control over. Based on (...)
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