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  1. Situated Nonmonotonic Temporal Reasoning with BABY-SIT.Varol Akman - manuscript
    gramming environment, BABY-SIT, which is based on situation theory. We then demonstrate how problems requir-.
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  2. Preference-Based Belief Revision for Rule-Based Agents.Natasha Alechina, Mark Jago & Brian Logan - 2008 - Synthese 165 (2):159-177.
    Agents which perform inferences on the basis of unreliable information need an ability to revise their beliefs if they discover an inconsistency. Such a belief revision algorithm ideally should be rational, should respect any preference ordering over the agent’s beliefs (removing less preferred beliefs where possible) and should be fast. However, while standard approaches to rational belief revision for classical reasoners allow preferences to be taken into account, they typically have quite high complexity. In this paper, we consider belief revision (...)
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  3. Logic, Reasoning and Revision.Patrick Allo - 2016 - Theoria 82 (1):3-31.
    The traditional connection between logic and reasoning has been under pressure ever since Gilbert Harman attacked the received view that logic yields norms for what we should believe. In this article I first place Harman's challenge in the broader context of the dialectic between logical revisionists like Bob Meyer and sceptics about the role of logic in reasoning like Harman. I then develop a formal model based on contemporary epistemic and doxastic logic in which the relation between logic and norms (...)
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  4. Adaptive Logic as a Modal Logic.Patrick Allo - 2013 - Studia Logica 101 (5):933-958.
    Modal logics have in the past been used as a unifying framework for the minimality semantics used in defeasible inference, conditional logic, and belief revision. The main aim of the present paper is to add adaptive logics, a general framework for a wide range of defeasible reasoning forms developed by Diderik Batens and his co-workers, to the growing list of formalisms that can be studied with the tools and methods of contemporary modal logic. By characterising the class of abnormality models, (...)
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  5. Local Information and Adaptive Consequence.Patrick Allo - 2006 - Logique Et Analyse 149:461-488.
    In this paper we provide a formal description of what it means to be in a local or partial information-state. Starting from the notion of locality in a relational structure, we define so-called adaptive gen- erated submodels. The latter are then shown to yield an adaptive logic wherein the derivability of Pφ is naturally interpreted as a core property of being in a state in which one holds the information that φ.
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  6. Non-Monotonic Logic.G. Aldo Antonelli - 2008 - Stanford Encyclopedia of Philosophy.
    The term "non-monotonic logic" covers a family of formal frameworks devised to capture and represent defeasible inference , i.e., that kind of inference of everyday life in which reasoners draw conclusions tentatively, reserving the right to retract them in the light of further information. Such inferences are called "non-monotonic" because the set of conclusions warranted on the basis of a given knowledge base does not increase (in fact, it can shrink) with the size of the knowledge base itself. This is (...)
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  7. Review: Dov M. Gabbay, C. J. Hogger, J. A. Robinson, D. Nute, Handbook of Logic in Artificial Intelligence and Logic Programming, Volume 3, Nonmonotonic Reasoning and Uncertain Reasoning. [REVIEW]G. Aldo Antonelli - 2000 - Bulletin of Symbolic Logic 6 (4):480-484.
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  8. REVIEWS-Nonmonotonic Reasoning.G. Antoniou & Marek A. Suchenek - 2000 - Bulletin of Symbolic Logic 6 (4):484-489.
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  9. Nonmonotonic Reasoning.Grigoris Antoniou - 2001 - Studia Logica 67 (1):144-146.
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  10. Partiality and Non-Monmotonicity in Classical Logic.van Jfak Benthem - 1986 - Logique Et Analyse 29:251-273.
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  11. Simple Hyperintensional Belief Revision.F. Berto - forthcoming - Erkenntnis:1-17.
    I present a possible worlds semantics for a hyperintensional belief revision operator, which reduces the logical idealization of cognitive agents affecting similar operators in doxastic and epistemic logics, as well as in standard AGM belief revision theory. belief states are not closed under classical logical consequence; revising by inconsistent information does not perforce lead to trivialization; and revision can be subject to ‘framing effects’: logically or necessarily equivalent contents can lead to different revisions. Such results are obtained without resorting to (...)
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  12. Impossible Worlds and the Logic of Imagination.Francesco Berto - 2017 - Erkenntnis 82 (6):1277-1297.
    I want to model a finite, fallible cognitive agent who imagines that p in the sense of mentally representing a scenario—a configuration of objects and properties—correctly described by p. I propose to capture imagination, so understood, via variably strict world quantifiers, in a modal framework including both possible and so-called impossible worlds. The latter secure lack of classical logical closure for the relevant mental states, while the variability of strictness captures how the agent imports information from actuality in the imagined (...)
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  13. Probabilistic Logic Under Coherence, Model-Theoretic Probabilistic Logic, and Default Reasoning in SystemP.Veronica Biazzo, Angelo Gilio, Thomas Lukasiewicz & Giuseppe Sanfilippo - 2002 - Journal of Applied Non-Classical Logics 12 (2):189-213.
    We study probabilistic logic under the viewpoint of the coherence principle of de Finetti. In detail, we explore how probabilistic reasoning under coherence is related to model- theoretic probabilistic reasoning and to default reasoning in System . In particular, we show that the notions of g-coherence and of g-coherent entailment can be expressed by combining notions in model-theoretic probabilistic logic with concepts from default reasoning. Moreover, we show that probabilistic reasoning under coherence is a generalization of default reasoning in System (...)
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  14. Propositional Plausible Logic: Introduction and Implementation.David Billington & Andrew Rock - 2001 - Studia Logica 67 (2):243-269.
    Plausible Logic allows defeasible deduction with arbitrary propositions, and yet when sufficiently simplified it is very similar to the Defeasible Logics of Billington and Nute. This paper presents Plausible Logic, explains some of the ideas behind the definitions, applies Plausible Logic to an example, and proves a coherence result which indicates that Plausible Logic is well behaved. We also report the first complete implementation of propositional Plausible Logic. The implementation has a web interface which makes it available to researchers and (...)
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  15. A Logical Theory of Nonmonotonic Inference and Belief Change.Alexander Bochman - 2001 - Springer.
    This is the first book that integrates nonmonotonic reasoning and belief change into a single framework from an artificial intelligence logic point-of-view.
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  16. Belief Contraction as Nonmonotonic Inference.Alexander Bochman - 2000 - Journal of Symbolic Logic 65 (2):605-626.
    A notion of an epistemic state is introduced as a generalization of common representations suggested for belief change. Based on it, a new kind of nonmonotonic inference relation corresponding to belief contractions is defined. A number of representation results is established that cover both traditional AGM contractions and contractions that do not satisfy recovery.
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  17. Modelling Belief Revision Via Belief Bases Using Situation Semantics.Ayse Sena Bozdag - 2017 - Dissertation, Bogazici University
    The belief base approach to belief representation and belief dynamics is developed as an alternative to the belief set approaches, which are pioneered by the AGM model. The belief base approach models collections of information and expectations of an agent as possibly incomplete and possibly inconsistent foundations for her beliefs. Nevertheless, the beliefs of an agent are always consistent; this is ensured by a sophisticated inference relation. Belief changes take place on the information base instead of on the belief set, (...)
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  18. Nonmonotonic Reasoning: An Overview.Gerhard Brewka, Jurgen Dix & Kurt Konolige - 1997 - Center for the Study of Language and Inf.
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  19. A Power Algebra for Theory Change.K. Britz - 1999 - Journal of Logic, Language and Information 8 (4):429-443.
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  20. Review of Jaap Hage's Law and Defeasibility. [REVIEW]Eugenio Bulygin - 2003 - Artificial Intelligence and Law 11 (2-3):245-250.
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  21. Nonmonotonic Reasoning , Argumentation and Machine Learning 1 Introduction.Peter Clark - 1990 - Argumentation:1-11.
    Machine learning and nonmonotonic reasoning are closely related, both concerned with making plausible as well as certain inferences based on available data. In this document a brief overview of different approaches to nonmonotonic reasoning is presented, and it is shown how the concept of argumentation systems arises. The relationship with machine learning work is also discussed. The document aims to highlight the links between nonmonotonic reasoning, argumentation and machine learning and as a result propose some potentially useful directions for new (...)
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  22. The Threshold-Versus-Duration Curve is Nonmonotonic.Thomas R. Corwin - 1984 - Bulletin of the Psychonomic Society 22 (5):441-442.
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  23. A Correction to “Nonmonotonic Inconsistency” [Artificial Intelligence 149 (2003) 161–178].Charles B. Cross - 2004 - Artificial Intelligence 160 (1-2):191-192.
    This note corrects an error in the statement and proof of Propositions 9 and 10 of [C. Cross, Nonmonotonic inconsistency, Artificial Intelligence 149 (2) (2003) 161–178]. Both results turn out to depend on the postulate of Consistency Preservation.
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  24. Nonmonotonic Inconsistency.Charles B. Cross - 2003 - Artificial Intelligence 149 (2):161-178.
    Nonmonotonic consequence is the subject of a vast literature, but the idea of a nonmonotonic counterpart of logical inconsistency—the idea of a defeasible property representing internal conflict of an inductive or evidential nature—has been entirely neglected. After considering and dismissing two possible analyses relating nonmonotonic consequence and a nonmonotonic counterpart of logical inconsistency, this paper offers a set of postulates for nonmonotonic inconsistency, an analysis of nonmonotonic inconsistency in terms of nonmonotonic consequence, and a series of results showing that nonmonotonic (...)
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  25. Belief Revision, Non-Monotonic Reasoning, and the Ramsey Test.Charles B. Cross - 1990 - In Kyburg Henry E., Loui Ronald P. & Carlson Greg N. (eds.), Knowledge Representation and Defeasible Reasoning. Kluwer Academic Publishers. pp. 223--244.
    Peter Gärdenfors has proved (Philosophical Review, 1986) that the Ramsey rule and the methodologically conservative Preservation principle are incompatible given innocuous-looking background assumptions about belief revision. Gärdenfors gives up the Ramsey rule; I argue for preserving the Ramsey rule and interpret Gärdenfors's theorem as showing that no rational belief-reviser can avoid reasoning nonmonotonically. I argue against the Preservation principle and show that counterexamples to it always involve nonmonotonic reasoning. I then construct a new formal model of belief revision that does (...)
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  26. Knowledge Bases and Neural Network Synthesis.Todd R. Davies - 1991 - In Hozumi Tanaka (ed.), Artificial Intelligence in the Pacific Rim: Proceedings of the Pacific Rim International Conference on Artificial Intelligence. IOS Press. pp. 717-722.
    We describe and try to motivate our project to build systems using both a knowledge based and a neural network approach. These two approaches are used at different stages in the solution of a problem, instead of using knowledge bases exclusively on some problems, and neural nets exclusively on others. The knowledge base (KB) is defined first in a declarative, symbolic language that is easy to use. It is then compiled into an efficient neural network (NN) representation, run, and the (...)
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  27. The Relationship Between KLM and MAK Models for Nonmonotonic Inference Operations.Jürgen Dix & David Makinson - 1992 - Journal of Logic, Language and Information 1 (2):131-140.
    The purpose of this note is to make quite clear the relationship between two variants of the general notion of a preferential model for nonmonotonic inference: the models of Kraus, Lehmann and Magidor (KLM models) and those of Makinson (MAK models).On the one hand, we introduce the notion of the core of a KLM model, which suffices to fully determine the associated nonmonotonic inference relation. On the other hand, we slightly amplify MAK models with a monotonic consequence operation as additional (...)
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  28. Nonmonotonic Reasoning Based on Incomplete Logic.Tuan-Fang Fan, I. -Peng Lin & Churn-Jung Liau - 1997 - Journal of Applied Non-Classical Logics 7 (4):375-395.
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  29. Arguments Whose Strength Depends on Continuous Variation.James Franklin - 2013 - Informal Logic 33 (1):33-56.
    Both the traditional Aristotelian and modern symbolic approaches to logic have seen logic in terms of discrete symbol processing. Yet there are several kinds of argument whose validity depends on some topological notion of continuous variation, which is not well captured by discrete symbols. Examples include extrapolation and slippery slope arguments, sorites, fuzzy logic, and those involving closeness of possible worlds. It is argued that the natural first attempts to analyze these notions and explain their relation to reasoning fail, so (...)
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  30. Nonmonotonic Reasoning: From Finitary Relations to Infinitary Inference Operations.Michael Freund & Daniel Lehmann - 1994 - Studia Logica 53 (2):161 - 201.
    A. Tarski [22] proposed the study of infinitary consequence operations as the central topic of mathematical logic. He considered monotonicity to be a property of all such operations. In this paper, we weaken the monotonicity requirement and consider more general operations, inference operations. These operations describe the nonmonotonic logics both humans and machines seem to be using when infering defeasible information from incomplete knowledge. We single out a number of interesting families of inference operations. This study of infinitary inference operations (...)
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  31. To Preference Via Entrenchment.Konstantinos Georgatos - 1999 - Annals of Pure and Applied Logic 96 (1--3):141--155.
    We introduce a simple generalization of Gardenfors and Makinson’s epistemic entrenchment called partial entrenchment. We show that preferential inference can be generated as the sceptical counterpart of an inference mechanism defined directly on partial entrenchment.
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  32. Entrenchment Relations: A Uniform Approach to Nonmonotonic Inference.Konstantinos Georgatos - 1997 - In D. Gabbay, R. Kruse, A. Nonnengart & H. J. Ohlbach (eds.), ESCQARU/FAPR 97. Springer. pp. 282--297.
    We show that Gabbay’s nonmonotonic consequence relations c an be reduced to a new family of relations, called entrenchment relations. Entrenchment relations provide a direct generalization of epistemic entrenchment and expectation ordering introduced by G ̈ardenfors and Makinson for the study of belief revision and expectation inference, respectively.
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  33. Ordering-Based Representations of Rational Inference.Konstantinos Georgatos - 1996 - In Jose Julio Alferes, Luis Moniz Pereira & Ewa Orlowska (eds.), JELIA 96. Springer. pp. 176-191.
    Rational inference relations were introduced by Lehmann and Magidor as the ideal systems for drawing conclusions from a conditional base. However, there has been no simple characterization of these relations, other than its original representation by preferential models. In this paper, we shall characterize them with a class of total preorders of formulas by improving and extending G ̈ardenfors and Makinson’s results f or expectation inference relations. A second representation is application-oriented and is obtained by considering a class of consequence (...)
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  34. Readings in Nonmonotonic Reasoning.Matthew Ginsberg (ed.) - 1980 - Morgan Kauffman.
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  35. A Theory of Presumption for Everyday Argumentation.David M. Godden & Douglas N. Walton - 2007 - Pragmatics and Cognition 15 (2):313-346.
    The paper considers contemporary models of presumption in terms of their ability to contribute to a working theory of presumption for argumentation. Beginning with the Whatelian model, we consider its contemporary developments and alternatives, as proposed by Sidgwick, Kauffeld, Cronkhite, Rescher, Walton, Freeman, Ullmann-Margalit, and Hansen. Based on these accounts, we present a picture of presumptions characterized by their nature, function, foundation and force. On our account, presumption is a modal status that is attached to a claim and has the (...)
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  36. The Pleadings Games: An Artificial Intelligence Model of Procedural Justice.Thomas F. Gordon - 1995 - Springer.
    The Pleadings Game is a major contribution to artificial intelligence and legal theory. The book draws on jurisprudence and moral philosophy to develop a formal model of argumentation called the pleadings game. From a technical perspective, the work can be viewed as an extension of recent argumentation-based approaches to non-monotonic logic: (1) the game is dialogical rather than mono-logical; (2) the validity and priority of defeasible rules is subject to debate; and (3) resource limitations are acknowledged by rules for fairly (...)
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  37. Law and Defeasibility.Jaap Hage - 2003 - Artificial Intelligence and Law 11 (2-3):221-243.
    The paper consists of three parts. In the first part five kinds of defeasibility are distinguished that is ontological, conceptual, epistemic, justification and logical defeasibility. In the second part it is argued that from these, justification defeat is the phenomenon that plays a role in legal reasoning. In the third part, the view is defended that non-monotonic logics are not necessary to model justification defeat, but that they are so to speak the natural way to model this phenomenon.
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  38. Donald NUTE (Ed.), Defeasible Deontic Logic.Jaap Hage - 2000 - Artificial Intelligence and Law 8 (1):75-91.
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  39. A Primer on Rational Consequence Relations, Popper Functions, and Their Ranked Structures.James Hawthorne - 2014 - Studia Logica 102 (4):731-749.
    Rational consequence relations and Popper functions provide logics for reasoning under uncertainty, the former purely qualitative, the latter probabilistic. But few researchers seem to be aware of the close connection between these two logics. I’ll show that Popper functions are probabilistic versions of rational consequence relations. I’ll not assume that the reader is familiar with either logic. I present them, and explicate the relationship between them, from the ground up. I’ll also present alternative axiomatizations for each logic, showing them to (...)
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  40. On the Logic of Nonmonotonic Conditionals and Conditional Probabilities: Predicate Logic. [REVIEW]James Hawthorne - 1998 - Journal of Philosophical Logic 27 (1):1-34.
    In a previous paper I described a range of nonmonotonic conditionals that behave like conditional probability functions at various levels of probabilistic support. These conditionals were defined as semantic relations on an object language for sentential logic. In this paper I extend the most prominent family of these conditionals to a language for predicate logic. My approach to quantifiers is closely related to Hartry Field's probabilistic semantics. Along the way I will show how Field's semantics differs from a substitutional interpretation (...)
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  41. On the Logic of Nonmonotonic Conditionals and Conditional Probabilities.James Hawthorne - 1996 - Journal of Philosophical Logic 25 (2):185-218.
    I will describe the logics of a range of conditionals that behave like conditional probabilities at various levels of probabilistic support. Families of these conditionals will be characterized in terms of the rules that their members obey. I will show that for each conditional, →, in a given family, there is a probabilistic support level r and a conditional probability function P such that, for all sentences C and B, 'C → B' holds just in case P[B | C] ≥ (...)
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  42. A Semantic Approach to Non-Monotonic Conditionals.James Hawthorne - 1988 - In J. F. Lemmer & L. N. Kanal (eds.), Uncertainty in Artificial Intelligence 2. Elsevier.
    Any inferential system in which the addition of new premises can lead to the retraction of previous conclusions is a non-monotonic logic. Classical conditional probability provides the oldest and most widely respected example of non-monotonic inference. This paper presents a semantic theory for a unified approach to qualitative and quantitative non-monotonic logic. The qualitative logic is unlike most other non- monotonic logics developed for AI systems. It is closely related to classical (i.e., Bayesian) probability theory. The semantic theory for qualitative (...)
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  43. The Quantitative/Qualitative Watershed for Rules of Uncertain Inference.James Hawthorne & David Makinson - 2007 - Studia Logica 86 (2):247-297.
    We chart the ways in which closure properties of consequence relations for uncertain inference take on different forms according to whether the relations are generated in a quantitative or a qualitative manner. Among the main themes are: the identification of watershed conditions between probabilistically and qualitatively sound rules; failsafe and classicality transforms of qualitatively sound rules; non-Horn conditions satisfied by probabilistic consequence; representation and completeness problems; and threshold-sensitive conditions such as `preface' and `lottery' rules.
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  44. Knowledge Representation and Defeasible Reasoning.Kyburg Henry E., Loui Ronald P. & Carlson Greg N. (eds.) - 1990 - Kluwer Academic Publishers.
  45. When Structural Principles Hold Merely Locally.Ulf Hlobil - 2017 - In Pavel Arazim & Tomáš Lávička (eds.), The Logica Yearbook 2016. London: College Publications. pp. 53-67.
    In substructural logics, structural principles may hold in some fragments of a consequence relation without holding globally. I look at this phenomenon in my preferred substructural logic, in which Weakening and Cut fail but which is supra-intuitionistic. I introduce object language operators that keep track of the admissibility of Weakening and of intuitionistic implications. I end with some ideas about local transitivity.
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  46. A Nonmonotonic Sequent Calculus for Inferentialist Expressivists.Ulf Hlobil - 2016 - In Pavel Arazim & Michal Dančák (eds.), The Logica Yearbook 2015. College Publications. pp. 87-105.
    I am presenting a sequent calculus that extends a nonmonotonic consequence relation over an atomic language to a logically complex language. The system is in line with two guiding philosophical ideas: (i) logical inferentialism and (ii) logical expressivism. The extension defined by the sequent rules is conservative. The conditional tracks the consequence relation and negation tracks incoherence. Besides the ordinary propositional connectives, the sequent calculus introduces a new kind of modal operator that marks implications that hold monotonically. Transitivity fails, but (...)
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  47. Argument Construction and Reinstatement in Logics for Defeasible Reasoning.John F. Horty - 2001 - Artificial Intelligence and Law 9 (1):1-28.
    This paper points out some problems with two recent logical systems – one due to Prakken and Sartor, the other due to Kowalski and Toni – designedfor the representation of defeasible arguments in general, but with a specialemphasis on legal reasoning.
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  48. Moral Dilemmas and Nonmonotonic Logic.John F. Horty - 1994 - Journal of Philosophical Logic 23 (1):35 - 65.
    From a philosophical standpoint, the work presented here is based on van Fraassen [26]. The bulk of that paper is organized around a series of arguments against the assumption, built into standard deontic logic, that moral dilemmas are impossible; and van Fraassen only briefly sketches his alternative approach. His paper ends with the conclusion that “the problem of possibly irresolvable moral conflict reveals serious flaws in the philosophical and semantic foundations of ‘orthodox’ deontic logic, but also suggests a rich set (...)
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  49. Makinson David. Bridges From Classical to Nonmonotonic Logic. Text in Computing, Vol. 5. King's College, London, 2005, Xvi+ 216 Pp. [REVIEW]Hykel Hosni - 2006 - Bulletin of Symbolic Logic 12 (3):499-502.
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  50. Toulmin's Rhetorical Logic: What's the Warrant for Warrants?William M. Keith & David E. Beard - 2008 - Philosophy and Rhetoric 41 (1):22-50.
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