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I will discuss a variety of cases such that the subject's believing truly is somewhat of an accident, but less so than in a Gettier case. In each case, this is because her reasons are not ultimately undefeated full stop, but they are ultimately undefeated with certain qualifications. For example, the subject's reasons might be ultimately defeated considered in themselves but ultimately undefeated considered as a proper part of an inference to the best explanation that is undefeated without qualification. In each section of the paper, I consider different qualifications and show how in each case we get an epistemic standing I call "coach-class knowledge". First-class knowledge requires justifying reasons that are undefeated without qualification. Coach-class knowledge only requires qualified lack of defeat. I will use this distinction to bring debates over knowledge from falsehood and fake barns to an ecumenical resolution. In both cases, the subject enjoys coach-class rather than first-class knowledge. I will also show that the defeasible reasoning tradition can better account for graded accidental truth than safety theories. [ABSTRACT FROM AUTHOR]

Recent technological advances have led to unprecedented amounts of generated data that originate from the Web, sensor networks, and social media. Analytics in terms of defeasible reasoning – for example, for decision making – could provide richer knowledge of the underlying domain. Traditionally, defeasible reasoning has focused on complex knowledge structures over small to medium amounts of data, but recent research efforts have attempted to parallelize the reasoning process over theories with large numbers of facts. Such work has shown that traditional defeasible logics come with overheads that limit scalability. In this work, we design a new logic for defeasible reasoning, thus ensuring scalability by design. We establish several properties of the logic, including its relation to existing defeasible logics. Our experimental results indicate that our approach is indeed scalable and defeasible reasoning can be applied to billions of facts. [ABSTRACT FROM AUTHOR]

In order to automate verification process, regulatory rules written in natural language need to be translated into a format that machines can understand. However, none of the existing formalisms can fully represent the elements that appear in legal norms. For instance, most of these formalisms do not provide features to capture the behavior of deontic effects, which is an important aspect in automated compliance checking. This paper presents an approach for transforming legal norms represented using legalruleml to a variant of modal defeasible logic (and vice versa) such that a legal statement represented using LegalRuleML can be transformed into a machine-readable format that can be understood and reasoned about depending upon the client's preferences. [ABSTRACT FROM AUTHOR]

Defeasible logics provide several linguistic features to support the expression of defeasible knowledge. There is also a wide variety of such logics, expressing different intuitions about defeasible reasoning. However, the logics can only combine in trivial ways. This limits their usefulness in contexts where different intuitions are at play in different aspects of a problem. In particular, in some legal settings, different actors have different burdens of proof, which might be expressed as reasoning in different defeasible logics. In this paper, we introduce annotated defeasible logic as a flexible formalism permitting multiple forms of defeasibility, and establish some properties of the formalism. [ABSTRACT FROM AUTHOR]

Our lives are permeated by various forms of legality, produced by multiple bodies - both statist and non-statist. The pervasive presence of non-statist, soft law schemes in the contemporary society poses a challenge for legal theory: how to conceptualize legal-like structures that evolve outside the boundaries of the state and are able nonetheless to exert significant normative power? Understanding this phenomenon requires, I argue, a new model of law that will not be bounded by the binary (either/or) structure of traditional jurisprudence and sociology of law. I respond to this challenge by developing a degree-theoretic model of legal-normativity which I term "fuzzy law". This model offers a new conceptual vocabulary for thinking about soft law as a social phenomenon. The model draws on three main theoretical sources: the theory of complementary pairs, fuzzy-set theory, and defeasible reasoning. I examine the jurisprudential and sociological implications of the fuzzy law model through a discussion of the dialectics of reasoning with fuzzy rules and an exploration of the coordination dynamics of quasi-legal systems. [ABSTRACT FROM PUBLISHER]

Information about several papers discussed during the 2014 Spring Meeting of the Association for Symbolic Logic held at Westin Gaslamp Quarter in San Diego, California from April 16-17 is presented. Topics include the aspects of the works on epistemic and intensional logic, the defeasible reasoning according to the idea of philosopher John Pollock, and the aspects of the varieties of formalism.

This article is devoted to the study of methods to change defeasible logic programs (de.l.p.s) which are the knowledge bases used by the Defeasible Logic Programming (DeLP) interpreter. DeLP is an argumentation formalism that allows to reason over potentially inconsistent de.l.p.s. Argument Theory Change (ATC) studies certain aspects of belief revision in order to make them suitable for abstract argumentation systems. In this article, abstract arguments are rendered concrete by using the particular rule-based defeasible logic adopted by DeLP. The objective of our proposal is to define prioritized argument revision operators à la ATC for de.l.p.s, in such a way that the newly inserted argument ends up undefeated after the revision, thus warranting its conclusion. In order to ensure this warrant, the de.l.p. has to be changed in concordance with a minimal change principle. To this end, we discuss different minimal change criteria that could be adopted. Finally, an algorithm is presented, implementing the argument revision operations. [ABSTRACT FROM AUTHOR]

Maher (2012) introduced an approach for relative expressiveness of defeasible logics, and two notions of relative expressiveness were investigated. Using the first of these definitions of relative expressiveness, we show that all the defeasible logics in the DL framework are equally expressive under this formulation of relative expressiveness. The second formulation of relative expressiveness is stronger than the first. However, we show that logics incorporating individual defeat are equally expressive as the corresponding logics with team defeat. Thus the only differences in expressiveness of logics in DL arise from differences in how ambiguity is handled. This completes the study of relative expressiveness in DL begun in Maher (2012). [ABSTRACT FROM AUTHOR]

We provide a method of translating theories of Nute's defeasible logic into logic programs, and a corresponding translation in the opposite direction. Under certain natural restrictions, the conclusions of defeasible theories under the ambiguity propagating defeasible logic ADL correspond to those of the well-founded semantics for normal logic programs, and so it turns out that the two formalisms are closely related. Using the same translation of logic programs into defeasible theories, the semantics for the ambiguity blocking defeasible logic NDL can be seen as indirectly providing an ambiguity blocking semantics for logic programs. We also provide antimonotone operators for both ADL and NDL, each based on the Gelfond–Lifschitz (GL) operator for logic programs. For defeasible theories without defeaters or priorities on rules, the operator for ADL corresponds to the GL operator and so can be seen as partially capturing the consequences according to ADL. Similarly, the operator for NDL captures the consequences according to NDL, though in this case no restrictions on theories apply. Both operators can be used to define stable model semantics for defeasible theories. [ABSTRACT FROM PUBLISHER]

We address the relative expressiveness of defeasible logics in the framework DL. Relative expressiveness is formulated as the ability to simulate the reasoning of one logic within another logic. We show that such simulations must be modular, in the sense that they also work if applied only to part of a theory, in order to achieve a useful notion of relative expressiveness. We present simulations showing that logics in DL with and without the capability of team defeat are equally expressive. We also show that logics that handle ambiguity differently – ambiguity blocking versus ambiguity propagating – have distinct expressiveness, with neither able to simulate the other under a different formulation of expressiveness. [ABSTRACT FROM AUTHOR]

We show how to develop a multitude of rules of nonmonotonic logic from very simple and natural notions of size, using them as building blocks. [ABSTRACT FROM AUTHOR]

AbstractThis article surveys existing practical implementations of both defeasible and argumentation-based reasoning engines and associated literature. We aim to summarize the current state of the art in the research area, show that there are many similiarities and connections between the various implementations and also highlight the differences regarding evaluation goals and strategies. An important goal of this paper is to argue for the need for well-designed empirical evaluations, as well as formal complexity analysis, in order to justify the practical applicability of a reasoning engine. There are indeed many challenges to be faced in developing implementations of argumentation. Not least of these is the inherent computational complexity of the formal models. We cover some of the ways these challenges have been addressed, and provide pointers for future directions in realizing the goal of practical argumentation. [ABSTRACT FROM AUTHOR]