Discourse Relations and Defeasible Knowledge`
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Defeasibility from the Perspective of Informal Logic
University of Windsor Scholarship at UWindsor OSSA Conference Archive OSSA 10 May 22nd, 9:00 AM - May 25th, 5:00 PM Defeasibility from the perspective of informal logic Ralph H. Johnson University of Windsor, Centre for Research in Reasoning, Argumentation and Rhetoric Follow this and additional works at: https://scholar.uwindsor.ca/ossaarchive Part of the Philosophy Commons Johnson, Ralph H., "Defeasibility from the perspective of informal logic" (2013). OSSA Conference Archive. 84. https://scholar.uwindsor.ca/ossaarchive/OSSA10/papersandcommentaries/84 This Paper is brought to you for free and open access by the Conferences and Conference Proceedings at Scholarship at UWindsor. It has been accepted for inclusion in OSSA Conference Archive by an authorized conference organizer of Scholarship at UWindsor. For more information, please contact [email protected]. Defeasibility from the perspective of informal logic RALPH H. JOHNSON Centre for Research in Reasoning, Argumentation and Rhetoric University of Windsor 401 Sunset Ave, Windsor, Ontario Canada [email protected] ABSTRACT: The notions of defeasibility and defeasible reasoning have generated a great deal of interest in various research communities. Here I want to focus on their use in logic and argumentation studies. I will approach these topics from the perspective of an informal logician who finds himself struggling with some issues that surround the idea of and the deployment of the concept of defeasibility. My intention is to make those struggles as clear as I can. KEYWORDS: deductive, defeasible, defeasibility, Pollock, undercutting defeater, rebutting defeater, Informal Logic Initiative 1. INTRODUCTION The notions of defeasibility and defeasible reasoning have generated a great deal of interest in various research communities. -
Bootstrapping, Defeasible Reasoning, Anda Priorijustification
PHILOSOPHICAL PERSPECTIVES Philosophical Perspectives, 24, Epistemology, 2010 BOOTSTRAPPING, DEFEASIBLE REASONING, AND APRIORIJUSTIFICATION Stewart Cohen The University of Arizona What is the relationship between (rationally) justified perceptual belief and (rationally) justified belief in the reliability of perception? A familiar argument has it that this relationship makes perceptual justification impossible. For on the one hand, pre-theoretically it seems reasonable to suppose: (1) We cannot have justified perceptual beliefs without having a prior justified belief that perception is reliable. If we are not justified in believing perception is reliable, then how can we trust its deliverances? On the other hand, it seems reasonable to suppose: (2) We cannot be justified in believing perception is reliable without having prior justified perceptual beliefs. It is a contingent matter whether perception is reliable. So how else could we be justified in believing perception is reliable other than by empirical investigation?1 Combining these two suppositions yields the disastrous result that we need justified perceptual beliefs prior to having justified perceptual beliefs. Unless we are content with a skeptical result, these two suppositions need to be reconsidered. Some theorists have elected to retain (1) and deny (2), by arguing that we have apriorijustification for believing perception is reliable.2 Others have elected to retain (2) and deny (1), allowing that we can have justified perceptual beliefs without having justification for believing perception is reliable.3 Denying (1) yields what I will call “basic justification” or “basic justified beliefs” — justified beliefs that are obtained without prior justification for believing that the processes that produces them are reliable. -
Implicitness of Discourse Relations
Implicitness of Discourse Relations F atemeh T orabi Asr and V era Demberg Cluster of Excellence Multimodal Computing and Interaction (MMCI) Saarland University Campus C7.4, !"# Saarbrüc&en, Germany [email protected], [email protected] Abstract The annotations of explicit and implicit discourse connectives in the Penn Discourse Treebank make it possible to investigate on a large scale how different types of discourse relations are expressed. Assuming an account of the Uniform Information Density hypothesis we expect that discourse relations should be expressed explicitly with a discourse connector when they are unexpected, but may be implicit when the discourse relation can be anticipated. !e investigate whether discourse relations which have been argued to be expected by the comprehender exhibit a higher ratio of implicit connectors. !e "nd support for two hypotheses put forth in previous research which suggest that continuous and causal relations are presupposed by language users when processing consecutive sentences in a text. !e then proceed to analyze the effect of Implicit Causality (IC) verbs (which have been argued to raise an expectation for an explanation) as a local cue for an upcoming causal relation. Keywords: Causality Continuity Discourse relations, Discourse cues Implicit discourse relations, Corpus study Uniform Information Density. Proceedings of COLING 2012: Technical Papers, pages 2669–2684, COLING 2012, Mumbai, December 2012. 2669 1 Introduction David Hume in his prominent work “An enquiry concerning human understanding” proposed that ideas in the human mind were associated according to at least three types of relations: resemblance contiguity in time or place, and causality (Hume, 1784). -
From Logic to Rhetoric: a Contextualized Pedagogy for Fallacies
Current Issue From the Editors Weblog Editorial Board Editorial Policy Submissions Archives Accessibility Search Composition Forum 32, Fall 2015 From Logic to Rhetoric: A Contextualized Pedagogy for Fallacies Anne-Marie Womack Abstract: This article reenvisions fallacies for composition classrooms by situating them within rhetorical practices. Fallacies are not formal errors in logic but rather persuasive failures in rhetoric. I argue fallacies are directly linked to successful rhetorical strategies and pose the visual organizer of the Venn diagram to demonstrate that claims can achieve both success and failure based on audience and context. For example, strong analogy overlaps false analogy and useful appeal to pathos overlaps manipulative emotional appeal. To advance this argument, I examine recent changes in fallacies theory, critique a-rhetorical textbook approaches, contextualize fallacies within the history and theory of rhetoric, and describe a methodology for rhetorically reclaiming these terms. Today, fallacy instruction in the teaching of written argument largely follows two paths: teachers elevate fallacies as almost mathematical formulas for errors or exclude them because they don’t fit into rhetorical curriculum. Both responses place fallacies outside the realm of rhetorical inquiry. Fallacies, though, are not as clear-cut as the current practice of spotting them might suggest. Instead, they rely on the rhetorical situation. Just as it is an argument to create a fallacy, it is an argument to name a fallacy. This article describes an approach in which students must justify naming claims as successful strategies and/or fallacies, a process that demands writing about contexts and audiences rather than simply linking terms to obviously weak statements. -
Evidence Graphs: Supporting Transparent and FAIR Computation, with Defeasible Reasoning on Data, Methods and Results
bioRxiv preprint doi: https://doi.org/10.1101/2021.03.29.437561; this version posted March 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Evidence Graphs: Supporting Transparent and FAIR Computation, with Defeasible Reasoning on Data, Methods and Results Sadnan Al Manir1 [0000-0003-4647-3877], Justin Niestroy1 [0000-0002-1103-3882], Maxwell Adam Levinson1 [0000-0003-0384-8499], and Timothy Clark1,2 [0000-0003-4060-7360]* 1 University of Virginia, School of Medicine, Charlottesville VA USA 2 University of Virginia, School of Data Science, Charlottesville VA USA [email protected] *Corresponding author: [email protected] Abstract. Introduction: Transparency of computation is a requirement for assessing the va- lidity of computed results and research claims based upon them; and it is essential for access to, assessment, and reuse of computational components. These com- ponents may be subject to methodological or other challenges over time. While reference to archived software and/or data is increasingly common in publica- tions, a single machine-interpretable, integrative representation of how results were derived, that supports defeasible reasoning, has been absent. Methods: We developed the Evidence Graph Ontology, EVI, in OWL 2, with a set of inference rules, to provide deep representations of supporting and challeng- ing evidence for computations, services, software, data, and results, across arbi- trarily deep networks of computations, in connected or fully distinct processes. EVI integrates FAIR practices on data and software, with important concepts from provenance models, and argumentation theory. -
1 a Tale of Two Interpretations
Notes 1 A Tale of Two Interpretations 1. As Georges Dicker puts it, “Hume’s influence on contemporary epistemology and metaphysics is second to none ... ” (1998, ix). Note, too, that Hume’s impact extends beyond philosophy. For consider the following passage from Einstein’s letter to Moritz Schlick: Your representations that the theory of rel. [relativity] suggests itself in positivism, yet without requiring it, are also very right. In this also you saw correctly that this line of thought had a great influence on my efforts, and more specifically, E. Mach, and even more so Hume, whose Treatise of Human Nature I had studied avidly and with admiration shortly before discovering the theory of relativity. It is very possible that without these philosophical studies I would not have arrived at the solution (Einstein 1998, 161). 2. For a brief overview of Hume’s connection to naturalized epistemology, see Morris (2008, 472–3). 3. For the sake of convenience, I sometimes refer to the “traditional reading of Hume as a sceptic” as, e.g., “the sceptical reading of Hume” or simply “the sceptical reading”. Moreover, I often refer to those who read Hume as a sceptic as, e.g., “the sceptical interpreters of Hume” or “the sceptical inter- preters”. By the same token, I sometimes refer to those who read Hume as a naturalist as, e.g., “the naturalist interpreters of Hume” or simply “the natu- ralist interpreters”. And the reading that the naturalist interpreters support I refer to as, e.g., “the naturalist reading” or “the naturalist interpretation”. 4. This is not to say, though, that dissenting voices were entirely absent. -
On a Flexible Representation for Defeasible Reasoning Variants
Session 27: Argumentation AAMAS 2018, July 10-15, 2018, Stockholm, Sweden On a Flexible Representation for Defeasible Reasoning Variants Abdelraouf Hecham Pierre Bisquert Madalina Croitoru University of Montpellier IATE, INRA University of Montpellier Montpellier, France Montpellier, France Montpellier, France [email protected] [email protected] [email protected] ABSTRACT Table 1: Defeasible features supported by tools. We propose Statement Graphs (SG), a new logical formalism for Tool Blocking Propagating Team Defeat No Team Defeat defeasible reasoning based on argumentation. Using a flexible label- ASPIC+ - X - X ing function, SGs can capture the variants of defeasible reasoning DEFT - X - X DeLP - X - X (ambiguity blocking or propagating, with or without team defeat, DR-DEVICE X - X - and circular reasoning). We evaluate our approach with respect Flora-2 X - X - to human reasoning and propose a working first order defeasible reasoning tool that, compared to the state of the art, has richer expressivity at no added computational cost. Such tool could be of great practical use in decision making projects such as H2020 Existing literature has established the link between argumenta- NoAW. tion and defeasible reasoning via grounded semantics [13, 28] and Dialectical Trees [14]. Such approaches only allow for ambiguity KEYWORDS propagation without team defeat [16, 26]. In this paper we propose a new logical formalism called State- Defeasible Reasoning; Defeasible Logics; Existential Rules ment Graph (SGs) that captures all features showed in Table 1 via ACM Reference Format: a flexible labelling function. The SG can be seen as a generalisa- Abdelraouf Hecham, Pierre Bisquert, and Madalina Croitoru. 2018. On a tion of Abstract Dialectical Frameworks (ADF) [8] that enrich ADF Flexible Representation for Defeasible Reasoning Variants. -
Explanations, Belief Revision and Defeasible Reasoning
Artificial Intelligence 141 (2002) 1–28 www.elsevier.com/locate/artint Explanations, belief revision and defeasible reasoning Marcelo A. Falappa a, Gabriele Kern-Isberner b, Guillermo R. Simari a,∗ a Artificial Intelligence Research and Development Laboratory, Department of Computer Science and Engineering, Universidad Nacional del Sur Av. Alem 1253, (B8000CPB) Bahía Blanca, Argentina b Department of Computer Science, LG Praktische Informatik VIII, FernUniversitaet Hagen, D-58084 Hagen, Germany Received 15 August 1999; received in revised form 18 March 2002 Abstract We present different constructions for nonprioritized belief revision, that is, belief changes in which the input sentences are not always accepted. First, we present the concept of explanation in a deductive way. Second, we define multiple revision operators with respect to sets of sentences (representing explanations), giving representation theorems. Finally, we relate the formulated operators with argumentative systems and default reasoning frameworks. 2002 Elsevier Science B.V. All rights reserved. Keywords: Belief revision; Change theory; Knowledge representation; Explanations; Defeasible reasoning 1. Introduction Belief Revision systems are logical frameworks for modelling the dynamics of knowledge. That is, how we modify our beliefs when we receive new information. The main problem arises when that information is inconsistent with the beliefs that represent our epistemic state. For instance, suppose we believe that a Ferrari coupe is the fastest car and then we found out that some Porsche cars are faster than any Ferrari cars. Surely, we * Corresponding author. E-mail addresses: [email protected] (M.A. Falappa), [email protected] (G. Kern-Isberner), [email protected] (G.R. -
Reasoning Strategies for Diagnostic Probability Estimates in Causal Contexts: Preference for Defeasible Deduction Over Abduction?
Reasoning strategies for diagnostic probability estimates in causal contexts: Preference for defeasible deduction over abduction? Jean-Louis Stilgenbauer1,2, Jean Baratgin1,3, and Igor Douven4 1 CHArt (P-A-R-I-S), Université Paris 8, EPHE, 4-14 rue Ferrus, 75014 Paris – France, http://paris-reasoning.eu/ 2 Facultés Libres de Philosophie et de Psychologie (IPC), 70 avenue Denfert-Rochereau, 75014 Paris – France [email protected] 3 Institut Jean Nicod (IJN), École Normale Supérieure (ENS), 29 rue d’Ulm, 75005 Paris – France [email protected] 4 Sciences, Normes, Décision (SND), CNRS/Université Paris-Sorbonne, 1 rue Victor Cousin, 75005 Paris – France [email protected] Abstract. Recently, Meder, Mayrhofer, and Waldmann [1,2] have pro- posed a model of causal diagnostic reasoning that predicts an interfer- ence of the predictive probability, Pr(Effect | Cause), in estimating the diagnostic probability, Pr(Cause | Effect), specifically, that the interfer- ence leads to an underestimation bias of the diagnostic probability. The objective of the experiment reported in the present paper was twofold. A first aim was to test the existence of the underestimation bias in in- dividuals. Our results indicate the presence of an underestimation of the diagnostic probability that depends on the value of the predictive probability. Secondly, we investigated whether this bias was related to the type of estimation strategy followed by participants. We tested two main strategies: abductive inference and defeasible deduction. Our re- sults reveal that the underestimation of diagnostic probability is more pronounced under abductive inference than under defeasible deduction. Our data also suggest that defeasible deduction is for individuals the most natural reasoning strategy to estimate Pr(Cause | Effect). -
Negation Markers and Discourse Connective Omission
Uniform Information Density at the Level of Discourse Relations: Negation Markers and Discourse Connective Omission Fatemeh Torabi Asr & Vera Demberg Saarland University fatemeh|[email protected] Abstract About half of the discourse relations annotated in Penn Discourse Treebank (Prasad et al., 2008) are not explicitly marked using a discourse connective. But we do not have extensive theories of when or why a discourse relation is marked explicitly or when the connective is omitted. Asr and Demberg (2012a) have suggested an information-theoretic perspective according to which discourse connectives are more likely to be omitted when they are marking a relation that is expected or pre- dictable. This account is based on the Uniform Information Density theory (Levy and Jaeger, 2007), which suggests that speakers choose among alternative formulations that are allowed in their lan- guage the ones that achieve a roughly uniform rate of information transmission. Optional discourse markers should thus be omitted if they would lead to a trough in information density, and be inserted in order to avoid peaks in information density. We here test this hypothesis by observing how far a specific cue, negation in any form, affects the discourse relations that can be predicted to hold in a text, and how the presence of this cue in turn affects the use of explicit discourse connectives. 1 Introduction Discourse connectives are known as optional linguistic elements to construct relations between clausal units in text: in the Penn Discourse Treebank (PDTB Prasad et al. 2008), only about half of the annotated discourse relations are marked in the text by a discourse connective. -
Obligatory Presupposition in Discourse
Obligatory presupposition in discourse Pascal Amsili1 & Claire Beyssade2* 1Université Paris Diderot & Laboratoire de Linguistique Formelle, CNRS/2Institut Jean Nicod, CNRS Paris Some presupposition triggers, like too, seem to be obligatory in discourses where the presupposition they induce is explicitely expressed. We show that this phenomenon concerns a larger class than is usually acknowledged, and suggest that this class corresponds to the class of presupposition triggers that have no asserted content. We then propose a pragmatic explanation relying on the neo-gricean notion of antipresupposition. We also show that the phenomenon has a complex interaction with discourse relations. 1. Introduction The starting point of this work is a number of situations where some presupposition triggers seem obligatory in discourse. Here are two examples. (1) a. Jean est allé il y a deux ans au Canada. Il n’ira plus là-bas. John went to Canada two years ago. He won’t go there anymore b. #Jean est allé il y a deux ans au Canada. Il n’ira pas là-bas. John went to Canada two years ago. He won’t go there c. Léa a fait une bêtise. Elle ne la refera pas. Lea did a silly thing. She won’t re-do it. d. #Léa a fait une bêtise. Elle ne la fera pas. Lea did a silly thing. She won’t do it. *This article benefitted from comments from the audience at CiD’06 (Maynooth), and particularly from discussion with Henk Zeevat. We are also very grateful to an anonymous reviewer who provided very detailed and constructive comments. -
1 the Reasoning View and Defeasible Practical Reasoning Samuel Asarnow Macalester College [email protected] Forthcoming In
The Reasoning View and Defeasible Practical Reasoning Samuel Asarnow Macalester College [email protected] Forthcoming in Philosophy and Phenomenological Research ABSTRACT: According to the Reasoning View about normative reasons, facts about normative reasons for action can be understood in terms of facts about the norms of practical reasoning. I argue that this view is subject to an overlooked class of counterexamples, familiar from debates about Subjectivist theories of normative reasons. Strikingly, the standard strategy Subjectivists have used to respond to this problem cannot be adapted to the Reasoning View. I think there is a solution to this problem, however. I argue that the norms of practical reasoning, like the norms of theoretical reasoning, are characteristically defeasible, in a sense I make precise. Recognizing this property of those norms makes space for a solution to the problem. The resulting view is in a way analogous to familiar defeasibility theories of knowledge, but it avoids a standard objection to that theory. Introduction It is a commonplace to observe that there is a connection between the idea of a normative reason and the idea of good reasoning. As Paul Grice put it, “reasons […] are the stuff of which reasoning is made.”1 Using a consideration as a premise in a piece of reasoning—making an inference on the basis of it—is a paradigmatic way of treating that consideration as a reason. And, very often, when we engage in good reasoning we are responding to the considerations that really are the normative