1. Introduction to Reasoning 2. Typology of Reasoning Exercises
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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. -
In Defence of Folk Psychology
FRANK JACKSON & PHILIP PETTIT IN DEFENCE OF FOLK PSYCHOLOGY (Received 14 October, 1988) It turned out that there was no phlogiston, no caloric fluid, and no luminiferous ether. Might it turn out that there are no beliefs and desires? Patricia and Paul Churchland say yes. ~ We say no. In part one we give our positive argument for the existence of beliefs and desires, and in part two we offer a diagnosis of what has misled the Church- lands into holding that it might very well turn out that there are no beliefs and desires. 1. THE EXISTENCE OF BELIEFS AND DESIRES 1.1. Our Strategy Eliminativists do not insist that it is certain as of now that there are no beliefs and desires. They insist that it might very well turn out that there are no beliefs and desires. Thus, in order to engage with their position, we need to provide a case for beliefs and desires which, in addition to being a strong one given what we now know, is one which is peculiarly unlikely to be undermined by future progress in neuroscience. Our first step towards providing such a case is to observe that the question of the existence of beliefs and desires as conceived in folk psychology can be divided into two questions. There exist beliefs and desires if there exist creatures with states truly describable as states of believing that such-and-such or desiring that so-and-so. Our question, then, can be divided into two questions. First, what is it for a state to be truly describable as a belief or as a desire; what, that is, needs to be the case according to our folk conception of belief and desire for a state to be a belief or a desire? And, second, is what needs to be the case in fact the case? Accordingly , if we accepted a certain, simple behaviourist account of, say, our folk Philosophical Studies 59:31--54, 1990. -
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. -
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. -
Discourse Relations and Defeasible Knowledge`
DISCOURSE RELATIONS AND DEFEASIBLE KNOWLEDGE* Alex Lascarides t Nicholas Asher Human Communication Research Centre Center for Cognitive Science University of Edinburgh University of Texas 2 Buccleuch Place, Edinburgh, EH8 9LW Austin, Texas 78712 Scotland USA alex@uk, ac. ed. cogsc£ asher@sygmund, cgs. utexas, edu Abstract of the event described in a, i.e. fl's event is part of the preparatory phase of a's: 2 This paper presents a formal account of the temporal interpretation of text. The distinct nat- (2) The council built the bridge. The architect ural interpretations of texts with similar syntax drew up the plans. are explained in terms of defeasible rules charac- terising causal laws and Gricean-style pragmatic Explanation(a, fl): For example the event de- maxims. Intuitively compelling patterns of defea,- scribed in clause fl caused the event described in sible entailment that are supported by the logic clause a: in which the theory is expressed are shown to un- derly temporal interpretation. (3) Max fell. John pushed him. Background(a, fl): For example the state de- The Problem scribed in fl is the 'backdrop' or circumstances under which the event in a occurred (so the event and state temporally overlap): The temporal interpretation of text involves an account of how the events described are related (4) Max opened the door. The room was pitch to each other. These relations follow from the dark. discourse relations that are central to temporal import. 1 Some of these are listed below, where Result(a, fl): The event described in a caused the clause a appears in the text before fl: the event or state described in fl: Narration(a,fl): The event described in fl is a consequence of (but not necessarily caused by) (5) Max switched off the light. -
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. -
Logic: a Brief Introduction Ronald L
Logic: A Brief Introduction Ronald L. Hall, Stetson University Chapter 1 - Basic Training 1.1 Introduction In this logic course, we are going to be relying on some “mental muscles” that may need some toning up. But don‟t worry, we recognize that it may take some time to get these muscles strengthened; so we are going to take it slow before we get up and start running. Are you ready? Well, let‟s begin our basic training with some preliminary conceptual stretching. Certainly all of us recognize that activities like riding a bicycle, balancing a checkbook, or playing chess are acquired skills. Further, we know that in order to acquire these skills, training and study are important, but practice is essential. It is also commonplace to acknowledge that these acquired skills can be exercised at various levels of mastery. Those who have studied the piano and who have practiced diligently certainly are able to play better than those of us who have not. The plain fact is that some people play the piano better than others. And the same is true of riding a bicycle, playing chess, and so forth. Now let‟s stretch this agreement about such skills a little further. Consider the activity of thinking. Obviously, we all think, but it is seldom that we think about thinking. So let's try to stretch our thinking to include thinking about thinking. As we do, and if this does not cause too much of a cramp, we will see that thinking is indeed an activity that has much in common with other acquired skills. -
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). -
The Philosophy of Mathematics: a Study of Indispensability and Inconsistency
Claremont Colleges Scholarship @ Claremont Scripps Senior Theses Scripps Student Scholarship 2016 The hiP losophy of Mathematics: A Study of Indispensability and Inconsistency Hannah C. Thornhill Scripps College Recommended Citation Thornhill, Hannah C., "The hiP losophy of Mathematics: A Study of Indispensability and Inconsistency" (2016). Scripps Senior Theses. Paper 894. http://scholarship.claremont.edu/scripps_theses/894 This Open Access Senior Thesis is brought to you for free and open access by the Scripps Student Scholarship at Scholarship @ Claremont. It has been accepted for inclusion in Scripps Senior Theses by an authorized administrator of Scholarship @ Claremont. For more information, please contact [email protected]. The Philosophy of Mathematics: A Study of Indispensability and Inconsistency Hannah C.Thornhill March 10, 2016 Submitted to Scripps College in Partial Fulfillment of the Degree of Bachelor of Arts in Mathematics and Philosophy Professor Avnur Professor Karaali Abstract This thesis examines possible philosophies to account for the prac- tice of mathematics, exploring the metaphysical, ontological, and epis- temological outcomes of each possible theory. Through a study of the two most probable ideas, mathematical platonism and fictionalism, I focus on the compelling argument for platonism given by an ap- peal to the sciences. The Indispensability Argument establishes the power of explanation seen in the relationship between mathematics and empirical science. Cases of this explanatory power illustrate how we might have reason to believe in the existence of mathematical en- tities present within our best scientific theories. The second half of this discussion surveys Newtonian Cosmology and other inconsistent theories as they pose issues that have received insignificant attention within the philosophy of mathematics.