Reasoning with Ambiguity
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Chapter 2 Introduction to Classical Propositional
CHAPTER 2 INTRODUCTION TO CLASSICAL PROPOSITIONAL LOGIC 1 Motivation and History The origins of the classical propositional logic, classical propositional calculus, as it was, and still often is called, go back to antiquity and are due to Stoic school of philosophy (3rd century B.C.), whose most eminent representative was Chryssipus. But the real development of this calculus began only in the mid-19th century and was initiated by the research done by the English math- ematician G. Boole, who is sometimes regarded as the founder of mathematical logic. The classical propositional calculus was ¯rst formulated as a formal ax- iomatic system by the eminent German logician G. Frege in 1879. The assumption underlying the formalization of classical propositional calculus are the following. Logical sentences We deal only with sentences that can always be evaluated as true or false. Such sentences are called logical sentences or proposi- tions. Hence the name propositional logic. A statement: 2 + 2 = 4 is a proposition as we assume that it is a well known and agreed upon truth. A statement: 2 + 2 = 5 is also a proposition (false. A statement:] I am pretty is modeled, if needed as a logical sentence (proposi- tion). We assume that it is false, or true. A statement: 2 + n = 5 is not a proposition; it might be true for some n, for example n=3, false for other n, for example n= 2, and moreover, we don't know what n is. Sentences of this kind are called propositional functions. We model propositional functions within propositional logic by treating propositional functions as propositions. -
Reasoning with Ambiguity
Noname manuscript No. (will be inserted by the editor) Reasoning with Ambiguity Christian Wurm the date of receipt and acceptance should be inserted later Abstract We treat the problem of reasoning with ambiguous propositions. Even though ambiguity is obviously problematic for reasoning, it is no less ob- vious that ambiguous propositions entail other propositions (both ambiguous and unambiguous), and are entailed by other propositions. This article gives a formal analysis of the underlying mechanisms, both from an algebraic and a logical point of view. The main result can be summarized as follows: sound (and complete) reasoning with ambiguity requires a distinction between equivalence on the one and congruence on the other side: the fact that α entails β does not imply β can be substituted for α in all contexts preserving truth. With- out this distinction, we will always run into paradoxical results. We present the (cut-free) sequent calculus ALcf , which we conjecture implements sound and complete propositional reasoning with ambiguity, and provide it with a language-theoretic semantics, where letters represent unambiguous meanings and concatenation represents ambiguity. Keywords Ambiguity, reasoning, proof theory, algebra, Computational Linguistics Acknowledgements Thanks to Timm Lichte, Roland Eibers, Roussanka Loukanova and Gerhard Schurz for helpful discussions; also I want to thank two anonymous reviewers for their many excellent remarks! 1 Introduction This article gives an extensive treatment of reasoning with ambiguity, more precisely with ambiguous propositions. We approach the problem from an Universit¨atD¨usseldorf,Germany Universit¨atsstr.1 40225 D¨usseldorf Germany E-mail: [email protected] 2 Christian Wurm algebraic and a logical perspective and show some interesting surprising results on both ends, which lead up to some interesting philosophical questions, which we address in a preliminary fashion. -
A Computer-Verified Monadic Functional Implementation of the Integral
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Theoretical Computer Science 411 (2010) 3386–3402 Contents lists available at ScienceDirect Theoretical Computer Science journal homepage: www.elsevier.com/locate/tcs A computer-verified monadic functional implementation of the integral Russell O'Connor, Bas Spitters ∗ Radboud University Nijmegen, Netherlands article info a b s t r a c t Article history: We provide a computer-verified exact monadic functional implementation of the Riemann Received 10 September 2008 integral in type theory. Together with previous work by O'Connor, this may be seen as Received in revised form 13 January 2010 the beginning of the realization of Bishop's vision to use constructive mathematics as a Accepted 23 May 2010 programming language for exact analysis. Communicated by G.D. Plotkin ' 2010 Elsevier B.V. All rights reserved. Keywords: Type theory Functional programming Exact real analysis Monads 1. Introduction Integration is one of the fundamental techniques in numerical computation. However, its implementation using floating- point numbers requires continuous effort on the part of the user in order to ensure that the results are correct. This burden can be shifted away from the end-user by providing a library of exact analysis in which the computer handles the error estimates. For high assurance we use computer-verified proofs that the implementation is actually correct; see [21] for an overview. It has long been suggested that, by using constructive mathematics, exact analysis and provable correctness can be unified [7,8]. Constructive mathematics provides a high-level framework for specifying computations (Section 2.1). -
Edinburgh Research Explorer
Edinburgh Research Explorer Propositions as Types Citation for published version: Wadler, P 2015, 'Propositions as Types', Communications of the ACM, vol. 58, no. 12, pp. 75-84. https://doi.org/10.1145/2699407 Digital Object Identifier (DOI): 10.1145/2699407 Link: Link to publication record in Edinburgh Research Explorer Document Version: Peer reviewed version Published In: Communications of the ACM General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact [email protected] providing details, and we will remove access to the work immediately and investigate your claim. Download date: 28. Sep. 2021 Propositions as Types ∗ Philip Wadler University of Edinburgh [email protected] 1. Introduction cluding Agda, Automath, Coq, Epigram, F#,F?, Haskell, LF, ML, Powerful insights arise from linking two fields of study previously NuPRL, Scala, Singularity, and Trellys. thought separate. Examples include Descartes’s coordinates, which Propositions as Types is a notion with mystery. Why should it links geometry to algebra, Planck’s Quantum Theory, which links be the case that intuitionistic natural deduction, as developed by particles to waves, and Shannon’s Information Theory, which links Gentzen in the 1930s, and simply-typed lambda calculus, as devel- thermodynamics to communication. -
A Multi-Modal Analysis of Anaphora and Ellipsis
University of Pennsylvania Working Papers in Linguistics Volume 5 Issue 2 Current Work in Linguistics Article 2 1998 A Multi-Modal Analysis of Anaphora and Ellipsis Gerhard Jaeger Follow this and additional works at: https://repository.upenn.edu/pwpl Recommended Citation Jaeger, Gerhard (1998) "A Multi-Modal Analysis of Anaphora and Ellipsis," University of Pennsylvania Working Papers in Linguistics: Vol. 5 : Iss. 2 , Article 2. Available at: https://repository.upenn.edu/pwpl/vol5/iss2/2 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/pwpl/vol5/iss2/2 For more information, please contact [email protected]. A Multi-Modal Analysis of Anaphora and Ellipsis This working paper is available in University of Pennsylvania Working Papers in Linguistics: https://repository.upenn.edu/pwpl/vol5/iss2/2 A Multi-Modal Analysis of Anaphora and Ellipsis Gerhard J¨ager 1. Introduction The aim of the present paper is to outline a unified account of anaphora and ellipsis phenomena within the framework of Type Logical Categorial Gram- mar.1 There is at least one conceptual and one empirical reason to pursue such a goal. Firstly, both phenomena are characterized by the fact that they re-use semantic resources that are also used elsewhere. This issue is discussed in detail in section 2. Secondly, they show a striking similarity in displaying the characteristic ambiguity between strict and sloppy readings. This supports the assumption that in fact the same mechanisms are at work in both cases. (1) a. John washed his car, and Bill did, too. b. John washed his car, and Bill waxed it. -
12 Propositional Logic
CHAPTER 12 ✦ ✦ ✦ ✦ Propositional Logic In this chapter, we introduce propositional logic, an algebra whose original purpose, dating back to Aristotle, was to model reasoning. In more recent times, this algebra, like many algebras, has proved useful as a design tool. For example, Chapter 13 shows how propositional logic can be used in computer circuit design. A third use of logic is as a data model for programming languages and systems, such as the language Prolog. Many systems for reasoning by computer, including theorem provers, program verifiers, and applications in the field of artificial intelligence, have been implemented in logic-based programming languages. These languages generally use “predicate logic,” a more powerful form of logic that extends the capabilities of propositional logic. We shall meet predicate logic in Chapter 14. ✦ ✦ ✦ ✦ 12.1 What This Chapter Is About Section 12.2 gives an intuitive explanation of what propositional logic is, and why it is useful. The next section, 12,3, introduces an algebra for logical expressions with Boolean-valued operands and with logical operators such as AND, OR, and NOT that Boolean algebra operate on Boolean (true/false) values. This algebra is often called Boolean algebra after George Boole, the logician who first framed logic as an algebra. We then learn the following ideas. ✦ Truth tables are a useful way to represent the meaning of an expression in logic (Section 12.4). ✦ We can convert a truth table to a logical expression for the same logical function (Section 12.5). ✦ The Karnaugh map is a useful tabular technique for simplifying logical expres- sions (Section 12.6). -
Propositional Calculus
CSC 438F/2404F Notes Winter, 2014 S. Cook REFERENCES The first two references have especially influenced these notes and are cited from time to time: [Buss] Samuel Buss: Chapter I: An introduction to proof theory, in Handbook of Proof Theory, Samuel Buss Ed., Elsevier, 1998, pp1-78. [B&M] John Bell and Moshe Machover: A Course in Mathematical Logic. North- Holland, 1977. Other logic texts: The first is more elementary and readable. [Enderton] Herbert Enderton: A Mathematical Introduction to Logic. Academic Press, 1972. [Mendelson] E. Mendelson: Introduction to Mathematical Logic. Wadsworth & Brooks/Cole, 1987. Computability text: [Sipser] Michael Sipser: Introduction to the Theory of Computation. PWS, 1997. [DSW] M. Davis, R. Sigal, and E. Weyuker: Computability, Complexity and Lan- guages: Fundamentals of Theoretical Computer Science. Academic Press, 1994. Propositional Calculus Throughout our treatment of formal logic it is important to distinguish between syntax and semantics. Syntax is concerned with the structure of strings of symbols (e.g. formulas and formal proofs), and rules for manipulating them, without regard to their meaning. Semantics is concerned with their meaning. 1 Syntax Formulas are certain strings of symbols as specified below. In this chapter we use formula to mean propositional formula. Later the meaning of formula will be extended to first-order formula. (Propositional) formulas are built from atoms P1;P2;P3;:::, the unary connective :, the binary connectives ^; _; and parentheses (,). (The symbols :; ^ and _ are read \not", \and" and \or", respectively.) We use P; Q; R; ::: to stand for atoms. Formulas are defined recursively as follows: Definition of Propositional Formula 1) Any atom P is a formula. -
Topics in Philosophical Logic
Topics in Philosophical Logic The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Litland, Jon. 2012. Topics in Philosophical Logic. Doctoral dissertation, Harvard University. Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:9527318 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA © Jon Litland All rights reserved. Warren Goldfarb Jon Litland Topics in Philosophical Logic Abstract In “Proof-Theoretic Justification of Logic”, building on work by Dummett and Prawitz, I show how to construct use-based meaning-theories for the logical constants. The assertability-conditional meaning-theory takes the meaning of the logical constants to be given by their introduction rules; the consequence-conditional meaning-theory takes the meaning of the log- ical constants to be given by their elimination rules. I then consider the question: given a set of introduction (elimination) rules , what are the R strongest elimination (introduction) rules that are validated by an assertabil- ity (consequence) conditional meaning-theory based on ? I prove that the R intuitionistic introduction (elimination) rules are the strongest rules that are validated by the intuitionistic elimination (introduction) rules. I then prove that intuitionistic logic is the strongest logic that can be given either an assertability-conditional or consequence-conditional meaning-theory. In “Grounding Grounding” I discuss the notion of grounding. My discus- sion revolves around the problem of iterated grounding-claims. -
Why Would You Trust B? Eric Jaeger, Catherine Dubois
Why Would You Trust B? Eric Jaeger, Catherine Dubois To cite this version: Eric Jaeger, Catherine Dubois. Why Would You Trust B?. Logic for Programming, Artificial In- telligence, and Reasoning, Nov 2007, Yerevan, Armenia. pp.288-302, 10.1007/978-3-540-75560-9. hal-00363345 HAL Id: hal-00363345 https://hal.archives-ouvertes.fr/hal-00363345 Submitted on 23 Feb 2009 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Why Would You Trust B? Eric´ Jaeger12 and Catherine Dubois3 1 LIP6, Universit´eParis 6, 4 place Jussieu, 75252 Paris Cedex 05, France 2 LTI, Direction centrale de la s´ecurit´edes syst`emes d’information, 51 boulevard de La Tour-Maubourg, 75700 Paris 07 SP, France 3 CEDRIC, Ecole´ nationale sup´erieure d’informatique pour l’industrie et l’entreprise, 18 all´ee Jean Rostand, 91025 Evry Cedex, France Abstract. The use of formal methods provides confidence in the cor- rectness of developments. Yet one may argue about the actual level of confidence obtained when the method itself – or its implementation – is not formally checked. We address this question for the B, a widely used formal method that allows for the derivation of correct programs from specifications. -
An Introduction to Formal Methods for Philosophy Students
An Introduction to Formal Methods for Philosophy Students Thomas Forster February 20, 2021 2 Contents 1 Introduction 13 1.1 What is Logic? . 13 1.1.1 Exercises for the first week: “Sheet 0” . 13 2 Introduction to Logic 17 2.1 Statements, Commands, Questions, Performatives . 18 2.1.1 Truth-functional connectives . 20 2.1.2 Truth Tables . 21 2.2 The Language of Propositional Logic . 23 2.2.1 Truth-tables for compound expressions . 24 2.2.2 Logical equivalence . 26 2.2.3 Non truth functional connectives . 27 2.3 Intension and Extension . 28 2.3.1 If–then . 31 2.3.2 Logical Form and Valid Argument . 33 2.3.3 The Type-Token Distinction . 33 2.3.4 Copies . 35 2.4 Tautology and Validity . 36 2.4.1 Valid Argument . 36 2.4.2 V and W versus ^ and _ .................... 40 2.4.3 Conjunctive and Disjunctive Normal Form . 41 2.5 Further Useful Logical Gadgetry . 46 2.5.1 The Analytic-Synthetic Distinction . 46 2.5.2 Necessary and Sufficient Conditions . 47 2.5.3 The Use-Mention Distinction . 48 2.5.4 Language-metalanguage distinction . 51 2.5.5 Semantic Optimisation and the Principle of Charity . 52 2.5.6 Inferring A-or-B from A . 54 2.5.7 Fault-tolerant pattern-matching . 54 2.5.8 Overinterpretation . 54 2.5.9 Affirming the consequent . 55 3 4 CONTENTS 3 Proof Systems for Propositional Logic 57 3.1 Arguments by LEGO . 57 3.2 The Rules of Natural Deduction . 57 3.2.1 Worries about reductio and hypothetical reasoning . -
Negation” Impedes Argumentation: the Case of Dawn
When “Negation” Impedes Argumentation: The Case of Dawn Morgan Sellers Arizona State University Abstract: This study investigates one student’s meanings for negations of various mathematical statements. The student, from a Transition-to-Proof course, participated in two clinical interviews in which she was asked to negate statements with one quantifier or logical connective. Then, the student was asked to negate statements with a combination of quantifiers and logical connectives. Lastly, the student was presented with several complex mathematical statements from Calculus and was asked to determine if these statements were true or false on a case-by- case basis using a series of graphs. The results reveal that the student used the same rule for negation in both simple and complex mathematical statements when she was asked to negate each statement. However, when the student was asked to determine if statements were true or false, she relied on her meaning for the mathematical statement and formed a mathematically convincing argument. Key words: Negation, Argumentation, Complex Mathematical Statements, Calculus, Transition- to-Proof Many studies have noted that students often interpret logical connectives (such as and and or) and quantifiers (such as for all and there exists) in mathematical statements in ways contrary to mathematical convention (Case, 2015; Dawkins & Cook, 2017; Dawkins & Roh, 2016; Dubinsky & Yiparki, 2000; Epp,1999, 2003; Selden & Selden, 1995; Shipman, 2013, Tall, 1990). Recently, researchers have also called for attention to the logical structures found within Calculus theorems and definitions (Case, 2015; Sellers, Roh, & David, 2017) because students must reason with these logical components in order to verify or refute mathematical claims. -
Logical Connectives in Natural Languages
Logical connectives in natural languages Leo´ Picat Introduction Natural languages all have common points. These shared features define and constrain them. A key property of all natural languages is their learnability. As long as children are exposed to it, they can learn any spoken or signed language. This process takes place in environments in which children are not exposed to the full diversity of their mother tongue: it is with only few evidences that they master the ability to express themselves through language. As children are not exposed to negative evidences, learning a language would not be possible if con- straints were not present to limit the space of possible languages. Input-based theories predict that these constraints result from general cognition mechanisms. Knowledge-based theories predict that they are language specific and are part of a Universal Grammar [1]. Which approach is the right one is still a matter of debate and the implementation of these constraints within our brain is still to be determined. Yet, one can get a taste of them as they surface in linguistic universals. Universals have been formulated for most domains of linguistics. The first person to open the way was Greenberg [2] who described 50 statements about syntax and morphology across languages. In the phono- logical domain, all languages have stops for example [3]. Though, few universals are this absolute; most of them are more statistical truth or take the form of conditional statements. Universals have also been defined for semantics with more or less success [4]. Some of them shed light on non-linguistic abilities.