An Introduction to Proof Theory
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Propositional Logic, Modal Logic, Propo- Sitional Dynamic Logic and first-Order Logic
A I L Madhavan Mukund Chennai Mathematical Institute E-mail: [email protected] Abstract ese are lecture notes for an introductory course on logic aimed at graduate students in Com- puter Science. e notes cover techniques and results from propositional logic, modal logic, propo- sitional dynamic logic and first-order logic. e notes are based on a course taught to first year PhD students at SPIC Mathematical Institute, Madras, during August–December, . Contents Propositional Logic . Syntax . . Semantics . . Axiomatisations . . Maximal Consistent Sets and Completeness . . Compactness and Strong Completeness . Modal Logic . Syntax . . Semantics . . Correspondence eory . . Axiomatising valid formulas . . Bisimulations and expressiveness . . Decidability: Filtrations and the finite model property . . Labelled transition systems and multi-modal logic . Dynamic Logic . Syntax . . Semantics . . Axiomatising valid formulas . First-Order Logic . Syntax . . Semantics . . Formalisations in first-order logic . . Satisfiability: Henkin’s reduction to propositional logic . . Compactness and the L¨owenheim-Skolem eorem . . A Complete Axiomatisation . . Variants of the L¨owenheim-Skolem eorem . . Elementary Classes . . Elementarily Equivalent Structures . . An Algebraic Characterisation of Elementary Equivalence . . Decidability . Propositional Logic . Syntax P = f g We begin with a countably infinite set of atomic propositions p0, p1,... and two logical con- nectives : (read as not) and _ (read as or). e set Φ of formulas of propositional logic is the smallest set satisfying the following conditions: • Every atomic proposition p is a member of Φ. • If α is a member of Φ, so is (:α). • If α and β are members of Φ, so is (α _ β). We shall normally omit parentheses unless we need to explicitly clarify the structure of a formula. -
Sequent Calculus and the Specification of Computation
Sequent Calculus and the Specification of Computation Lecture Notes Draft: 5 September 2001 These notes are being used with lectures for CSE 597 at Penn State in Fall 2001. These notes had been prepared to accompany lectures given at the Marktoberdorf Summer School, 29 July – 10 August 1997 for a course titled “Proof Theoretic Specification of Computation”. An earlier draft was used in courses given between 27 January and 11 February 1997 at the University of Siena and between 6 and 21 March 1997 at the University of Genoa. A version of these notes was also used at Penn State for CSE 522 in Fall 2000. For the most recent version of these notes, contact the author. °c Dale Miller 321 Pond Lab Computer Science and Engineering Department The Pennsylvania State University University Park, PA 16802-6106 USA Office: +(814)865-9505 [email protected] http://www.cse.psu.edu/»dale Contents 1 Overview and Motivation 5 1.1 Roles for logic in the specification of computations . 5 1.2 Desiderata for declarative programming . 6 1.3 Relating algorithm and logic . 6 2 First-Order Logic 8 2.1 Types and signatures . 8 2.2 First-order terms and formulas . 8 2.3 Sequent calculus . 10 2.4 Classical, intuitionistic, and minimal logics . 10 2.5 Permutations of inference rules . 12 2.6 Cut-elimination . 12 2.7 Consequences of cut-elimination . 13 2.8 Additional readings . 13 2.9 Exercises . 13 3 Logic Programming Considered Abstractly 15 3.1 Problems with proof search . 15 3.2 Interpretation as goal-directed search . -
Chapter 1 Preliminaries
Chapter 1 Preliminaries 1.1 First-order theories In this section we recall some basic definitions and facts about first-order theories. Most proofs are postponed to the end of the chapter, as exercises for the reader. 1.1.1 Definitions Definition 1.1 (First-order theory) —A first-order theory T is defined by: A first-order language L , whose terms (notation: t, u, etc.) and formulas (notation: φ, • ψ, etc.) are constructed from a fixed set of function symbols (notation: f , g, h, etc.) and of predicate symbols (notation: P, Q, R, etc.) using the following grammar: Terms t ::= x f (t1,..., tk) | Formulas φ, ψ ::= t1 = t2 P(t1,..., tk) φ | | > | ⊥ | ¬ φ ψ φ ψ φ ψ x φ x φ | ⇒ | ∧ | ∨ | ∀ | ∃ (assuming that each use of a function symbol f or of a predicate symbol P matches its arity). As usual, we call a constant symbol any function symbol of arity 0. A set of closed formulas of the language L , written Ax(T ), whose elements are called • the axioms of the theory T . Given a closed formula φ of the language of T , we say that φ is derivable in T —or that φ is a theorem of T —and write T φ when there are finitely many axioms φ , . , φ Ax(T ) such ` 1 n ∈ that the sequent φ , . , φ φ (or the formula φ φ φ) is derivable in a deduction 1 n ` 1 ∧ · · · ∧ n ⇒ system for classical logic. The set of all theorems of T is written Th(T ). Conventions 1.2 (1) In this course, we only work with first-order theories with equality. -
Philosophy 405: Knowledge, Truth and Mathematics Hamilton College Spring 2008 Russell Marcus M, W: 1-2:15Pm [email protected]
Philosophy 405: Knowledge, Truth and Mathematics Hamilton College Spring 2008 Russell Marcus M, W: 1-2:15pm [email protected] Class 15: Hilbert and Gödel I. Hilbert’s programme We have seen four different Hilberts: the term formalist (mathematical terms refer to inscriptions), the game formalist (ideal terms are meaningless), the deductivist (mathematics consists of deductions within consistent systems) the finitist (mathematics must proceed on finitary, but not foolishly so, basis). Gödel’s Theorems apply specifically to the deductivist Hilbert. But, Gödel would not have pursued them without the term formalist’s emphasis on terms, which lead to the deductivist’s pursuit of meta-mathematics. We have not talked much about the finitist Hilbert, which is the most accurate label for Hilbert’s programme. Hilbert makes a clear distinction between finite statements, and infinitary statements, which include reference to ideal elements. Ideal elements allow generality in mathematical formulas, and require acknowledgment of infinitary statements. See Hilbert 195-6. When Hilbert mentions ‘a+b=b+a’, he is referring to a universally quantified formula: (x)(y)(x+y=y+x) x and y range over all numbers, and so are not finitary. See Shapiro 159 on bounded and unbounded quantifiers. Hilbert’s blocky notation refers to bounded quantifiers. Note that a universal statement, taken as finitary, is incapable of negation, since it becomes an infinite statement. (x)Px is a perfectly finitary statement -(x)Px is equivalent to (x)-Px, which is infinitary - uh-oh! The admission of ideal elements begs questions of the meanings of terms in ideal statements. To what do the a and the b in ‘a+b=b+a’ refer? See Hilbert 194. -
UNDERSTANDING MATHEMATICS to UNDERSTAND PLATO -THEAETEUS (147D-148B Salomon Ofman
UNDERSTANDING MATHEMATICS TO UNDERSTAND PLATO -THEAETEUS (147d-148b Salomon Ofman To cite this version: Salomon Ofman. UNDERSTANDING MATHEMATICS TO UNDERSTAND PLATO -THEAETEUS (147d-148b. Lato Sensu, revue de la Société de philosophie des sciences, Société de philosophie des sciences, 2014, 1 (1). hal-01305361 HAL Id: hal-01305361 https://hal.archives-ouvertes.fr/hal-01305361 Submitted on 20 Apr 2016 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. UNDERSTANDING MATHEMATICS TO UNDERSTAND PLATO - THEAETEUS (147d-148b) COMPRENDRE LES MATHÉMATIQUES POUR COMPRENDRE PLATON - THÉÉTÈTE (147d-148b) Salomon OFMAN Institut mathématique de Jussieu-PRG Histoire des Sciences mathématiques 4 Place Jussieu 75005 Paris [email protected] Abstract. This paper is an updated translation of an article published in French in the Journal Lato Sensu (I, 2014, p. 70-80). We study here the so- called ‘Mathematical part’ of Plato’s Theaetetus. Its subject concerns the incommensurability of certain magnitudes, in modern terms the question of the rationality or irrationality of the square roots of integers. As the most ancient text on the subject, and on Greek mathematics and mathematicians as well, its historical importance is enormous. -
On Basic Probability Logic Inequalities †
mathematics Article On Basic Probability Logic Inequalities † Marija Boriˇci´cJoksimovi´c Faculty of Organizational Sciences, University of Belgrade, Jove Ili´ca154, 11000 Belgrade, Serbia; [email protected] † The conclusions given in this paper were partially presented at the European Summer Meetings of the Association for Symbolic Logic, Logic Colloquium 2012, held in Manchester on 12–18 July 2012. Abstract: We give some simple examples of applying some of the well-known elementary probability theory inequalities and properties in the field of logical argumentation. A probabilistic version of the hypothetical syllogism inference rule is as follows: if propositions A, B, C, A ! B, and B ! C have probabilities a, b, c, r, and s, respectively, then for probability p of A ! C, we have f (a, b, c, r, s) ≤ p ≤ g(a, b, c, r, s), for some functions f and g of given parameters. In this paper, after a short overview of known rules related to conjunction and disjunction, we proposed some probabilized forms of the hypothetical syllogism inference rule, with the best possible bounds for the probability of conclusion, covering simultaneously the probabilistic versions of both modus ponens and modus tollens rules, as already considered by Suppes, Hailperin, and Wagner. Keywords: inequality; probability logic; inference rule MSC: 03B48; 03B05; 60E15; 26D20; 60A05 1. Introduction The main part of probabilization of logical inference rules is defining the correspond- Citation: Boriˇci´cJoksimovi´c,M. On ing best possible bounds for probabilities of propositions. Some of them, connected with Basic Probability Logic Inequalities. conjunction and disjunction, can be obtained immediately from the well-known Boole’s Mathematics 2021, 9, 1409. -
Predicate Logic. Formal and Informal Proofs
CS 441 Discrete Mathematics for CS Lecture 5 Predicate logic Milos Hauskrecht [email protected] 5329 Sennott Square CS 441 Discrete mathematics for CS M. Hauskrecht Negation of quantifiers English statement: • Nothing is perfect. • Translation: ¬ x Perfect(x) Another way to express the same meaning: • Everything ... M. Hauskrecht 1 Negation of quantifiers English statement: • Nothing is perfect. • Translation: ¬ x Perfect(x) Another way to express the same meaning: • Everything is imperfect. • Translation: x ¬ Perfect(x) Conclusion: ¬ x P (x) is equivalent to x ¬ P(x) M. Hauskrecht Negation of quantifiers English statement: • It is not the case that all dogs are fleabags. • Translation: ¬ x Dog(x) Fleabag(x) Another way to express the same meaning: • There is a dog that … M. Hauskrecht 2 Negation of quantifiers English statement: • It is not the case that all dogs are fleabags. • Translation: ¬ x Dog(x) Fleabag(x) Another way to express the same meaning: • There is a dog that is not a fleabag. • Translation: x Dog(x) ¬ Fleabag(x) • Logically equivalent to: – x ¬ ( Dog(x) Fleabag(x) ) Conclusion: ¬ x P (x) is equivalent to x ¬ P(x) M. Hauskrecht Negation of quantified statements (aka DeMorgan Laws for quantifiers) Negation Equivalent ¬x P(x) x ¬P(x) ¬x P(x) x ¬P(x) M. Hauskrecht 3 Formal and informal proofs CS 441 Discrete mathematics for CS M. Hauskrecht Theorems and proofs • The truth value of some statement about the world is obvious and easy to assign • The truth of other statements may not be obvious, … …. But it may still follow (be derived) from known facts about the world To show the truth value of such a statement following from other statements we need to provide a correct supporting argument - a proof Important questions: – When is the argument correct? – How to construct a correct argument, what method to use? CS 441 Discrete mathematics for CS M. -
The Corcoran-Smiley Interpretation of Aristotle's Syllogistic As
November 11, 2013 15:31 History and Philosophy of Logic Aristotelian_syllogisms_HPL_house_style_color HISTORY AND PHILOSOPHY OF LOGIC, 00 (Month 200x), 1{27 Aristotle's Syllogistic and Core Logic by Neil Tennant Department of Philosophy The Ohio State University Columbus, Ohio 43210 email [email protected] Received 00 Month 200x; final version received 00 Month 200x I use the Corcoran-Smiley interpretation of Aristotle's syllogistic as my starting point for an examination of the syllogistic from the vantage point of modern proof theory. I aim to show that fresh logical insights are afforded by a proof-theoretically more systematic account of all four figures. First I regiment the syllogisms in the Gentzen{Prawitz system of natural deduction, using the universal and existential quantifiers of standard first- order logic, and the usual formalizations of Aristotle's sentence-forms. I explain how the syllogistic is a fragment of my (constructive and relevant) system of Core Logic. Then I introduce my main innovation: the use of binary quantifiers, governed by introduction and elimination rules. The syllogisms in all four figures are re-proved in the binary system, and are thereby revealed as all on a par with each other. I conclude with some comments and results about grammatical generativity, ecthesis, perfect validity, skeletal validity and Aristotle's chain principle. 1. Introduction: the Corcoran-Smiley interpretation of Aristotle's syllogistic as concerned with deductions Two influential articles, Corcoran 1972 and Smiley 1973, convincingly argued that Aristotle's syllogistic logic anticipated the twentieth century's systematizations of logic in terms of natural deductions. They also showed how Aristotle in effect advanced a completeness proof for his deductive system. -
Mapping the Meaning of Knowledge in Design Research Kristina Niedderer University of Hertfordshire
V.2:2 April 2007 www.designresearchsociety.org Design Research Society ISSN 1752-8445 Mapping the Meaning of Knowledge in Design Research Kristina Niedderer University of Hertfordshire Knowledge plays a vital role in our life This question has arisen for design in Table of Contents: in that it reflects how we understand the UK, as well as more generally for the world around us and thus deter- creative and practice-led disciplines Articles: 1 Mapping the Meaning of Knowledge mines how we act upon it. In this sense, (CPDs), because research regulations in Design Research knowledge is of particular importance and requirements in the UK remain Kristina Niedderer for designers because they act to shape silent about what knowledge and our world. Conventionally, knowledge understanding mean in the context of 3 Call for Papers: Design Research creation has been assumed by (design) their specifications while implicitly pri- Quarterly research. However developments of oritising propositional knowledge over Case Studies in Research: Knowledge using practice within research have knowledge that cannot be expressed in and Inquiry pointed to knowledge creation within that form (Niedderer 2007). and through practice. This has raised This has led to a number of prob- Listings: the question of the meaning, role and lems concerning the role and format 14 Current Research in Design: format of knowledge in both research of knowledge in research and practice ToCs from Leading Design Journals and practice, and about the compatibil- in the UK. For example, because of the ity between knowledge of research and language-based mode of proposition- 21 Upcoming Events Worldwide practice. -
Marko Malink (NYU)
Demonstration by reductio ad impossibile in Posterior Analytics 1.26 Marko Malink (New York University) Contents 1. Aristotle’s thesis in Posterior Analytics 1. 26 ................................................................................. 1 2. Direct negative demonstration vs. demonstration by reductio ................................................. 14 3. Aristotle’s argument from priority in nature .............................................................................. 25 4. Priority in nature for a-propositions ............................................................................................ 38 5. Priority in nature for e-, i-, and o-propositions .......................................................................... 55 6. Accounting for Aristotle’s thesis in Posterior Analytics 1. 26 ................................................... 65 7. Parts and wholes ............................................................................................................................. 77 References ............................................................................................................................................ 89 1. Aristotle’s thesis in Posterior Analytics 1. 26 At the beginning of the Analytics, Aristotle states that the subject of the treatise is demonstration (ἀπόδειξις). A demonstration, for Aristotle, is a kind of deductive argument. It is a deduction through which, when we possess it, we have scientific knowledge (ἐπιστήμη). While the Prior Analytics deals with deduction in -
Does Reductive Proof Theory Have a Viable Rationale?
DOES REDUCTIVE PROOF THEORY HAVE A VIABLE RATIONALE? Solomon Feferman Abstract The goals of reduction and reductionism in the natural sciences are mainly explanatory in character, while those in mathematics are primarily foundational. In contrast to global reductionist programs which aim to reduce all of mathematics to one supposedly “univer- sal” system or foundational scheme, reductive proof theory pursues local reductions of one formal system to another which is more jus- tified in some sense. In this direction, two specific rationales have been proposed as aims for reductive proof theory, the constructive consistency-proof rationale and the foundational reduction rationale. However, recent advances in proof theory force one to consider the viability of these rationales. Despite the genuine problems of foun- dational significance raised by that work, the paper concludes with a defense of reductive proof theory at a minimum as one of the principal means to lay out what rests on what in mathematics. In an extensive appendix to the paper, various reduction relations between systems are explained and compared, and arguments against proof-theoretic reduction as a “good” reducibility relation are taken up and rebutted. 1 1 Reduction and reductionism in the natural sciencesandinmathematics. The purposes of reduction in the natural sciences and in mathematics are quite different. In the natural sciences, one main purpose is to explain cer- tain phenomena in terms of more basic phenomena, such as the nature of the chemical bond in terms of quantum mechanics, and of macroscopic ge- netics in terms of molecular biology. In mathematics, the main purpose is foundational. This is not to be understood univocally; as I have argued in (Feferman 1984), there are a number of foundational ways that are pursued in practice. -
Classical First-Order Logic Software Formal Verification
Classical First-Order Logic Software Formal Verification Maria Jo~aoFrade Departmento de Inform´atica Universidade do Minho 2008/2009 Maria Jo~aoFrade (DI-UM) First-Order Logic (Classical) MFES 2008/09 1 / 31 Introduction First-order logic (FOL) is a richer language than propositional logic. Its lexicon contains not only the symbols ^, _, :, and ! (and parentheses) from propositional logic, but also the symbols 9 and 8 for \there exists" and \for all", along with various symbols to represent variables, constants, functions, and relations. There are two sorts of things involved in a first-order logic formula: terms, which denote the objects that we are talking about; formulas, which denote truth values. Examples: \Not all birds can fly." \Every child is younger than its mother." \Andy and Paul have the same maternal grandmother." Maria Jo~aoFrade (DI-UM) First-Order Logic (Classical) MFES 2008/09 2 / 31 Syntax Variables: x; y; z; : : : 2 X (represent arbitrary elements of an underlying set) Constants: a; b; c; : : : 2 C (represent specific elements of an underlying set) Functions: f; g; h; : : : 2 F (every function f as a fixed arity, ar(f)) Predicates: P; Q; R; : : : 2 P (every predicate P as a fixed arity, ar(P )) Fixed logical symbols: >, ?, ^, _, :, 8, 9 Fixed predicate symbol: = for \equals" (“first-order logic with equality") Maria Jo~aoFrade (DI-UM) First-Order Logic (Classical) MFES 2008/09 3 / 31 Syntax Terms The set T , of terms of FOL, is given by the abstract syntax T 3 t ::= x j c j f(t1; : : : ; tar(f)) Formulas The set L, of formulas of FOL, is given by the abstract syntax L 3 φ, ::= ? j > j :φ j φ ^ j φ _ j φ ! j t1 = t2 j 8x: φ j 9x: φ j P (t1; : : : ; tar(P )) :, 8, 9 bind most tightly; then _ and ^; then !, which is right-associative.