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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. -
Mathematical Induction - a Miscellany of Theory, History and Technique
Mathematical Induction - a miscellany of theory, history and technique Theory and applications for advanced secondary students Part 4 Peter Haggstrom This work is subject to Copyright. It is a chapter in a larger work. You can however copy this chapter for educational purposes under the Statutory License of the Copyright Act 1968 - Part VB For more information [email protected] Copyright 2009 [email protected] The building blocks of Gödelʼs Theorem The foundations of Gödel’s Theorem (ie his undecidability theorem) are to be found in about 50 papers contained in a book by Jean van Heijenoort:, “From Frege to Gödel: A Source Book in Mathematical Logic, 1879 - 1931”. Every serious logic student has read this book. Van Heijenoort is worth mentioning even if only for his colourful past which is described by Benjamin H Yandell in his book “The Honors Class: Hilbert’s Problems and Their Solvers”, A K Peters, 2002, page 66. I quote in full: “ I assumed van Heijenoort was merely a logician as I gratefully pored over his book and was astounded when I learned that as a young man, in the 1930s, he had followed Leon Trotsky from Turkey to France to Norway to Mexico, as his body guard and secretary. Anita Feferman’s ”From Trotsky to Gödel”: The Life of Jean van Heijenoort” tells van Heijenoort’s remarkable story. Trotsky and his camp were pursued by Stalinist agents; van Heijenoort always packed a gun. Van Heijenoort had an affair with an artist Frida Kahlo. He epitomized cool and was attractive to women, and this continued even after he became a logician, He had grown tired of the rigors of life with Trotsky and traveled to New York in 1939 on a somewhat vague mission. -
Model Theory, Arithmetic & Algebraic Geometry
MODEL THEORY, ARITHMETIC & ALGEBRAIC GEOMETRY JOEL TORRES DEL VALLE 1. LANGUAGES AND STRUCTURES. 1.1. What is Model Theory? Model Theory is the study of the relationship between theories and mathematical struc- tures which satisfies them [11]. Model Theory introduces Mathematical Logic in the prac- tice of Universal Algebra, so we can think it like Model Theory = Universal Algebra + Mathematical Logic. I started this pages with the same question Chang-Keisler started their celebrated book [3]: ‘What is Model Theory?’ They also summarize the answer to the equation above. In this pages I summarize the relationship between Model Theory, Arithmetic and Algebraic Geometry. The topics will be the basic ones in the area, so this is just an invitation, in the presentation of topics I mainly follow the philosophy of the references, my basic reference is [9]. The early pioneers in Model Theory were Leopold L¨owenheim in 1915, in his work ‘Uber¨ M¨oglichkeiten im Relativkalk¨ul’1 there he proved that if a first order theory T that has an infinite model then has a countable model. Thoralf Skolem in 1920 proved a second version of L¨owenheim result, in his work ‘Logisch-kombinatorische Untersuchungen ¨uber die Erf¨ullbarkeit oder Beweisbarkeit mathematischer S¨atze nebst einem Theoreme ¨uber dichte Mengen’2. Kurt G¨odel in 1930 proved his Completeness and Compactness Theorems for countable languages in his Doctoral dissertation at the University of Viena titled ‘Die Vollst¨andigkeit der Axiome des logischen Funktionenkalk¨uls’3. Alfred Tarski in 1931 -
Theorem Proving in Classical Logic
MEng Individual Project Imperial College London Department of Computing Theorem Proving in Classical Logic Supervisor: Dr. Steffen van Bakel Author: David Davies Second Marker: Dr. Nicolas Wu June 16, 2021 Abstract It is well known that functional programming and logic are deeply intertwined. This has led to many systems capable of expressing both propositional and first order logic, that also operate as well-typed programs. What currently ties popular theorem provers together is their basis in intuitionistic logic, where one cannot prove the law of the excluded middle, ‘A A’ – that any proposition is either true or false. In classical logic this notion is provable, and the_: corresponding programs turn out to be those with control operators. In this report, we explore and expand upon the research about calculi that correspond with classical logic; and the problems that occur for those relating to first order logic. To see how these calculi behave in practice, we develop and implement functional languages for propositional and first order logic, expressing classical calculi in the setting of a theorem prover, much like Agda and Coq. In the first order language, users are able to define inductive data and record types; importantly, they are able to write computable programs that have a correspondence with classical propositions. Acknowledgements I would like to thank Steffen van Bakel, my supervisor, for his support throughout this project and helping find a topic of study based on my interests, for which I am incredibly grateful. His insight and advice have been invaluable. I would also like to thank my second marker, Nicolas Wu, for introducing me to the world of dependent types, and suggesting useful resources that have aided me greatly during this report. -
Implicit Versus Explicit Knowledge in Dialogical Logic Manuel Rebuschi
Implicit versus Explicit Knowledge in Dialogical Logic Manuel Rebuschi To cite this version: Manuel Rebuschi. Implicit versus Explicit Knowledge in Dialogical Logic. Ondrej Majer, Ahti-Veikko Pietarinen and Tero Tulenheimo. Games: Unifying Logic, Language, and Philosophy, Springer, pp.229-246, 2009, 10.1007/978-1-4020-9374-6_10. halshs-00556250 HAL Id: halshs-00556250 https://halshs.archives-ouvertes.fr/halshs-00556250 Submitted on 16 Jan 2011 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. Implicit versus Explicit Knowledge in Dialogical Logic Manuel Rebuschi L.P.H.S. – Archives H. Poincar´e Universit´ede Nancy 2 [email protected] [The final version of this paper is published in: O. Majer et al. (eds.), Games: Unifying Logic, Language, and Philosophy, Dordrecht, Springer, 2009, 229-246.] Abstract A dialogical version of (modal) epistemic logic is outlined, with an intuitionistic variant. Another version of dialogical epistemic logic is then provided by means of the S4 mapping of intuitionistic logic. Both systems cast new light on the relationship between intuitionism, modal logic and dialogical games. Introduction Two main approaches to knowledge in logic can be distinguished [1]. The first one is an implicit way of encoding knowledge and consists in an epistemic interpretation of usual logic. -
Henkin's Method and the Completeness Theorem
Henkin's Method and the Completeness Theorem Guram Bezhanishvili∗ 1 Introduction Let L be a first-order logic. For a sentence ' of L, we will use the standard notation \` '" for ' is provable in L (that is, ' is derivable from the axioms of L by the use of the inference rules of L); and \j= '" for ' is valid (that is, ' is satisfied in every interpretation of L). The soundness theorem for L states that if ` ', then j= '; and the completeness theorem for L states that if j= ', then ` '. Put together, the soundness and completeness theorems yield the correctness theorem for L: a sentence is derivable in L iff it is valid. Thus, they establish a crucial feature of L; namely, that syntax and semantics of L go hand-in-hand: every theorem of L is a logical law (can not be refuted in any interpretation of L), and every logical law can actually be derived in L. In fact, a stronger version of this result is also true. For each first-order theory T and a sentence ' (in the language of T ), we have that T ` ' iff T j= '. Thus, each first-order theory T (pick your favorite one!) is sound and complete in the sense that everything that we can derive from T is true in all models of T , and everything that is true in all models of T is in fact derivable from T . This is a very strong result indeed. One possible reading of it is that the first-order formalization of a given mathematical theory is adequate in the sense that every true statement about T that can be formalized in the first-order language of T is derivable from the axioms of T . -
Relevant and Substructural Logics
Relevant and Substructural Logics GREG RESTALL∗ PHILOSOPHY DEPARTMENT, MACQUARIE UNIVERSITY [email protected] June 23, 2001 http://www.phil.mq.edu.au/staff/grestall/ Abstract: This is a history of relevant and substructural logics, written for the Hand- book of the History and Philosophy of Logic, edited by Dov Gabbay and John Woods.1 1 Introduction Logics tend to be viewed of in one of two ways — with an eye to proofs, or with an eye to models.2 Relevant and substructural logics are no different: you can focus on notions of proof, inference rules and structural features of deduction in these logics, or you can focus on interpretations of the language in other structures. This essay is structured around the bifurcation between proofs and mod- els: The first section discusses Proof Theory of relevant and substructural log- ics, and the second covers the Model Theory of these logics. This order is a natural one for a history of relevant and substructural logics, because much of the initial work — especially in the Anderson–Belnap tradition of relevant logics — started by developing proof theory. The model theory of relevant logic came some time later. As we will see, Dunn's algebraic models [76, 77] Urquhart's operational semantics [267, 268] and Routley and Meyer's rela- tional semantics [239, 240, 241] arrived decades after the initial burst of ac- tivity from Alan Anderson and Nuel Belnap. The same goes for work on the Lambek calculus: although inspired by a very particular application in lin- guistic typing, it was developed first proof-theoretically, and only later did model theory come to the fore. -
From Axioms to Rules — a Coalition of Fuzzy, Linear and Substructural Logics
From Axioms to Rules — A Coalition of Fuzzy, Linear and Substructural Logics Kazushige Terui National Institute of Informatics, Tokyo Laboratoire d’Informatique de Paris Nord (Joint work with Agata Ciabattoni and Nikolaos Galatos) Genova, 21/02/08 – p.1/?? Parties in Nonclassical Logics Modal Logics Default Logic Intermediate Logics (Padova) Basic Logic Paraconsistent Logic Linear Logic Fuzzy Logics Substructural Logics Genova, 21/02/08 – p.2/?? Parties in Nonclassical Logics Modal Logics Default Logic Intermediate Logics (Padova) Basic Logic Paraconsistent Logic Linear Logic Fuzzy Logics Substructural Logics Our aim: Fruitful coalition of the 3 parties Genova, 21/02/08 – p.2/?? Basic Requirements Substractural Logics: Algebraization ´µ Ä Î ´Äµ Genova, 21/02/08 – p.3/?? Basic Requirements Substractural Logics: Algebraization ´µ Ä Î ´Äµ Fuzzy Logics: Standard Completeness ´µ Ä Ã ´Äµ ¼½ Genova, 21/02/08 – p.3/?? Basic Requirements Substractural Logics: Algebraization ´µ Ä Î ´Äµ Fuzzy Logics: Standard Completeness ´µ Ä Ã ´Äµ ¼½ Linear Logic: Cut Elimination Genova, 21/02/08 – p.3/?? Basic Requirements Substractural Logics: Algebraization ´µ Ä Î ´Äµ Fuzzy Logics: Standard Completeness ´µ Ä Ã ´Äµ ¼½ Linear Logic: Cut Elimination A logic without cut elimination is like a car without engine (J.-Y. Girard) Genova, 21/02/08 – p.3/?? Outcome We classify axioms in Substructural and Fuzzy Logics according to the Substructural Hierarchy, which is defined based on Polarity (Linear Logic). Genova, 21/02/08 – p.4/?? Outcome We classify axioms in Substructural and Fuzzy Logics according to the Substructural Hierarchy, which is defined based on Polarity (Linear Logic). Give an automatic procedure to transform axioms up to level ¼ È È ¿ ( , in the absense of Weakening) into Hyperstructural ¿ Rules in Hypersequent Calculus (Fuzzy Logics). -
Bunched Hypersequent Calculi for Distributive Substructural Logics
EPiC Series in Computing Volume 46, 2017, Pages 417{434 LPAR-21. 21st International Conference on Logic for Programming, Artificial Intelligence and Reasoning Bunched Hypersequent Calculi for Distributive Substructural Logics Agata Ciabattoni and Revantha Ramanayake Technische Universit¨atWien, Austria fagata,[email protected]∗ Abstract We introduce a new proof-theoretic framework which enhances the expressive power of bunched sequents by extending them with a hypersequent structure. A general cut- elimination theorem that applies to bunched hypersequent calculi satisfying general rule conditions is then proved. We adapt the methods of transforming axioms into rules to provide cutfree bunched hypersequent calculi for a large class of logics extending the dis- tributive commutative Full Lambek calculus DFLe and Bunched Implication logic BI. The methodology is then used to formulate new logics equipped with a cutfree calculus in the vicinity of Boolean BI. 1 Introduction The wide applicability of logical methods and their use in new subject areas has resulted in an explosion of new logics. The usefulness of these logics often depends on the availability of an analytic proof calculus (formal proof system), as this provides a natural starting point for investi- gating metalogical properties such as decidability, complexity, interpolation and conservativity, for developing automated deduction procedures, and for establishing semantic properties like standard completeness [26]. A calculus is analytic when every derivation (formal proof) in the calculus has the property that every formula occurring in the derivation is a subformula of the formula that is ultimately proved (i.e. the subformula property). The use of an analytic proof calculus tremendously restricts the set of possible derivations of a given statement to deriva- tions with a discernible structure (in certain cases this set may even be finite). -
The Z of ZF and ZFC and ZF¬C
From SIAM News , Volume 41, Number 1, January/February 2008 The Z of ZF and ZFC and ZF ¬C Ernst Zermelo: An Approach to His Life and Work. By Heinz-Dieter Ebbinghaus, Springer, New York, 2007, 356 pages, $64.95. The Z, of course, is Ernst Zermelo (1871–1953). The F, in case you had forgotten, is Abraham Fraenkel (1891–1965), and the C is the notorious Axiom of Choice. The book under review, by a prominent logician at the University of Freiburg, is a splendid in-depth biography of a complex man, a treatment that shies away neither from personal details nor from the mathematical details of Zermelo’s creations. BOOK R EV IEW Zermelo was a Berliner whose early scientific work was in applied By Philip J. Davis mathematics: His PhD thesis (1894) was in the calculus of variations. He had thought about this topic for at least ten additional years when, in 1904, in collaboration with Hans Hahn, he wrote an article on the subject for the famous Enzyclopedia der Mathematische Wissenschaften . In point of fact, though he is remembered today primarily for his axiomatization of set theory, he never really gave up applications. In his Habilitation thesis (1899), Zermelo was arguing with Ludwig Boltzmann about the foun - dations of the kinetic theory of heat. Around 1929, he was working on the problem of the path of an airplane going in minimal time from A to B at constant speed but against a distribution of winds. This was a problem that engaged Levi-Civita, von Mises, Carathéodory, Philipp Frank, and even more recent investigators. -
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.