Abstract Algebraic Logic and the Deduction Theorem
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The Deduction Rule and Linear and Near-Linear Proof Simulations
The Deduction Rule and Linear and Near-linear Proof Simulations Maria Luisa Bonet¤ Department of Mathematics University of California, San Diego Samuel R. Buss¤ Department of Mathematics University of California, San Diego Abstract We introduce new proof systems for propositional logic, simple deduction Frege systems, general deduction Frege systems and nested deduction Frege systems, which augment Frege systems with variants of the deduction rule. We give upper bounds on the lengths of proofs in Frege proof systems compared to lengths in these new systems. As applications we give near-linear simulations of the propositional Gentzen sequent calculus and the natural deduction calculus by Frege proofs. The length of a proof is the number of lines (or formulas) in the proof. A general deduction Frege proof system provides at most quadratic speedup over Frege proof systems. A nested deduction Frege proof system provides at most a nearly linear speedup over Frege system where by \nearly linear" is meant the ratio of proof lengths is O(®(n)) where ® is the inverse Ackermann function. A nested deduction Frege system can linearly simulate the propositional sequent calculus, the tree-like general deduction Frege calculus, and the natural deduction calculus. Hence a Frege proof system can simulate all those proof systems with proof lengths bounded by O(n ¢ ®(n)). Also we show ¤Supported in part by NSF Grant DMS-8902480. 1 that a Frege proof of n lines can be transformed into a tree-like Frege proof of O(n log n) lines and of height O(log n). As a corollary of this fact we can prove that natural deduction and sequent calculus tree-like systems simulate Frege systems with proof lengths bounded by O(n log n). -
6.5 the Recursion Theorem
6.5. THE RECURSION THEOREM 417 6.5 The Recursion Theorem The recursion Theorem, due to Kleene, is a fundamental result in recursion theory. Theorem 6.5.1 (Recursion Theorem, Version 1 )Letϕ0,ϕ1,... be any ac- ceptable indexing of the partial recursive functions. For every total recursive function f, there is some n such that ϕn = ϕf(n). The recursion Theorem can be strengthened as follows. Theorem 6.5.2 (Recursion Theorem, Version 2 )Letϕ0,ϕ1,... be any ac- ceptable indexing of the partial recursive functions. There is a total recursive function h such that for all x ∈ N,ifϕx is total, then ϕϕx(h(x)) = ϕh(x). 418 CHAPTER 6. ELEMENTARY RECURSIVE FUNCTION THEORY A third version of the recursion Theorem is given below. Theorem 6.5.3 (Recursion Theorem, Version 3 ) For all n ≥ 1, there is a total recursive function h of n +1 arguments, such that for all x ∈ N,ifϕx is a total recursive function of n +1arguments, then ϕϕx(h(x,x1,...,xn),x1,...,xn) = ϕh(x,x1,...,xn), for all x1,...,xn ∈ N. As a first application of the recursion theorem, we can show that there is an index n such that ϕn is the constant function with output n. Loosely speaking, ϕn prints its own name. Let f be the recursive function such that f(x, y)=x for all x, y ∈ N. 6.5. THE RECURSION THEOREM 419 By the s-m-n Theorem, there is a recursive function g such that ϕg(x)(y)=f(x, y)=x for all x, y ∈ N. -
A Survey of Abstract Algebraic Logic 15 Bras
J. M. Font A Survey of Abstract Algebraic R. Jansana D. Pigozzi Logic Contents Introduction 14 1. The First Steps 16 1.1. Consequence operations and logics . 17 1.2. Logical matrices . 20 1.3. Lindenbaum-Tarski algebras . 22 2. The Lindenbaum-Tarski Process Fully Generalized 24 2.1. Frege's principles . 24 2.2. Algebras and matrices canonically associated with a logic . 26 3. The Core Theory of Abstract Algebraic Logic 29 3.1. Elements of the general theory of matrices . 29 3.2. Protoalgebraic logics . 33 3.3. Algebraizable logics . 38 3.4. The Leibniz hierarchy . 43 4. Extensions of the Core Theory 50 4.1. k-deductive systems and universal algebra . 50 4.2. Gentzen systems and their generalizations . 55 4.3. Equality-free universal Horn logic . 61 4.4. Algebras of Logic . 64 5. Generalized Matrix Semantics and Full Models 71 6. Extensions to More Complex Notions of Logic 79 6.1. The semantics-based approach . 80 6.2. The categorial approach . 85 References 88 Special Issue on Abstract Algebraic Logic { Part II Edited by Josep Maria Font, Ramon Jansana, and Don Pigozzi Studia Logica 74: 13{97, 2003. c 2003 Kluwer Academic Publishers. Printed in the Netherlands. 14 J. M. Font, R. Jansana, and D. Pigozzi Introduction Algebraic logic was born in the XIXth century with the work of Boole, De Morgan, Peirce, Schr¨oder, etc. on classical logic, see [12, 16]. They took logical equivalence rather than truth as the primitive logical predicate, and, exploiting the similarity between logical equivalence and equality, they devel- oped logical systems in which metalogical investigations take on a distinctly algebraic character. -
April 22 7.1 Recursion Theorem
CSE 431 Theory of Computation Spring 2014 Lecture 7: April 22 Lecturer: James R. Lee Scribe: Eric Lei Disclaimer: These notes have not been subjected to the usual scrutiny reserved for formal publications. They may be distributed outside this class only with the permission of the Instructor. An interesting question about Turing machines is whether they can reproduce themselves. A Turing machine cannot be be defined in terms of itself, but can it still somehow print its own source code? The answer to this question is yes, as we will see in the recursion theorem. Afterward we will see some applications of this result. 7.1 Recursion Theorem Our end goal is to have a Turing machine that prints its own source code and operates on it. Last lecture we proved the existence of a Turing machine called SELF that ignores its input and prints its source code. We construct a similar proof for the recursion theorem. We will also need the following lemma proved last lecture. ∗ ∗ Lemma 7.1 There exists a computable function q :Σ ! Σ such that q(w) = hPwi, where Pw is a Turing machine that prints w and hats. Theorem 7.2 (Recursion theorem) Let T be a Turing machine that computes a function t :Σ∗ × Σ∗ ! Σ∗. There exists a Turing machine R that computes a function r :Σ∗ ! Σ∗, where for every w, r(w) = t(hRi; w): The theorem says that for an arbitrary computable function t, there is a Turing machine R that computes t on hRi and some input. Proof: We construct a Turing Machine R in three parts, A, B, and T , where T is given by the statement of the theorem. -
Intuitionism on Gödel's First Incompleteness Theorem
The Yale Undergraduate Research Journal Volume 2 Issue 1 Spring 2021 Article 31 2021 Incomplete? Or Indefinite? Intuitionism on Gödel’s First Incompleteness Theorem Quinn Crawford Yale University Follow this and additional works at: https://elischolar.library.yale.edu/yurj Part of the Mathematics Commons, and the Philosophy Commons Recommended Citation Crawford, Quinn (2021) "Incomplete? Or Indefinite? Intuitionism on Gödel’s First Incompleteness Theorem," The Yale Undergraduate Research Journal: Vol. 2 : Iss. 1 , Article 31. Available at: https://elischolar.library.yale.edu/yurj/vol2/iss1/31 This Article is brought to you for free and open access by EliScholar – A Digital Platform for Scholarly Publishing at Yale. It has been accepted for inclusion in The Yale Undergraduate Research Journal by an authorized editor of EliScholar – A Digital Platform for Scholarly Publishing at Yale. For more information, please contact [email protected]. Incomplete? Or Indefinite? Intuitionism on Gödel’s First Incompleteness Theorem Cover Page Footnote Written for Professor Sun-Joo Shin’s course PHIL 437: Philosophy of Mathematics. This article is available in The Yale Undergraduate Research Journal: https://elischolar.library.yale.edu/yurj/vol2/iss1/ 31 Crawford: Intuitionism on Gödel’s First Incompleteness Theorem Crawford | Philosophy Incomplete? Or Indefinite? Intuitionism on Gödel’s First Incompleteness Theorem By Quinn Crawford1 1Department of Philosophy, Yale University ABSTRACT This paper analyzes two natural-looking arguments that seek to leverage Gödel’s first incompleteness theo- rem for and against intuitionism, concluding in both cases that the argument is unsound because it equivo- cates on the meaning of “proof,” which differs between formalism and intuitionism. -
Chapter 1 Logic and Set Theory
Chapter 1 Logic and Set Theory To criticize mathematics for its abstraction is to miss the point entirely. Abstraction is what makes mathematics work. If you concentrate too closely on too limited an application of a mathematical idea, you rob the mathematician of his most important tools: analogy, generality, and simplicity. – Ian Stewart Does God play dice? The mathematics of chaos In mathematics, a proof is a demonstration that, assuming certain axioms, some statement is necessarily true. That is, a proof is a logical argument, not an empir- ical one. One must demonstrate that a proposition is true in all cases before it is considered a theorem of mathematics. An unproven proposition for which there is some sort of empirical evidence is known as a conjecture. Mathematical logic is the framework upon which rigorous proofs are built. It is the study of the principles and criteria of valid inference and demonstrations. Logicians have analyzed set theory in great details, formulating a collection of axioms that affords a broad enough and strong enough foundation to mathematical reasoning. The standard form of axiomatic set theory is denoted ZFC and it consists of the Zermelo-Fraenkel (ZF) axioms combined with the axiom of choice (C). Each of the axioms included in this theory expresses a property of sets that is widely accepted by mathematicians. It is unfortunately true that careless use of set theory can lead to contradictions. Avoiding such contradictions was one of the original motivations for the axiomatization of set theory. 1 2 CHAPTER 1. LOGIC AND SET THEORY A rigorous analysis of set theory belongs to the foundations of mathematics and mathematical logic. -
What Is Abstract Algebraic Logic?
What is Abstract Algebraic Logic? Umberto Rivieccio University of Genoa Department of Philosophy Via Balbi 4 - Genoa, Italy email [email protected] Abstract Our aim is to answer the question of the title, explaining which kind of problems form the nucleus of the branch of algebraic logic that has come to be known as Abstract Algebraic Logic. We give a concise account of the birth and evolution of the field, that led from the discovery of the connections between certain logical systems and certain algebraic structures to a general theory of algebraization of logics. We consider first the so-called algebraizable logics, which may be regarded as a paradigmatic case in Abstract Algebraic Logic; then we shift our attention to some wider classes of logics and to the more general framework in which they are studied. Finally, we review some other topics in Abstract Algebraic Logic that, though equally interesting and promising for future research, could not be treated here in detail. 1 Introduction Algebraic logic can be described in very general terms as the study of the relations between algebra and logic. One of the main reasons that motivate such a study is the possibility to treat logical problems with algebraic methods. This means that, in order to solve a logical problem, we may try to translate it into algebraic terms, find the solution using algebraic techniques, and then translate back the result into logic. This strategy proved to be fruitful, since algebra is an old and well{established field of mathematics, that offers powerful tools to treat problems that would possibly be much harder to solve using the logical machinery alone. -
Subverting the Classical Picture: (Co)Algebra, Constructivity and Modalities∗
Informatik 8, FAU Erlangen-Nürnberg [email protected] Subverting the Classical Picture: (Co)algebra, Constructivity and Modalities∗ Tadeusz Litak Contents 1. Subverting the Classical Picture 2 2. Beyond Frege and Russell: Modalities Instead of Predicates 6 3. Beyond Peirce, Tarski and Kripke: Coalgebras and CPL 11 3.1. Introduction to the Coalgebraic Framework ............. 11 3.2. Coalgebraic Predicate Logic ...................... 14 4. Beyond Cantor: Effectivity, Computability and Determinacy 16 4.1. Finite vs. Classical Model Theory: The Case of CPL ........ 17 4.2. Effectivity, Choice and Determinacy in Formal Economics ..... 19 4.3. Quasiconstructivity and Modal Logic ................. 21 5. Beyond Scott, Montague and Moss: Algebras and Possibilities 23 5.1. Dual Algebras, Neighbourhood Frames and CA-baes ........ 23 5.2. A Hierachy of (In)completeness Notions for Normal Modal Logics . 24 5.3. Possibility Semantics and Complete Additivity ........... 26 5.4. GQM: One Modal Logic to Rule Them All? ............. 28 6. Beyond Boole and Lewis: Intuitionistic Modal Logic 30 6.1. Curry-Howard Correspondence, Constructive Logic and 2 ..... 31 6.2. Guarded Recursion and Its Neighbours ................ 33 6.3. KM, mHC, LC and the Topos of Trees ................ 34 6.4. Between Boole and Heyting: Negative Translations ......... 35 7. Unifying Lewis and Brouwer 37 7.1. Constructive Strict Implication .................... 37 7.2. Relevance, Resources and (G)BI .................... 40 ∗Introductory overview chapter for my cumulative habilitation thesis as required by FAU Erlangen-Nürnberg regulations (submitted in 2018, finally approved in May 2019). Available online at https://www8.cs.fau. de/ext/litak/gitpipe/tadeusz_habilitation.pdf. 1 8. Beyond Brouwer, Heyting and Kolmogorov: Nondistributivity 43 8.1. -
What Is a Logic Translation? in Memoriam Joseph Goguen
, 1{29 c 2009 Birkh¨auserVerlag Basel/Switzerland What is a Logic Translation? In memoriam Joseph Goguen Till Mossakowski, R˘azvan Diaconescu and Andrzej Tarlecki Abstract. We study logic translations from an abstract perspective, with- out any commitment to the structure of sentences and the nature of logical entailment, which also means that we cover both proof-theoretic and model- theoretic entailment. We show how logic translations induce notions of logical expressiveness, consistency strength and sublogic, leading to an explanation of paradoxes that have been described in the literature. Connectives and quanti- fiers, although not present in the definition of logic and logic translation, can be recovered by their abstract properties and are preserved and reflected by translations under suitable conditions. 1. Introduction The development of a notion of logic translation presupposes the development of a notion of logic. Logic has been characterised as the study of sound reasoning, of what follows from what. Hence, the notion of logical consequence is central. It can be obtained in two complementary ways: via the model-theoretic notion of satisfaction in a model and via the proof-theoretic notion of derivation according to proof rules. These notions can be captured in a completely abstract manner, avoiding any particular commitment to the nature of models, sentences, or rules. The paper [40], which is the predecessor of our current work, explains the notion of logic along these lines. Similarly, an abstract notion of logic translation can be developed, both at the model-theoretic and at the proof-theoretic level. A central question concern- ing such translations is their interaction with logical structure, such as given by logical connectives, and logical properties. -
Chapter 9: Initial Theorems About Axiom System
Initial Theorems about Axiom 9 System AS1 1. Theorems in Axiom Systems versus Theorems about Axiom Systems ..................................2 2. Proofs about Axiom Systems ................................................................................................3 3. Initial Examples of Proofs in the Metalanguage about AS1 ..................................................4 4. The Deduction Theorem.......................................................................................................7 5. Using Mathematical Induction to do Proofs about Derivations .............................................8 6. Setting up the Proof of the Deduction Theorem.....................................................................9 7. Informal Proof of the Deduction Theorem..........................................................................10 8. The Lemmas Supporting the Deduction Theorem................................................................11 9. Rules R1 and R2 are Required for any DT-MP-Logic........................................................12 10. The Converse of the Deduction Theorem and Modus Ponens .............................................14 11. Some General Theorems About ......................................................................................15 12. Further Theorems About AS1.............................................................................................16 13. Appendix: Summary of Theorems about AS1.....................................................................18 2 Hardegree, -
5 Deduction in First-Order Logic
5 Deduction in First-Order Logic The system FOLC. Let C be a set of constant symbols. FOLC is a system of deduction for # the language LC . Axioms: The following are axioms of FOLC. (1) All tautologies. (2) Identity Axioms: (a) t = t for all terms t; (b) t1 = t2 ! (A(x; t1) ! A(x; t2)) for all terms t1 and t2, all variables x, and all formulas A such that there is no variable y occurring in t1 or t2 such that there is free occurrence of x in A in a subformula of A of the form 8yB. (3) Quantifier Axioms: 8xA ! A(x; t) for all formulas A, variables x, and terms t such that there is no variable y occurring in t such that there is a free occurrence of x in A in a subformula of A of the form 8yB. Rules of Inference: A; (A ! B) Modus Ponens (MP) B (A ! B) Quantifier Rule (QR) (A ! 8xB) provided the variable x does not occur free in A. Discussion of the axioms and rules. (1) We would have gotten an equivalent system of deduction if instead of taking all tautologies as axioms we had taken as axioms all instances (in # LC ) of the three schemas on page 16. All instances of these schemas are tautologies, so the change would have not have increased what we could 52 deduce. In the other direction, we can apply the proof of the Completeness Theorem for SL by thinking of all sententially atomic formulas as sentence # letters. The proof so construed shows that every tautology in LC is deducible using MP and schemas (1){(3). -
Explanations
© Copyright, Princeton University Press. No part of this book may be distributed, posted, or reproduced in any form by digital or mechanical means without prior written permission of the publisher. CHAPTER 1 Explanations 1.1 SALLIES Language is an instrument of Logic, but not an indispensable instrument. Boole 1847a, 118 We know that mathematicians care no more for logic than logicians for mathematics. The two eyes of exact science are mathematics and logic; the mathematical sect puts out the logical eye, the logical sect puts out the mathematical eye; each believing that it sees better with one eye than with two. De Morgan 1868a,71 That which is provable, ought not to be believed in science without proof. Dedekind 1888a, preface If I compare arithmetic with a tree that unfolds upwards in a multitude of techniques and theorems whilst the root drives into the depthswx . Frege 1893a, xiii Arithmetic must be discovered in just the same sense in which Columbus discovered the West Indies, and we no more create numbers than he created the Indians. Russell 1903a, 451 1.2 SCOPE AND LIMITS OF THE BOOK 1.2.1 An outline history. The story told here from §3 onwards is re- garded as well known. It begins with the emergence of set theory in the 1870s under the inspiration of Georg Cantor, and the contemporary development of mathematical logic by Gottlob Frege andŽ. especially Giuseppe Peano. A cumulation of these and some related movements was achieved in the 1900s with the philosophy of mathematics proposed by Alfred North Whitehead and Bertrand Russell.