Chapter 4/Proof
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Tt-Satisfiable
CMPSCI 601: Recall From Last Time Lecture 6 Boolean Syntax: ¡ ¢¤£¦¥¨§¨£ © §¨£ § Boolean variables: A boolean variable represents an atomic statement that may be either true or false. There may be infinitely many of these available. Boolean expressions: £ atomic: , (“top”), (“bottom”) § ! " # $ , , , , , for Boolean expressions Note that any particular expression is a finite string, and thus may use only finitely many variables. £ £ A literal is an atomic expression or its negation: , , , . As you may know, the choice of operators is somewhat arbitary as long as we have a complete set, one that suf- fices to simulate all boolean functions. On HW#1 we ¢ § § ! argued that is already a complete set. 1 CMPSCI 601: Boolean Logic: Semantics Lecture 6 A boolean expression has a meaning, a truth value of true or false, once we know the truth values of all the individual variables. ¢ £ # ¡ A truth assignment is a function ¢ true § false , where is the set of all variables. An as- signment is appropriate to an expression ¤ if it assigns a value to all variables used in ¤ . ¡ The double-turnstile symbol ¥ (read as “models”) de- notes the relationship between a truth assignment and an ¡ ¥ ¤ expression. The statement “ ” (read as “ models ¤ ¤ ”) simply says “ is true under ”. 2 ¡ ¤ ¥ ¤ If is appropriate to , we define when is true by induction on the structure of ¤ : is true and is false for any , £ A variable is true iff says that it is, ¡ ¡ ¡ ¡ " ! ¥ ¤ ¥ ¥ If ¤ , iff both and , ¡ ¡ ¡ ¡ " ¥ ¤ ¥ ¥ If ¤ , iff either or or both, ¡ ¡ ¡ ¡ " # ¥ ¤ ¥ ¥ If ¤ , unless and , ¡ ¡ ¡ ¡ $ ¥ ¤ ¥ ¥ If ¤ , iff and are both true or both false. 3 Definition 6.1 A boolean expression ¤ is satisfiable iff ¡ ¥ ¤ there exists . -
Proof Theory Can Be Viewed As the General Study of Formal Deductive Systems
Proof Theory Jeremy Avigad December 19, 2017 Abstract Proof theory began in the 1920’s as a part of Hilbert’s program, which aimed to secure the foundations of mathematics by modeling infinitary mathematics with formal axiomatic systems and proving those systems consistent using restricted, finitary means. The program thus viewed mathematics as a system of reasoning with precise linguistic norms, governed by rules that can be described and studied in concrete terms. Today such a viewpoint has applications in mathematics, computer science, and the philosophy of mathematics. Keywords: proof theory, Hilbert’s program, foundations of mathematics 1 Introduction At the turn of the nineteenth century, mathematics exhibited a style of argumentation that was more explicitly computational than is common today. Over the course of the century, the introduction of abstract algebraic methods helped unify developments in analysis, number theory, geometry, and the theory of equations, and work by mathematicians like Richard Dedekind, Georg Cantor, and David Hilbert towards the end of the century introduced set-theoretic language and infinitary methods that served to downplay or suppress computational content. This shift in emphasis away from calculation gave rise to concerns as to whether such methods were meaningful and appropriate in mathematics. The discovery of paradoxes stemming from overly naive use of set-theoretic language and methods led to even more pressing concerns as to whether the modern methods were even consistent. This led to heated debates in the early twentieth century and what is sometimes called the “crisis of foundations.” In lectures presented in 1922, Hilbert launched his Beweistheorie, or Proof Theory, which aimed to justify the use of modern methods and settle the problem of foundations once and for all. -
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, -
Systematic Construction of Natural Deduction Systems for Many-Valued Logics
23rd International Symposium on Multiple Valued Logic. Sacramento, CA, May 1993 Proceedings. (IEEE Press, Los Alamitos, 1993) pp. 208{213 Systematic Construction of Natural Deduction Systems for Many-valued Logics Matthias Baaz∗ Christian G. Ferm¨ullery Richard Zachy Technische Universit¨atWien, Austria Abstract sion.) Each position i corresponds to one of the truth values, vm is the distinguished truth value. The in- A construction principle for natural deduction sys- tended meaning is as follows: Derive that at least tems for arbitrary finitely-many-valued first order log- one formula of Γm takes the value vm under the as- ics is exhibited. These systems are systematically ob- sumption that no formula in Γi takes the value vi tained from sequent calculi, which in turn can be au- (1 i m 1). ≤ ≤ − tomatically extracted from the truth tables of the log- Our starting point for the construction of natural ics under consideration. Soundness and cut-free com- deduction systems are sequent calculi. (A sequent is pleteness of these sequent calculi translate into sound- a tuple Γ1 ::: Γm, defined to be satisfied by an ness, completeness and normal form theorems for the interpretationj iffj for some i 1; : : : ; m at least one 2 f g natural deduction systems. formula in Γi takes the truth value vi.) For each pair of an operator 2 or quantifier Q and a truth value vi 1 Introduction we construct a rule introducing a formula of the form 2(A ;:::;A ) or (Qx)A(x), respectively, at position i The study of natural deduction systems for many- 1 n of a sequent. -
Complexities of Proof-Theoretical Reductions
Complexities of Proof-Theoretical Reductions Michael Toppel Submitted in accordance with the requirements for the degree of Doctor of Philosophy The University of Leeds Department of Pure Mathematics September 2016 iii The candidate confirms that the work submitted is his own and that appropriate credit has been given where reference has been made to the work of others. This copy has been supplied on the understanding that it is copyright material and that no quotation from the thesis may be published without proper acknowledgement. c 2016 The University of Leeds and Michael Toppel iv v Abstract The present thesis is a contribution to a project that is carried out by Michael Rathjen 0 and Andreas Weiermann to give a general method to study the proof-complexity of Σ1- sentences. This general method uses the generalised ordinal-analysis that was given by Buchholz, Ruede¨ and Strahm in [5] and [44] as well as the generalised characterisation of provable-recursive functions of PA + TI(≺ α) that was given by Weiermann in [60]. The present thesis links these two methods by giving an explicit elementary bound for the i proof-complexity increment that occurs after the transition from the theory IDc ! + TI(≺ α), which was used by Ruede¨ and Strahm, to the theory PA + TI(≺ α), which was analysed by Weiermann. vi vii Contents Abstract . v Contents . vii Introduction 1 1 Justifying the use of Multi-Conclusion Sequents 5 1.1 Introduction . 5 1.2 A Gentzen-semantics . 8 1.3 Multi-Conclusion Sequents . 15 1.4 Comparison with other Positions and Responses to Objections . -
Chapter 13: Formal Proofs and Quantifiers
Chapter 13: Formal Proofs and Quantifiers § 13.1 Universal quantifier rules Universal Elimination (∀ Elim) ∀x S(x) ❺ S(c) Here x stands for any variable, c stands for any individual constant, and S(c) stands for the result of replacing all free occurrences of x in S(x) with c. Example 1. ∀x ∃y (Adjoins(x, y) ∧ SameSize(y, x)) 2. ∃y (Adjoins(b, y) ∧ SameSize(y, b)) ∀ Elim: 1 General Conditional Proof (∀ Intro) ✾c P(c) Where c does not occur outside Q(c) the subproof where it is introduced. ❺ ∀x (P(x) → Q(x)) There is an important bit of new notation here— ✾c , the “boxed constant” at the beginning of the assumption line. This says, in effect, “let’s call it c.” To enter the boxed constant in Fitch, start a new subproof and click on the downward pointing triangle ❼. This will open a menu that lets you choose the constant you wish to use as a name for an arbitrary object. Your subproof will typically end with some sentence containing this constant. In giving the justification for the universal generalization, we cite the entire subproof (as we do in the case of → Intro). Notice that although c may not occur outside the subproof where it is introduced, it may occur again inside a subproof within the original subproof. Universal Introduction (∀ Intro) ✾c Where c does not occur outside the subproof where it is P(c) introduced. ❺ ∀x P(x) Remember, any time you set up a subproof for ∀ Intro, you must choose a “boxed constant” on the assumption line of the subproof, even if there is no sentence on the assumption line. -
An Integration of Resolution and Natural Deduction Theorem Proving
From: AAAI-86 Proceedings. Copyright ©1986, AAAI (www.aaai.org). All rights reserved. An Integration of Resolution and Natural Deduction Theorem Proving Dale Miller and Amy Felty Computer and Information Science University of Pennsylvania Philadelphia, PA 19104 Abstract: We present a high-level approach to the integra- ble of translating between them. In order to achieve this goal, tion of such different theorem proving technologies as resolution we have designed a programming language which permits proof and natural deduction. This system represents natural deduc- structures as values and types. This approach builds on and ex- tion proofs as X-terms and resolution refutations as the types of tends the LCF approach to natural deduction theorem provers such X-terms. These type structures, called ezpansion trees, are by replacing the LCF notion of a uakfation with explicit term essentially formulas in which substitution terms are attached to representation of proofs. The terms which represent proofs are quantifiers. As such, this approach to proofs and their types ex- given types which generalize the formulas-as-type notion found tends the formulas-as-type notion found in proof theory. The in proof theory [Howard, 19691. Resolution refutations are seen LCF notion of tactics and tacticals can also be extended to in- aa specifying the type of a natural deduction proofs. This high corporate proofs as typed X-terms. Such extended tacticals can level view of proofs as typed terms can be easily combined with be used to program different interactive and automatic natural more standard aspects of LCF to yield the integration for which Explicit representation of proofs deduction theorem provers. -
Natural Deduction and the Curry-Howard-Isomorphism
Natural Deduction and the Curry-Howard-Isomorphism Andreas Abel August 2016 Abstract We review constructive propositional logic and natural deduction and connect it to the simply-typed lambda-calculus with the Curry- Howard Isomorphism. Constructive Logic A fundamental property of constructive logic is the disjunction property: If the disjunction A _ B is provable, then either A is provable or B is provable. This property is not compatible with the principle of the excluded middle (tertium non datur), which states that A _:A holds for any proposition A. While each fool can state the classical tautology \aliens exist or don't", this certainly does not give us a means to decide whether aliens exist or not. A constructive proof of the fool's statement would require either showcasing an alien or a stringent argument for the impossibility of their existence.1 1 Natural deduction for propositional logic The proof calculus of natural deduction goes back to Gentzen[1935]. 1 For a more mathematical example of undecidability, refer to the continuum hypothesis CH which states that no cardinal exists between the set of the natural numbers and the set of reals. It is independent of ZFC, Zermelo-Fr¨ankel set theory with the axiom of choice, meaning that in ZFC, neither CH nor :CH is provable. 1 1.1 Propositions Formulæ of propositional logic are given by the following grammar: P; Q atomic proposition A; B; C ::= P j A ) B implication j A ^ B j > conjunction, truth j A _ B j ? disjunction, absurdity Even though we write formulas in linearized (string) form, we think of them as (abstract syntax) trees. -
Logic and Proof Release 3.18.4
Logic and Proof Release 3.18.4 Jeremy Avigad, Robert Y. Lewis, and Floris van Doorn Sep 10, 2021 CONTENTS 1 Introduction 1 1.1 Mathematical Proof ............................................ 1 1.2 Symbolic Logic .............................................. 2 1.3 Interactive Theorem Proving ....................................... 4 1.4 The Semantic Point of View ....................................... 5 1.5 Goals Summarized ............................................ 6 1.6 About this Textbook ........................................... 6 2 Propositional Logic 7 2.1 A Puzzle ................................................. 7 2.2 A Solution ................................................ 7 2.3 Rules of Inference ............................................ 8 2.4 The Language of Propositional Logic ................................... 15 2.5 Exercises ................................................. 16 3 Natural Deduction for Propositional Logic 17 3.1 Derivations in Natural Deduction ..................................... 17 3.2 Examples ................................................. 19 3.3 Forward and Backward Reasoning .................................... 20 3.4 Reasoning by Cases ............................................ 22 3.5 Some Logical Identities .......................................... 23 3.6 Exercises ................................................. 24 4 Propositional Logic in Lean 25 4.1 Expressions for Propositions and Proofs ................................. 25 4.2 More commands ............................................ -
On Synthetic Undecidability in Coq, with an Application to the Entscheidungsproblem
On Synthetic Undecidability in Coq, with an Application to the Entscheidungsproblem Yannick Forster Dominik Kirst Gert Smolka Saarland University Saarland University Saarland University Saarbrücken, Germany Saarbrücken, Germany Saarbrücken, Germany [email protected] [email protected] [email protected] Abstract like decidability, enumerability, and reductions are avail- We formalise the computational undecidability of validity, able without reference to a concrete model of computation satisfiability, and provability of first-order formulas follow- such as Turing machines, general recursive functions, or ing a synthetic approach based on the computation native the λ-calculus. For instance, representing a given decision to Coq’s constructive type theory. Concretely, we consider problem by a predicate p on a type X, a function f : X ! B Tarski and Kripke semantics as well as classical and intu- with 8x: p x $ f x = tt is a decision procedure, a function itionistic natural deduction systems and provide compact д : N ! X with 8x: p x $ ¹9n: д n = xº is an enumer- many-one reductions from the Post correspondence prob- ation, and a function h : X ! Y with 8x: p x $ q ¹h xº lem (PCP). Moreover, developing a basic framework for syn- for a predicate q on a type Y is a many-one reduction from thetic computability theory in Coq, we formalise standard p to q. Working formally with concrete models instead is results concerning decidability, enumerability, and reducibil- cumbersome, given that every defined procedure needs to ity without reference to a concrete model of computation. be shown representable by a concrete entity of the model. -
1 Symbols (2286)
1 Symbols (2286) USV Symbol Macro(s) Description 0009 \textHT <control> 000A \textLF <control> 000D \textCR <control> 0022 ” \textquotedbl QUOTATION MARK 0023 # \texthash NUMBER SIGN \textnumbersign 0024 $ \textdollar DOLLAR SIGN 0025 % \textpercent PERCENT SIGN 0026 & \textampersand AMPERSAND 0027 ’ \textquotesingle APOSTROPHE 0028 ( \textparenleft LEFT PARENTHESIS 0029 ) \textparenright RIGHT PARENTHESIS 002A * \textasteriskcentered ASTERISK 002B + \textMVPlus PLUS SIGN 002C , \textMVComma COMMA 002D - \textMVMinus HYPHEN-MINUS 002E . \textMVPeriod FULL STOP 002F / \textMVDivision SOLIDUS 0030 0 \textMVZero DIGIT ZERO 0031 1 \textMVOne DIGIT ONE 0032 2 \textMVTwo DIGIT TWO 0033 3 \textMVThree DIGIT THREE 0034 4 \textMVFour DIGIT FOUR 0035 5 \textMVFive DIGIT FIVE 0036 6 \textMVSix DIGIT SIX 0037 7 \textMVSeven DIGIT SEVEN 0038 8 \textMVEight DIGIT EIGHT 0039 9 \textMVNine DIGIT NINE 003C < \textless LESS-THAN SIGN 003D = \textequals EQUALS SIGN 003E > \textgreater GREATER-THAN SIGN 0040 @ \textMVAt COMMERCIAL AT 005C \ \textbackslash REVERSE SOLIDUS 005E ^ \textasciicircum CIRCUMFLEX ACCENT 005F _ \textunderscore LOW LINE 0060 ‘ \textasciigrave GRAVE ACCENT 0067 g \textg LATIN SMALL LETTER G 007B { \textbraceleft LEFT CURLY BRACKET 007C | \textbar VERTICAL LINE 007D } \textbraceright RIGHT CURLY BRACKET 007E ~ \textasciitilde TILDE 00A0 \nobreakspace NO-BREAK SPACE 00A1 ¡ \textexclamdown INVERTED EXCLAMATION MARK 00A2 ¢ \textcent CENT SIGN 00A3 £ \textsterling POUND SIGN 00A4 ¤ \textcurrency CURRENCY SIGN 00A5 ¥ \textyen YEN SIGN 00A6 -
Data Stream Algorithms Lecture Notes
CS49: Data Stream Algorithms Lecture Notes, Fall 2011 Amit Chakrabarti Dartmouth College Latest Update: October 14, 2014 DRAFT Acknowledgements These lecture notes began as rough scribe notes for a Fall 2009 offering of the course “Data Stream Algorithms” at Dartmouth College. The initial scribe notes were prepared mostly by students enrolled in the course in 2009. Subsequently, during a Fall 2011 offering of the course, I edited the notes heavily, bringing them into presentable form, with the aim being to create a resource for students and other teachers of this material. I would like to acknowledge the initial effort by the 2009 students that got these notes started: Radhika Bhasin, Andrew Cherne, Robin Chhetri, Joe Cooley, Jon Denning, Alina Dja- mankulova, Ryan Kingston, Ranganath Kondapally, Adrian Kostrubiak, Konstantin Kutzkow, Aarathi Prasad, Priya Natarajan, and Zhenghui Wang. DRAFT Contents 0 Preliminaries: The Data Stream Model 5 0.1 TheBasicSetup................................... ........... 5 0.2 TheQualityofanAlgorithm’sAnswer . ................. 5 0.3 VariationsoftheBasicSetup . ................ 6 1 Finding Frequent Items Deterministically 7 1.1 TheProblem...................................... .......... 7 1.2 TheMisra-GriesAlgorithm. ............... 7 1.3 AnalysisoftheAlgorithm . .............. 7 2 Estimating the Number of Distinct Elements 9 2.1 TheProblem...................................... .......... 9 2.2 TheAlgorithm .................................... .......... 9 2.3 TheQualityoftheAlgorithm’sEstimate . ..................