Formal Proof—Getting Started Freek Wiedijk
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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. -
AMATH 731: Applied Functional Analysis Lecture Notes
AMATH 731: Applied Functional Analysis Lecture Notes Sumeet Khatri November 24, 2014 Table of Contents List of Tables ................................................... v List of Theorems ................................................ ix List of Definitions ................................................ xii Preface ....................................................... xiii 1 Review of Real Analysis .......................................... 1 1.1 Convergence and Cauchy Sequences...............................1 1.2 Convergence of Sequences and Cauchy Sequences.......................1 2 Measure Theory ............................................... 2 2.1 The Concept of Measurability...................................3 2.1.1 Simple Functions...................................... 10 2.2 Elementary Properties of Measures................................ 11 2.2.1 Arithmetic in [0, ] .................................... 12 1 2.3 Integration of Positive Functions.................................. 13 2.4 Integration of Complex Functions................................. 14 2.5 Sets of Measure Zero......................................... 14 2.6 Positive Borel Measures....................................... 14 2.6.1 Vector Spaces and Topological Preliminaries...................... 14 2.6.2 The Riesz Representation Theorem........................... 14 2.6.3 Regularity Properties of Borel Measures........................ 14 2.6.4 Lesbesgue Measure..................................... 14 2.6.5 Continuity Properties of Measurable Functions................... -
List of Theorems from Geometry 2321, 2322
List of Theorems from Geometry 2321, 2322 Stephanie Hyland [email protected] April 24, 2010 There’s already a list of geometry theorems out there, but the course has changed since, so here’s a new one. They’re in order of ‘appearance in my notes’, which corresponds reasonably well to chronolog- ical order. 24 onwards is Hilary term stuff. The following theorems have actually been asked (in either summer or schol papers): 5, 7, 8, 17, 18, 20, 21, 22, 26, 27, 30 a), 31 (associative only), 35, 36 a), 37, 38, 39, 43, 45, 47, 48. Definitions are also asked, which aren’t included here. 1. On a finite-dimensional real vector space, the statement ‘V is open in M’ is independent of the choice of norm on M. ′ f f i 2. Let Rn ⊃ V −→ Rm be differentiable with f = (f 1, ..., f m). Then Rn −→ Rm, and f ′ = ∂f ∂xj f 3. Let M ⊃ V −→ N,a ∈ V . Then f is differentiable at a ⇒ f is continuous at a. 4. f = (f 1, ...f n) continuous ⇔ f i continuous, and same for differentiable. 5. The chain rule for functions on finite-dimensional real vector spaces. 6. The chain rule for functions of several real variables. f 7. Let Rn ⊃ V −→ R, V open. Then f is C1 ⇔ ∂f exists and is continuous, for i =1, ..., n. ∂xi 2 2 Rn f R 2 ∂ f ∂ f 8. Let ⊃ V −→ , V open. f is C . Then ∂xi∂xj = ∂xj ∂xi 9. (φ ◦ ψ)∗ = φ∗ ◦ ψ∗, where φ, ψ are maps of manifolds, and φ∗ is the push-forward of φ. -
Chapter 10: Symbolic Trails and Formal Proofs of Validity, Part 2
Essential Logic Ronald C. Pine CHAPTER 10: SYMBOLIC TRAILS AND FORMAL PROOFS OF VALIDITY, PART 2 Introduction In the previous chapter there were many frustrating signs that something was wrong with our formal proof method that relied on only nine elementary rules of validity. Very simple, intuitive valid arguments could not be shown to be valid. For instance, the following intuitively valid arguments cannot be shown to be valid using only the nine rules. Somalia and Iran are both foreign policy risks. Therefore, Iran is a foreign policy risk. S I / I Either Obama or McCain was President of the United States in 2009.1 McCain was not President in 2010. So, Obama was President of the United States in 2010. (O v C) ~(O C) ~C / O If the computer networking system works, then Johnson and Kaneshiro will both be connected to the home office. Therefore, if the networking system works, Johnson will be connected to the home office. N (J K) / N J Either the Start II treaty is ratified or this landmark treaty will not be worth the paper it is written on. Therefore, if the Start II treaty is not ratified, this landmark treaty will not be worth the paper it is written on. R v ~W / ~R ~W 1 This or statement is obviously exclusive, so note the translation. 427 If the light is on, then the light switch must be on. So, if the light switch in not on, then the light is not on. L S / ~S ~L Thus, the nine elementary rules of validity covered in the previous chapter must be only part of a complete system for constructing formal proofs of validity. -
Calculus I – Math
Math 380: Low-Dimensional Topology Instructor: Aaron Heap Office: South 330C E-mail: [email protected] Web Page: http://www.geneseo.edu/math/heap Textbook: Topology Now!, by Robert Messer & Philip Straffin. Course Info: We will cover topological equivalence, deformations, knots and links, surfaces, three- dimensional manifolds, and the fundamental group. Topics are subject to change depending on the progress of the class, and various topics may be skipped due to time constraints. An accurate reading schedule will be posted on the website, and you should check it often. By the time you take this course, most of you should be fairly comfortable with mathematical proofs. Although this course only has multivariable calculus, elementary linear algebra, and mathematical proofs as prerequisites, students are strongly encouraged to take abstract algebra (Math 330) prior to this course or concurrently. It requires a certain level of mathematical sophistication. There will be a lot of new terminology you must learn, and we will be doing a significant number of proofs. Please note that we will work on developing your independent reading skills in Mathematics and your ability to learn and use definitions and theorems. I certainly won't be able to cover in class all the material you will be required to learn. As a result, you will be expected to do a lot of reading. The reading assignments will be on topics to be discussed in the following lecture to enable you to ask focused questions in the class and to better understand the material. It is imperative that you keep up with the reading assignments. -
Fundamental Theorems in Mathematics
SOME FUNDAMENTAL THEOREMS IN MATHEMATICS OLIVER KNILL Abstract. An expository hitchhikers guide to some theorems in mathematics. Criteria for the current list of 243 theorems are whether the result can be formulated elegantly, whether it is beautiful or useful and whether it could serve as a guide [6] without leading to panic. The order is not a ranking but ordered along a time-line when things were writ- ten down. Since [556] stated “a mathematical theorem only becomes beautiful if presented as a crown jewel within a context" we try sometimes to give some context. Of course, any such list of theorems is a matter of personal preferences, taste and limitations. The num- ber of theorems is arbitrary, the initial obvious goal was 42 but that number got eventually surpassed as it is hard to stop, once started. As a compensation, there are 42 “tweetable" theorems with included proofs. More comments on the choice of the theorems is included in an epilogue. For literature on general mathematics, see [193, 189, 29, 235, 254, 619, 412, 138], for history [217, 625, 376, 73, 46, 208, 379, 365, 690, 113, 618, 79, 259, 341], for popular, beautiful or elegant things [12, 529, 201, 182, 17, 672, 673, 44, 204, 190, 245, 446, 616, 303, 201, 2, 127, 146, 128, 502, 261, 172]. For comprehensive overviews in large parts of math- ematics, [74, 165, 166, 51, 593] or predictions on developments [47]. For reflections about mathematics in general [145, 455, 45, 306, 439, 99, 561]. Encyclopedic source examples are [188, 705, 670, 102, 192, 152, 221, 191, 111, 635]. -
Math 025-1,2 List of Theorems and Definitions Fall 2010
Math 025-1,2 List of Theorems and Definitions Fall 2010 Here are the 19 theorems of Math 25: Domination Law (aka Monotonicity Law) If f and g are integrable functions on [a; b] such that R b R b f(x) ≤ g(x) for all x 2 [a; b], then a f(x) dx ≤ a g(x) dx. R b Positivity Law If f is a nonnegative, integrable function on [a; b], then a f(x) dx ≥ 0. Also, if f(x) is R b a nonnegative, continuous function on [a; b] and a f(x) dx = 0, then f(x) = 0 for all x 2 [a; b]. Max-Min Inequality If f(x) is an integrable function on [a; b], then Z b (min value of f(x) on [a; b]) · (b − a) ≤ f(x) dx ≤ (max value of f(x) on [a; b]) · (b − a): a Triangle Inequality (for Integrals) Let f :[a; b] ! R be integrable. Then Z b Z b f(x) dx ≤ jf(x)j dx: a a Mean Value Theorem for Integrals Let f : R ! R be continuous on [a; b]. Then there exists a number c 2 (a; b) such that 1 Z b f(c) = f(x) dx: b − a a Fundamental Theorem of Calculus (one part) Let f :[a; b] ! R be continuous and define F : R x [a; b] ! R by F (x) = a f(t) dt. Then F is differentiable (hence continuous) on [a; b] and F 0(x) = f(x). Fundamental Theorem of Calculus (other part) Let f :[a; b] ! R be continuous and let F be any antiderivative of f on [a; b]. -
Logic and Proof
Logic and Proof Computer Science Tripos Part IB Michaelmas Term Lawrence C Paulson Computer Laboratory University of Cambridge [email protected] Copyright c 2000 by Lawrence C. Paulson Contents 1 Introduction and Learning Guide 1 2 Propositional Logic 3 3 Proof Systems for Propositional Logic 12 4 Ordered Binary Decision Diagrams 19 5 First-order Logic 22 6 Formal Reasoning in First-Order Logic 29 7 Clause Methods for Propositional Logic 34 8 Skolem Functions and Herbrand’s Theorem 42 9 Unification 49 10 Applications of Unification 58 11 Modal Logics 65 12 Tableaux-Based Methods 70 i ii 1 1 Introduction and Learning Guide This course gives a brief introduction to logic, with including the resolution method of theorem-proving and its relation to the programming language Prolog. Formal logic is used for specifying and verifying computer systems and (some- times) for representing knowledge in Artificial Intelligence programs. The course should help you with Prolog for AI and its treatment of logic should be helpful for understanding other theoretical courses. Try to avoid getting bogged down in the details of how the various proof methods work, since you must also acquire an intuitive feel for logical reasoning. The most suitable course text is this book: Michael Huth and Mark Ryan, Logic in Computer Science: Modelling and Reasoning about Systems (CUP, 2000) It costs £18.36 from Amazon. It covers most aspects of this course with the ex- ception of resolution theorem proving. It includes material that may be useful in Specification and Verification II next year, namely symbolic model checking. -
Calculus I Teacher(S): Mr
Remote Learning Packet NB: Please keep all work produced this week. Details regarding how to turn in this work will be forthcoming. April 20 - 24, 2020 Course: 11 Calculus I Teacher(s): Mr. Simmons Weekly Plan: Monday, April 20 ⬜ Revise your proof of Fermat’s Theorem. Tuesday, April 21 ⬜ Extreme Value Theorem proof and diagram. Wednesday, April 22 ⬜ Diagrams for Fermat’s Theorem, Rolle’s Theorem, and the MVT Thursday, April 23 ⬜ Prove Rolle’s Theorem. Friday, April 24 ⬜ Prove the MVT. Statement of Academic Honesty I affirm that the work completed from the packet I affirm that, to the best of my knowledge, my is mine and that I completed it independently. child completed this work independently _______________________________________ _______________________________________ Student Signature Parent Signature Monday, April 20 I would like to apologize, because in the list of theorems that I sent you, there was a typo. In the hypotheses for two of the theorems, there were written nonstrict inequalities, but they should have been strict inequalities. I have corrected this in the new version. If you have felt particularly challenged by these proofs, that’s okay! I hope that this is an opportunity for you not to memorize a method and execute it perfectly, but rather to be challenged and to struggle with real mathematical problems. I highly encourage you to come to office hours (virtually) to ask questions about these problems. And feel free to email me as well! This week’s handout is a rewriting of those same theorems, along with one more, the Extreme Value Theorem. I apologize for all the changes, but I - along with the rest of you - am still adjusting to this new setup. -
Foundations of Mathematics
Foundations of Mathematics Fall 2019 ii Contents 1 Propositional Logic 1 1.1 The basic definitions . .1 1.2 Disjunctive Normal Form Theorem . .3 1.3 Proofs . .4 1.4 The Soundness Theorem . 11 1.5 The Completeness Theorem . 12 1.6 Completeness, Consistency and Independence . 14 2 Predicate Logic 17 2.1 The Language of Predicate Logic . 17 2.2 Models and Interpretations . 19 2.3 The Deductive Calculus . 21 2.4 Soundness Theorem for Predicate Logic . 24 3 Models for Predicate Logic 27 3.1 Models . 27 3.2 The Completeness Theorem for Predicate Logic . 27 3.3 Consequences of the completeness theorem . 31 4 Computability Theory 33 4.1 Introduction and Examples . 33 4.2 Finite State Automata . 34 4.3 Exercises . 37 4.4 Turing Machines . 38 4.5 Recursive Functions . 43 4.6 Exercises . 48 iii iv CONTENTS Chapter 1 Propositional Logic 1.1 The basic definitions Propositional logic concerns relationships between sentences built up from primitive proposition symbols with logical connectives. The symbols of the language of predicate calculus are 1. Logical connectives: ,&, , , : _ ! $ 2. Punctuation symbols: ( , ) 3. Propositional variables: A0, A1, A2,.... A propositional variable is intended to represent a proposition which can either be true or false. Restricted versions, , of the language of propositional logic can be constructed by specifying a subset of the propositionalL variables. In this case, let PVar( ) denote the propositional variables of . L L Definition 1.1.1. The collection of sentences, denoted Sent( ), of a propositional language is defined by recursion. L L 1. The basis of the set of sentences is the set PVar( ) of propositional variables of . -
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 ............................................ -
CHAPTER 8 Hilbert Proof Systems, Formal Proofs, Deduction Theorem
CHAPTER 8 Hilbert Proof Systems, Formal Proofs, Deduction Theorem The Hilbert proof systems are systems based on a language with implication and contain a Modus Ponens rule as a rule of inference. They are usually called Hilbert style formalizations. We will call them here Hilbert style proof systems, or Hilbert systems, for short. Modus Ponens is probably the oldest of all known rules of inference as it was already known to the Stoics (3rd century B.C.). It is also considered as the most "natural" to our intuitive thinking and the proof systems containing it as the inference rule play a special role in logic. The Hilbert proof systems put major emphasis on logical axioms, keeping the rules of inference to minimum, often in propositional case, admitting only Modus Ponens, as the sole inference rule. 1 Hilbert System H1 Hilbert proof system H1 is a simple proof system based on a language with implication as the only connective, with two axioms (axiom schemas) which characterize the implication, and with Modus Ponens as a sole rule of inference. We de¯ne H1 as follows. H1 = ( Lf)g; F fA1;A2g MP ) (1) where A1;A2 are axioms of the system, MP is its rule of inference, called Modus Ponens, de¯ned as follows: A1 (A ) (B ) A)); A2 ((A ) (B ) C)) ) ((A ) B) ) (A ) C))); MP A ;(A ) B) (MP ) ; B 1 and A; B; C are any formulas of the propositional language Lf)g. Finding formal proofs in this system requires some ingenuity. Let's construct, as an example, the formal proof of such a simple formula as A ) A.