A Unified View of Induction Reasoning for First-Order Logic Sorin Stratulat
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Chapter 3 Induction and Recursion
Chapter 3 Induction and Recursion 3.1 Induction: An informal introduction This section is intended as a somewhat informal introduction to The Principle of Mathematical Induction (PMI): a theorem that establishes the validity of the proof method which goes by the same name. There is a particular format for writing the proofs which makes it clear that PMI is being used. We will not explicitly use this format when introducing the method, but will do so for the large number of different examples given later. Suppose you are given a large supply of L-shaped tiles as shown on the left of the figure below. The question you are asked to answer is whether these tiles can be used to exactly cover the squares of an 2n × 2n punctured grid { a 2n × 2n grid that has had one square cut out { say the 8 × 8 example shown in the right of the figure. 1 2 CHAPTER 3. INDUCTION AND RECURSION In order for this to be possible at all, the number of squares in the punctured grid has to be a multiple of three. It is. The number of squares is 2n2n − 1 = 22n − 1 = 4n − 1 ≡ 1n − 1 ≡ 0 (mod 3): But that does not mean we can tile the punctured grid. In order to get some traction on what to do, let's try some small examples. The tiling is easy to find if n = 1 because 2 × 2 punctured grid is exactly covered by one tile. Let's try n = 2, so that our punctured grid is 4 × 4. -
Mathematical Induction
Mathematical Induction Lecture 10-11 Menu • Mathematical Induction • Strong Induction • Recursive Definitions • Structural Induction Climbing an Infinite Ladder Suppose we have an infinite ladder: 1. We can reach the first rung of the ladder. 2. If we can reach a particular rung of the ladder, then we can reach the next rung. From (1), we can reach the first rung. Then by applying (2), we can reach the second rung. Applying (2) again, the third rung. And so on. We can apply (2) any number of times to reach any particular rung, no matter how high up. This example motivates proof by mathematical induction. Principle of Mathematical Induction Principle of Mathematical Induction: To prove that P(n) is true for all positive integers n, we complete these steps: Basis Step: Show that P(1) is true. Inductive Step: Show that P(k) → P(k + 1) is true for all positive integers k. To complete the inductive step, assuming the inductive hypothesis that P(k) holds for an arbitrary integer k, show that must P(k + 1) be true. Climbing an Infinite Ladder Example: Basis Step: By (1), we can reach rung 1. Inductive Step: Assume the inductive hypothesis that we can reach rung k. Then by (2), we can reach rung k + 1. Hence, P(k) → P(k + 1) is true for all positive integers k. We can reach every rung on the ladder. Logic and Mathematical Induction • Mathematical induction can be expressed as the rule of inference (P(1) ∧ ∀k (P(k) → P(k + 1))) → ∀n P(n), where the domain is the set of positive integers. -
Chapter 4 Induction and Recursion
Chapter 4 Induction and Recursion 4.1 Induction: An informal introduction This section is intended as a somewhat informal introduction to The Principle of Mathematical Induction (PMI): a theorem that establishes the validity of the proof method which goes by the same name. There is a particular format for writing the proofs which makes it clear that PMI is being used. We will not explicitly use this format when introducing the method, but will do so for the large number of different examples given later. Suppose you are given a large supply of L-shaped tiles as shown on the left of the figure below. The question you are asked to answer is whether these tiles can be used to exactly cover the squares of an 2n × 2n punctured grid { a 2n × 2n grid that has had one square cut out { say the 8 × 8 example shown in the right of the figure. 1 2 CHAPTER 4. INDUCTION AND RECURSION In order for this to be possible at all, the number of squares in the punctured grid has to be a multiple of three. By direct calculation we can see that it is true when n = 1; 2 or 3, and these are the cases we're interested in here. It turns out to be true in general; this is easy to show using congruences, which we will study later, and also can be shown using methods in this chapter. But that does not mean we can tile the punctured grid. In order to get some traction on what to do, let's try some small examples. -
Chapter 7. Induction and Recursion
Chapter 7. Induction and Recursion Part 1. Mathematical Induction The principle of mathematical induction is this: to establish an infinite sequence of propositions P1,P2,P3,...,Pn,... (or, simply put, Pn (n 1)), it is enough to verify the following two things ≥ (1) P1, and (2) Pk Pk ; (that is, assuming Pk vaild, we can rpove the validity of Pk ). ⇒ + 1 + 1 These two things will give a “domino effect” for the validity of all Pn (n 1). Indeed, ≥ step (1) tells us that P1 is true. Applying (2) to the case n = 1, we know that P2 is true. Knowing that P2 is true and applying (2) to the case n = 2 we know that P3 is true. Continue in this manner, we see that P4 is true, P5 is true, etc. This argument can go on and on. Now you should be convinced that Pn is true, no matter how big is n. We give some examples to show how this induction principle works. Example 1. Use mathematical induction to show 1 + 3 + 5 + + (2n 1) = n2. ··· − (Remember: in mathematics, “show” means “prove”.) Answer: For n = 1, the identity becomes 1 = 12, which is obviously true. Now assume the validity of the identity for n = k: 1 + 3 + 5 + + (2k 1) = k2. ··· − For n = k + 1, the left hand side of the identity is 1 + 3 + 5 + + (2k 1) + (2(k + 1) 1) = k2 + (2k + 1) = (k + 1)2 ··· − − which is the right hand side for n = k + 1. The proof is complete. 1 Example 2. Use mathematical induction to show the following formula for a geometric series: 1 xn+ 1 1 + x + x2 + + xn = − . -
A Survey of Engineering of Formally Verified Software
The version of record is available at: http://dx.doi.org/10.1561/2500000045 QED at Large: A Survey of Engineering of Formally Verified Software Talia Ringer Karl Palmskog University of Washington University of Texas at Austin [email protected] [email protected] Ilya Sergey Milos Gligoric Yale-NUS College University of Texas at Austin and [email protected] National University of Singapore [email protected] Zachary Tatlock University of Washington [email protected] arXiv:2003.06458v1 [cs.LO] 13 Mar 2020 Errata for the present version of this paper may be found online at https://proofengineering.org/qed_errata.html The version of record is available at: http://dx.doi.org/10.1561/2500000045 Contents 1 Introduction 103 1.1 Challenges at Scale . 104 1.2 Scope: Domain and Literature . 105 1.3 Overview . 106 1.4 Reading Guide . 106 2 Proof Engineering by Example 108 3 Why Proof Engineering Matters 111 3.1 Proof Engineering for Program Verification . 112 3.2 Proof Engineering for Other Domains . 117 3.3 Practical Impact . 124 4 Foundations and Trusted Bases 126 4.1 Proof Assistant Pre-History . 126 4.2 Proof Assistant Early History . 129 4.3 Proof Assistant Foundations . 130 4.4 Trusted Computing Bases of Proofs and Programs . 137 5 Between the Engineer and the Kernel: Languages and Automation 141 5.1 Styles of Automation . 142 5.2 Automation in Practice . 156 The version of record is available at: http://dx.doi.org/10.1561/2500000045 6 Proof Organization and Scalability 162 6.1 Property Specification and Encodings . -
3 Mathematical Induction
Hardegree, Metalogic, Mathematical Induction page 1 of 27 3 Mathematical Induction 1. Introduction.......................................................................................................................................2 2. Explicit Definitions ..........................................................................................................................2 3. Inductive Definitions ........................................................................................................................3 4. An Aside on Terminology.................................................................................................................3 5. Induction in Arithmetic .....................................................................................................................3 6. Inductive Proofs in Arithmetic..........................................................................................................4 7. Inductive Proofs in Meta-Logic ........................................................................................................5 8. Expanded Induction in Arithmetic.....................................................................................................7 9. Expanded Induction in Meta-Logic...................................................................................................8 10. How Induction Captures ‘Nothing Else’...........................................................................................9 11. Exercises For Chapter 3 .................................................................................................................11 -
Collection Principles in Dependent Type Theory
This is a repository copy of Collection Principles in Dependent Type Theory. White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/113157/ Version: Accepted Version Proceedings Paper: Azcel, P and Gambino, N orcid.org/0000-0002-4257-3590 (2002) Collection Principles in Dependent Type Theory. In: Lecture Notes in Computer Science: TYPES 2000. International Workshop on Types for Proofs and Programs (TYPES) 2000, 08-12 Dec 2000, Durham, UK. Springer Verlag , pp. 1-23. ISBN 3-540-43287-6 © 2002, Springer-Verlag Berlin Heidelberg. This is an author produced version of a conference paper published in Lecture Notes in Computer Science: Types for Proofs and Programs. Uploaded in accordance with the publisher's self-archiving policy. Reuse Items deposited in White Rose Research Online are protected by copyright, with all rights reserved unless indicated otherwise. They may be downloaded and/or printed for private study, or other acts as permitted by national copyright laws. The publisher or other rights holders may allow further reproduction and re-use of the full text version. This is indicated by the licence information on the White Rose Research Online record for the item. Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the reason for the withdrawal request. [email protected] https://eprints.whiterose.ac.uk/ Collection Principles in Dependent Type Theory⋆ Peter Aczel1 and Nicola Gambino2 1 Departments of Mathematics and Computer Science, University of Manchester, e-mail: [email protected] 2 Department of Computer Science, University of Manchester, e-mail: [email protected] Abstract. -
Proofs and Mathematical Reasoning
Proofs and Mathematical Reasoning University of Birmingham Author: Supervisors: Agata Stefanowicz Joe Kyle Michael Grove September 2014 c University of Birmingham 2014 Contents 1 Introduction 6 2 Mathematical language and symbols 6 2.1 Mathematics is a language . .6 2.2 Greek alphabet . .6 2.3 Symbols . .6 2.4 Words in mathematics . .7 3 What is a proof? 9 3.1 Writer versus reader . .9 3.2 Methods of proofs . .9 3.3 Implications and if and only if statements . 10 4 Direct proof 11 4.1 Description of method . 11 4.2 Hard parts? . 11 4.3 Examples . 11 4.4 Fallacious \proofs" . 15 4.5 Counterexamples . 16 5 Proof by cases 17 5.1 Method . 17 5.2 Hard parts? . 17 5.3 Examples of proof by cases . 17 6 Mathematical Induction 19 6.1 Method . 19 6.2 Versions of induction. 19 6.3 Hard parts? . 20 6.4 Examples of mathematical induction . 20 7 Contradiction 26 7.1 Method . 26 7.2 Hard parts? . 26 7.3 Examples of proof by contradiction . 26 8 Contrapositive 29 8.1 Method . 29 8.2 Hard parts? . 29 8.3 Examples . 29 9 Tips 31 9.1 What common mistakes do students make when trying to present the proofs? . 31 9.2 What are the reasons for mistakes? . 32 9.3 Advice to students for writing good proofs . 32 9.4 Friendly reminder . 32 c University of Birmingham 2014 10 Sets 34 10.1 Basics . 34 10.2 Subsets and power sets . 34 10.3 Cardinality and equality . -
MATHEMATICAL INDUCTION SEQUENCES and SERIES
MISS MATHEMATICAL INDUCTION SEQUENCES and SERIES John J O'Connor 2009/10 Contents This booklet contains eleven lectures on the topics: Mathematical Induction 2 Sequences 9 Series 13 Power Series 22 Taylor Series 24 Summary 29 Mathematician's pictures 30 Exercises on these topics are on the following pages: Mathematical Induction 8 Sequences 13 Series 21 Power Series 24 Taylor Series 28 Solutions to the exercises in this booklet are available at the Web-site: www-history.mcs.st-andrews.ac.uk/~john/MISS_solns/ 1 Mathematical induction This is a method of "pulling oneself up by one's bootstraps" and is regarded with suspicion by non-mathematicians. Example Suppose we want to sum an Arithmetic Progression: 1+ 2 + 3 +...+ n = 1 n(n +1). 2 Engineers' induction € Check it for (say) the first few values and then for one larger value — if it works for those it's bound to be OK. Mathematicians are scornful of an argument like this — though notice that if it fails for some value there is no point in going any further. Doing it more carefully: We define a sequence of "propositions" P(1), P(2), ... where P(n) is "1+ 2 + 3 +...+ n = 1 n(n +1)" 2 First we'll prove P(1); this is called "anchoring the induction". Then we will prove that if P(k) is true for some value of k, then so is P(k + 1) ; this is€ c alled "the inductive step". Proof of the method If P(1) is OK, then we can use this to deduce that P(2) is true and then use this to show that P(3) is true and so on. -
Logicism, Interpretability, and Knowledge of Arithmetic
ZU064-05-FPR RSL-logicism-final 1 December 2013 21:42 The Review of Symbolic Logic Volume 0, Number 0, Month 2013 Logicism, Interpretability, and Knowledge of Arithmetic Sean Walsh Department of Logic and Philosophy of Science, University of California, Irvine Abstract. A crucial part of the contemporary interest in logicism in the philosophy of mathematics resides in its idea that arithmetical knowledge may be based on logical knowledge. Here an implementation of this idea is considered that holds that knowledge of arithmetical principles may be based on two things: (i) knowledge of logical principles and (ii) knowledge that the arithmetical principles are representable in the logical principles. The notions of representation considered here are related to theory-based and structure- based notions of representation from contemporary mathematical logic. It is argued that the theory-based versions of such logicism are either too liberal (the plethora problem) or are committed to intuitively incorrect closure conditions (the consistency problem). Structure-based versions must on the other hand respond to a charge of begging the question (the circularity problem) or explain how one may have a knowledge of structure in advance of a knowledge of axioms (the signature problem). This discussion is significant because it gives us a better idea of what a notion of representation must look like if it is to aid in realizing some of the traditional epistemic aims of logicism in the philosophy of mathematics. Received February 2013 Acknowledgements: This is material coming out of my dissertation, and I would thus like to thank my advisors, Dr. Michael Detlefsen and Dr. -
Why Proofs by Mathematical Induction Are Generally Not Explanatory MARC LANGE
Why proofs by mathematical induction are generally not explanatory MARC LANGE Philosophers who regard some mathematical proofs as explaining why the- orems hold, and others as merely proving that they do hold, disagree sharply about the explanatory value of proofs by mathematical induction. I offer an argument that aims to resolve this conflict of intuitions without making any controversial presuppositions about what mathematical explanations would be. 1. The problem Proposed accounts of scientific explanation have long been tested against certain canonical examples. Various arguments are paradigmatically expla- natory, such as Newton’s explanations of Kepler’s laws and the tides, Darwin’s explanations of various biogeographical and anatomical facts, Wegener’s explanation of the correspondence between the South American and African coastlines, and Einstein’s explanation of the equality of inertial and gravitational mass. Any promising comprehensive theory of scientific explanation must deem these arguments to be genuinely explanatory. By the same token, there is widespread agreement that various other arguments are not explanatory – examples so standard that I need only give their famil- iar monikers: the flagpole, the eclipse, the barometer, the hexed salt and so forth. Although there are some controversial cases, of course (such as ‘expla- nations’ of the dormitive-virtue variety), philosophers who defend rival accounts of scientific explanation nevertheless agree to a large extent on the phenomena that they are trying to save. Alas, the same cannot be said when it comes to mathematical explanation. Philosophers disagree sharply about which proofs of a given theorem explain why that theorem holds and which merely prove that it holds.1 This kind of disagreement makes it difficult to test proposed accounts of mathematical explanation without making controversial presuppositions about the phe- nomena to be saved. -
Proofs by Induction Maths Delivers! Proofs by Induction
1 Maths delivers! 2 3 4 5 6 12 11 7 10 8 9 A guide for teachers – Years 11 and 12 Proofs by induction Maths delivers! Proofs by induction Professor Brian A. Davey, La Trobe University Editor: Dr Jane Pitkethly, La Trobe University Illustrations and web design: Catherine Tan, Michael Shaw For teachers of Secondary Mathematics These notes are based in part on lecture notes and printed notes prepared by the author for use in teaching mathematical induction to first-year students at Latrobe University. © The University of Melbourne on behalf of the Australian Mathematical Sciences Institute (AMSI), 2013 (except where otherwise indicated). This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. 2011. http://creativecommons.org/licenses/by-nc-nd/3.0/ Australian Mathematical Sciences Institute Building 161 The University of Melbourne VIC 3010 Email: [email protected] Website: www.amsi.org.au The principle of mathematical induction ........................ 4 A typical proof by induction ................................ 6 Two non-proofs by induction ................................ 7 Modified or strong induction ................................ 9 The Tower of Hanoi puzzle ................................. 10 A two-colour theorem .................................... 14 If you can’t prove it, prove something harder! ..................... 17 Answers to exercises ..................................... 20 maths delivers! Proofs by induction The principle of mathematical induction The idea of induction: falling dominoes There are two steps involved in knocking over a row of dominoes. Step 1. You have to knock over the first domino. Step 2. You have to be sure that when domino k falls, it knocks over domino k 1. Å These are the same as the steps in a proof by induction.