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Chapter 2 Introduction to Classical Propositional
CHAPTER 2 INTRODUCTION TO CLASSICAL PROPOSITIONAL LOGIC 1 Motivation and History The origins of the classical propositional logic, classical propositional calculus, as it was, and still often is called, go back to antiquity and are due to Stoic school of philosophy (3rd century B.C.), whose most eminent representative was Chryssipus. But the real development of this calculus began only in the mid-19th century and was initiated by the research done by the English math- ematician G. Boole, who is sometimes regarded as the founder of mathematical logic. The classical propositional calculus was ¯rst formulated as a formal ax- iomatic system by the eminent German logician G. Frege in 1879. The assumption underlying the formalization of classical propositional calculus are the following. Logical sentences We deal only with sentences that can always be evaluated as true or false. Such sentences are called logical sentences or proposi- tions. Hence the name propositional logic. A statement: 2 + 2 = 4 is a proposition as we assume that it is a well known and agreed upon truth. A statement: 2 + 2 = 5 is also a proposition (false. A statement:] I am pretty is modeled, if needed as a logical sentence (proposi- tion). We assume that it is false, or true. A statement: 2 + n = 5 is not a proposition; it might be true for some n, for example n=3, false for other n, for example n= 2, and moreover, we don't know what n is. Sentences of this kind are called propositional functions. We model propositional functions within propositional logic by treating propositional functions as propositions. -
CS311H: Discrete Mathematics Recursive Definitions Recursive
Recursive Definitions CS311H: Discrete Mathematics I Should be familiar with recursive functions from programming: Recursive Definitions public int fact(int n) { if(n <= 1) return 1; return n * fact(n - 1); Instructor: I¸sıl Dillig } I Recursive definitions are also used in math for defining sets, functions, sequences etc. Instructor: I¸sıl Dillig, CS311H: Discrete Mathematics Recursive Definitions 1/18 Instructor: I¸sıl Dillig, CS311H: Discrete Mathematics Recursive Definitions 2/18 Recursive Definitions in Math Recursively Defined Functions I Consider the following sequence: I Just like sequences, functions can also be defined recursively 1, 3, 9, 27, 81,... I Example: I This sequence can be defined recursively as follows: f (0) = 3 f (n + 1) = 2f (n) + 3 (n 1) a0 = 1 ≥ an = 3 an 1 · − I What is f (1)? I First part called base case; second part called recursive step I What is f (2)? I Very similar to induction; in fact, recursive definitions I What is f (3)? sometimes also called inductive definitions Instructor: I¸sıl Dillig, CS311H: Discrete Mathematics Recursive Definitions 3/18 Instructor: I¸sıl Dillig, CS311H: Discrete Mathematics Recursive Definitions 4/18 Recursive Definition Examples Recursive Definitions of Important Functions I Some important functions/sequences defined recursively I Consider f (n) = 2n + 1 where n is non-negative integer I Factorial function: I What’s a recursive definition for f ? f (1) = 1 f (n) = n f (n 1) (n 2) · − ≥ I Consider the sequence 1, 4, 9, 16,... I Fibonacci numbers: 1, 1, 2, 3, 5, 8, 13, 21,... I What is a recursive -
Aristotle's Assertoric Syllogistic and Modern Relevance Logic*
Aristotle’s assertoric syllogistic and modern relevance logic* Abstract: This paper sets out to evaluate the claim that Aristotle’s Assertoric Syllogistic is a relevance logic or shows significant similarities with it. I prepare the grounds for a meaningful comparison by extracting the notion of relevance employed in the most influential work on modern relevance logic, Anderson and Belnap’s Entailment. This notion is characterized by two conditions imposed on the concept of validity: first, that some meaning content is shared between the premises and the conclusion, and second, that the premises of a proof are actually used to derive the conclusion. Turning to Aristotle’s Prior Analytics, I argue that there is evidence that Aristotle’s Assertoric Syllogistic satisfies both conditions. Moreover, Aristotle at one point explicitly addresses the potential harmfulness of syllogisms with unused premises. Here, I argue that Aristotle’s analysis allows for a rejection of such syllogisms on formal grounds established in the foregoing parts of the Prior Analytics. In a final section I consider the view that Aristotle distinguished between validity on the one hand and syllogistic validity on the other. Following this line of reasoning, Aristotle’s logic might not be a relevance logic, since relevance is part of syllogistic validity and not, as modern relevance logic demands, of general validity. I argue that the reasons to reject this view are more compelling than the reasons to accept it and that we can, cautiously, uphold the result that Aristotle’s logic is a relevance logic. Keywords: Aristotle, Syllogism, Relevance Logic, History of Logic, Logic, Relevance 1. -
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. -
Recursive Definitions and Structural Induction 1 Recursive Definitions
Massachusetts Institute of Technology Course Notes 6 6.042J/18.062J, Fall ’02: Mathematics for Computer Science Professor Albert Meyer and Dr. Radhika Nagpal Recursive Definitions and Structural Induction 1 Recursive Definitions Recursive definitions say how to build something from a simpler version of the same thing. They have two parts: • Base case(s) that don’t depend on anything else. • Combination case(s) that depend on simpler cases. Here are some examples of recursive definitions: Example 1.1. Define a set, E, recursively as follows: 1. 0 E, 2 2. if n E, then n + 2 E, 2 2 3. if n E, then n E. 2 − 2 Using this definition, we can see that since 0 E by 1., it follows from 2. that 0 + 2 = 2 E, and 2 2 so 2 + 2 = 4 E, 4 + 2 = 6 E, : : : , and in fact any nonegative even number is in E. Also, by 3., 2 2 2; 4; 6; E. − − − · · · 2 Is anything else in E? The definition doesn’t say so explicitly, but an implicit condition on a recursive definition is that the only way things get into E is as a consequence of 1., 2., and 3. So clearly E is exactly the set of even integers. Example 1.2. Define a set, S, of strings of a’s and b’s recursively as follows: 1. λ S, where λ is the empty string, 2 2. if x S, then axb S, 2 2 3. if x S, then bxa S, 2 2 4. if x; y S, then xy S. -
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. -
John P. Burgess Department of Philosophy Princeton University Princeton, NJ 08544-1006, USA [email protected]
John P. Burgess Department of Philosophy Princeton University Princeton, NJ 08544-1006, USA [email protected] LOGIC & PHILOSOPHICAL METHODOLOGY Introduction For present purposes “logic” will be understood to mean the subject whose development is described in Kneale & Kneale [1961] and of which a concise history is given in Scholz [1961]. As the terminological discussion at the beginning of the latter reference makes clear, this subject has at different times been known by different names, “analytics” and “organon” and “dialectic”, while inversely the name “logic” has at different times been applied much more broadly and loosely than it will be here. At certain times and in certain places — perhaps especially in Germany from the days of Kant through the days of Hegel — the label has come to be used so very broadly and loosely as to threaten to take in nearly the whole of metaphysics and epistemology. Logic in our sense has often been distinguished from “logic” in other, sometimes unmanageably broad and loose, senses by adding the adjectives “formal” or “deductive”. The scope of the art and science of logic, once one gets beyond elementary logic of the kind covered in introductory textbooks, is indicated by two other standard references, the Handbooks of mathematical and philosophical logic, Barwise [1977] and Gabbay & Guenthner [1983-89], though the latter includes also parts that are identified as applications of logic rather than logic proper. The term “philosophical logic” as currently used, for instance, in the Journal of Philosophical Logic, is a near-synonym for “nonclassical logic”. There is an older use of the term as a near-synonym for “philosophy of language”. -
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. -
A Quasi-Classical Logic for Classical Mathematics
Theses Honors College 11-2014 A Quasi-Classical Logic for Classical Mathematics Henry Nikogosyan University of Nevada, Las Vegas Follow this and additional works at: https://digitalscholarship.unlv.edu/honors_theses Part of the Logic and Foundations Commons Repository Citation Nikogosyan, Henry, "A Quasi-Classical Logic for Classical Mathematics" (2014). Theses. 21. https://digitalscholarship.unlv.edu/honors_theses/21 This Honors Thesis is protected by copyright and/or related rights. It has been brought to you by Digital Scholarship@UNLV with permission from the rights-holder(s). You are free to use this Honors Thesis in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/or on the work itself. This Honors Thesis has been accepted for inclusion in Theses by an authorized administrator of Digital Scholarship@UNLV. For more information, please contact [email protected]. A QUASI-CLASSICAL LOGIC FOR CLASSICAL MATHEMATICS By Henry Nikogosyan Honors Thesis submitted in partial fulfillment for the designation of Departmental Honors Department of Philosophy Ian Dove James Woodbridge Marta Meana College of Liberal Arts University of Nevada, Las Vegas November, 2014 ABSTRACT Classical mathematics is a form of mathematics that has a large range of application; however, its application has boundaries. In this paper, I show that Sperber and Wilson’s concept of relevance can demarcate classical mathematics’ range of applicability by demarcating classical logic’s range of applicability. -
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. -
The Development of Mathematical Logic from Russell to Tarski: 1900–1935
The Development of Mathematical Logic from Russell to Tarski: 1900–1935 Paolo Mancosu Richard Zach Calixto Badesa The Development of Mathematical Logic from Russell to Tarski: 1900–1935 Paolo Mancosu (University of California, Berkeley) Richard Zach (University of Calgary) Calixto Badesa (Universitat de Barcelona) Final Draft—May 2004 To appear in: Leila Haaparanta, ed., The Development of Modern Logic. New York and Oxford: Oxford University Press, 2004 Contents Contents i Introduction 1 1 Itinerary I: Metatheoretical Properties of Axiomatic Systems 3 1.1 Introduction . 3 1.2 Peano’s school on the logical structure of theories . 4 1.3 Hilbert on axiomatization . 8 1.4 Completeness and categoricity in the work of Veblen and Huntington . 10 1.5 Truth in a structure . 12 2 Itinerary II: Bertrand Russell’s Mathematical Logic 15 2.1 From the Paris congress to the Principles of Mathematics 1900–1903 . 15 2.2 Russell and Poincar´e on predicativity . 19 2.3 On Denoting . 21 2.4 Russell’s ramified type theory . 22 2.5 The logic of Principia ......................... 25 2.6 Further developments . 26 3 Itinerary III: Zermelo’s Axiomatization of Set Theory and Re- lated Foundational Issues 29 3.1 The debate on the axiom of choice . 29 3.2 Zermelo’s axiomatization of set theory . 32 3.3 The discussion on the notion of “definit” . 35 3.4 Metatheoretical studies of Zermelo’s axiomatization . 38 4 Itinerary IV: The Theory of Relatives and Lowenheim’s¨ Theorem 41 4.1 Theory of relatives and model theory . 41 4.2 The logic of relatives . -
Introduction to Formal Logic II (3 Credit
PHILOSOPHY 115 INTRODUCTION TO FORMAL LOGIC II BULLETIN INFORMATION PHIL 115 – Introduction to Formal Logic II (3 credit hrs) Course Description: Intermediate topics in predicate logic, including second-order predicate logic; meta-theory, including soundness and completeness; introduction to non-classical logic. SAMPLE COURSE OVERVIEW Building on the material from PHIL 114, this course introduces new topics in logic and applies them to both propositional and first-order predicate logic. These topics include argument by induction, duality, compactness, and others. We will carefully prove important meta-logical results, including soundness and completeness for both propositional logic and first-order predicate logic. We will also learn a new system of proof, the Gentzen-calculus, and explore first-order predicate logic with functions and identity. Finally, we will discuss potential motivations for alternatives to classical logic, and examine how those motivations lead to the development of intuitionistic logic, including a formal system for intuitionistic logic, comparing the features of that formal system to those of classical first-order predicate logic. ITEMIZED LEARNING OUTCOMES Upon successful completion of PHIL 115, students will be able to: 1. Apply, as appropriate, principles of analytical reasoning, using as a foundation the knowledge of mathematical, logical, and algorithmic principles 2. Recognize and use connections among mathematical, logical, and algorithmic methods across disciplines 3. Identify and describe problems using formal symbolic methods and assess the appropriateness of these methods for the available data 4. Effectively communicate the results of such analytical reasoning and problem solving 5. Explain and apply important concepts from first-order logic, including duality, compactness, soundness, and completeness 6.