Chapter 2 of "Modern Logic"
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1 Elementary Set Theory
1 Elementary Set Theory Notation: fg enclose a set. f1; 2; 3g = f3; 2; 2; 1; 3g because a set is not defined by order or multiplicity. f0; 2; 4;:::g = fxjx is an even natural numberg because two ways of writing a set are equivalent. ; is the empty set. x 2 A denotes x is an element of A. N = f0; 1; 2;:::g are the natural numbers. Z = f:::; −2; −1; 0; 1; 2;:::g are the integers. m Q = f n jm; n 2 Z and n 6= 0g are the rational numbers. R are the real numbers. Axiom 1.1. Axiom of Extensionality Let A; B be sets. If (8x)x 2 A iff x 2 B then A = B. Definition 1.1 (Subset). Let A; B be sets. Then A is a subset of B, written A ⊆ B iff (8x) if x 2 A then x 2 B. Theorem 1.1. If A ⊆ B and B ⊆ A then A = B. Proof. Let x be arbitrary. Because A ⊆ B if x 2 A then x 2 B Because B ⊆ A if x 2 B then x 2 A Hence, x 2 A iff x 2 B, thus A = B. Definition 1.2 (Union). Let A; B be sets. The Union A [ B of A and B is defined by x 2 A [ B if x 2 A or x 2 B. Theorem 1.2. A [ (B [ C) = (A [ B) [ C Proof. Let x be arbitrary. x 2 A [ (B [ C) iff x 2 A or x 2 B [ C iff x 2 A or (x 2 B or x 2 C) iff x 2 A or x 2 B or x 2 C iff (x 2 A or x 2 B) or x 2 C iff x 2 A [ B or x 2 C iff x 2 (A [ B) [ C Definition 1.3 (Intersection). -
Logic: Representation and Automated Reasoning
Logic Knowledge Representation & Reasoning Mechanisms Logic ● Logic as KR ■ Propositional Logic ■ Predicate Logic (predicate Calculus) ● Automated Reasoning ■ Logical inferences ■ Resolution and Theorem-proving Logic ● Logic as KR ■ Propositional Logic ■ Predicate Logic (predicate Calculus) ● Automated Reasoning ■ Logical inferences ■ Resolution and Theorem-proving Propositional Logic ● Symbols: ■ truth symbols: true, false ■ propositions: a statement that is “true” or “false” but not both E.g., P = “Two plus two equals four” Q = “It rained yesterday.” ■ connectives: ~, →, ∧, ∨, ≡ • Sentences - propositions or truth symbols • Well formed formulas (expressions) - sentences that are legally well-formed with connectives E.g., P ∧ R → and P ~ are not wff but P ∧ R → ~ Q is Examples P Q AI is hard but it is interesting P ∧ Q AI is neither hard nor interesting ~P ∧ ~ Q P Q If you don’t do assignments then you will fail P → Q ≡ Do assignments or fail (Prove by truth table) ~ P ∨ Q None or both of P and Q is true (~ P ∧ ~ Q) ∨ (P ∧ Q) ≡ T Exactly one of P and Q is true (~ P ∧ Q) ∨ (P ∧ ~ Q) ≡ T Predicate Logic ● Symbols: • truth symbols • constants: represents objects in the world • variables: represents ranging objects } Terms • functions: represent properties • Predicates: functions of terms with true/false values e.g., bill_residence_city (vancouver) or lives (bill, vancouver) ● Atomic sentences: true, false, or predicates ● Quantifiers: ∀, ∃ ● Sentences (expressions): sequences of legal applications of connectives and quantifiers to atomic -
First-Order Logic
First-Order Logic Chapter 8 1 Outline • Why FOL? • Syntax and semantics of FOL • Using FOL • Wumpus world in FOL • Knowledge engineering in FOL 2 Pros and cons of propositional logic ☺ Propositional logic is declarative ☺ Propositional logic allows partial/disjunctive/negated information – (unlike most data structures and databases) ☺ Propositional logic is compositional: – meaning of B1,1 ∧ P1,2 is derived from meaning of B1,1 and of P1,2 ☺ Meaning in propositional logic is context-independent – (unlike natural language, where meaning depends on context) Propositional logic has very limited expressive power – (unlike natural language) – E.g., cannot say "pits cause breezes in adjacent squares“ • except by writing one sentence for each square 3 First-order logic • Whereas propositional logic assumes the world contains facts, • first-order logic (like natural language) assumes the world contains – Objects: people, houses, numbers, colors, baseball games, wars, … – Relations: red, round, prime, brother of, bigger than, part of, comes between, … – Functions: father of, best friend, one more than, plus, … 4 Syntax of FOL: Basic elements • Constants KingJohn, 2, NUS,... • Predicates Brother, >,... • Functions Sqrt, LeftLegOf,... • Variables x, y, a, b,... • Connectives ¬, ⇒, ∧, ∨, ⇔ • Equality = • Quantifiers ∀, ∃ 5 Atomic sentences Atomic sentence = predicate (term1 ,...,termn) or term = term 1 2 Term = function (term1,..., termn) or constant or variable • E.g., Brother(KingJohn,RichardTheLionheart) > (Length(LeftLegOf(Richard)), Length(LeftLegOf(KingJohn))) -
Atomic Sentences
Symbolic Logic Study Guide: Class Notes 5 1.2. Notes for Chapter 2: Atomic Sentences 1.2.1. The Basic Structure of Atomic Sentences (2.1, 2.2, 2.3, and 2.5 of the Text) 1. Comparison between simple English sentences and atomic sentences Simple English Sentences Atomic sentences (FOL) (subject-predicate sentences) John is a freshman Freshman (John) John swims. Swim (John) John loves Jenny. Love (John, Jenny) John prefers Jenny to Amy. Prefer (John, Jenny, Amy) John’s mother loves Jenny. Love (mother (John), Jenny) The father of Jenny is angry. Angry (father (Jenny)) John is the brother of Jenny. John = brother (Jenny) [relational identity] 2. Names Definition: Names are individual constants that refer to some fixed individual objects or other. (1) The rule of naming (p. 10) • No empty name. • No multiple references (do not use one name to refer to different objects). • Multiple names: you can name one object by different names. (2) General terms / names: using a predicate, instead of a constant, to represent a general term. For example, John is a student Student (John) [correct] John = student [wrong!!!] 3. Predicates Definition: Predicates are symbols used to denote some property of objects or some relationship between objects. (1) Arity of predicates • Unary predicates--property • Binary predicates Relations • Ternary predicates (2) The predicates used in Tarski’s World: see p. 11. (3) Two rules of predicates: see p.12. 6 Symbolic Logic Study Guide: Class Notes 4. Functions Definition: A function is an individual constant determined by another constant. (1) Comparison with names: • Both refer to some fixed individual objects. -
1 Winnowing Wittgenstein: What's Worth Salvaging from the Wreck Of
Winnowing Wittgenstein: What’s Worth Salvaging from the Wreck of the Tractatus Peter Simons Trinity College Dublin Abstract Wittgenstein’s Tractatus still harbours valuable lessons for contemporary philosophy, but which ones? Wittgenstein’s long list of things we cannot speak about is set aside, but his insistence that the logical constants do not represent is retained, as is the absolute distinction between names and sentences. We preserve his atomism of elementary sentences but discard the atomism of simple objects in states of affairs. The fundamental harmony between language and the world is rejected: it is the source of much that is wrong in the Tractatus. What remains is a clarified role for items in making elementary sentences true. 1 Introduction Kevin Mulligan has maintained throughout his philosophical career a keen and judicious appreciation of the chief figures of that great philosophical explosion centred on Austria in the 19th and early 20th century. Of these figures, the best-known and most widely influential is Ludwig Wittgenstein.1 Kevin has maintained, quite rightly, that it is impossible to appreciate the extent to which Wittgenstein’s contributions to philosophy are as original as his many admirers contend without a great deal more knowledge of the Central European milieu from which Wittgenstein emerged than the majority of these admirers care to or are prepared to investigate. In this respect the more diffuse and ample later philosophy presents a much greater challenge than the early work which culminated in the Logisch-philosophische Abhandlung.2 The modest extent of the Tractatus and its more limited period of genesis, as well as its relatively crisper form and content, render it a more manageable and ultimately less controversial work than the post-Tractarian writings, whose thrust is even today occasionally obscure, despite more than a half century of frenzied exegesis. -
Chapter 1. Sentential Logic
CHAPTER 1. SENTENTIAL LOGIC 1. Introduction In sentential logic we study how given sentences may be combined to form more complicated compound sentences. For example, from the sentences 7 is prime, 7 is odd, 2 is prime, 2 is odd, we can obtain the following sentences: • 7 is prime and 7 is odd • 7 is odd and 2 is odd • 7 is odd or 2 is odd • 7 is not odd • If 2 is odd then 2 is prime Of course, this process can be iterated as often as we want, obtaining also: • If 7 is not odd then 2 is odd • If 7 is odd and 2 is odd then 2 is not prime • (7 is odd and 2 is odd) or 2 is prime We have improved on English in the last example by using parentheses to resolve an ambiguity. And, or, not, if . then (or implies) are called (sentential) connectives. Using them we can define more connectives, for example 2 is prime iff 2 is odd can be defined as (If 2 is prime then 2 is odd) and (if 2 is odd then 2 is prime). The truth value of any compound sentence is determined completely by the truth values of its component parts. For example, assuming 2, 7, odd, prime all have their usual meanings then 7 is odd and 2 is odd is false but (7 is odd and 2 is odd) or 2 is prime is true. We will discuss implication later. In the formal system of sentential logic we study in this Chapter, we do not use English sentences, but build the compound sentences from an infinite collection of symbols which we think of as referring to sentences — since these are not built up from other sentences we refer to them as atomic sentences. -
Logic, Proofs
CHAPTER 1 Logic, Proofs 1.1. Propositions A proposition is a declarative sentence that is either true or false (but not both). For instance, the following are propositions: “Paris is in France” (true), “London is in Denmark” (false), “2 < 4” (true), “4 = 7 (false)”. However the following are not propositions: “what is your name?” (this is a question), “do your homework” (this is a command), “this sentence is false” (neither true nor false), “x is an even number” (it depends on what x represents), “Socrates” (it is not even a sentence). The truth or falsehood of a proposition is called its truth value. 1.1.1. Connectives, Truth Tables. Connectives are used for making compound propositions. The main ones are the following (p and q represent given propositions): Name Represented Meaning Negation p “not p” Conjunction p¬ q “p and q” Disjunction p ∧ q “p or q (or both)” Exclusive Or p ∨ q “either p or q, but not both” Implication p ⊕ q “if p then q” Biconditional p → q “p if and only if q” ↔ The truth value of a compound proposition depends only on the value of its components. Writing F for “false” and T for “true”, we can summarize the meaning of the connectives in the following way: 6 1.1. PROPOSITIONS 7 p q p p q p q p q p q p q T T ¬F T∧ T∨ ⊕F →T ↔T T F F F T T F F F T T F T T T F F F T F F F T T Note that represents a non-exclusive or, i.e., p q is true when any of p, q is true∨ and also when both are true. -
Logic, Sets, and Proofs David A
Logic, Sets, and Proofs David A. Cox and Catherine C. McGeoch Amherst College 1 Logic Logical Statements. A logical statement is a mathematical statement that is either true or false. Here we denote logical statements with capital letters A; B. Logical statements be combined to form new logical statements as follows: Name Notation Conjunction A and B Disjunction A or B Negation not A :A Implication A implies B if A, then B A ) B Equivalence A if and only if B A , B Here are some examples of conjunction, disjunction and negation: x > 1 and x < 3: This is true when x is in the open interval (1; 3). x > 1 or x < 3: This is true for all real numbers x. :(x > 1): This is the same as x ≤ 1. Here are two logical statements that are true: x > 4 ) x > 2. x2 = 1 , (x = 1 or x = −1). Note that \x = 1 or x = −1" is usually written x = ±1. Converses, Contrapositives, and Tautologies. We begin with converses and contrapositives: • The converse of \A implies B" is \B implies A". • The contrapositive of \A implies B" is \:B implies :A" Thus the statement \x > 4 ) x > 2" has: • Converse: x > 2 ) x > 4. • Contrapositive: x ≤ 2 ) x ≤ 4. 1 Some logical statements are guaranteed to always be true. These are tautologies. Here are two tautologies that involve converses and contrapositives: • (A if and only if B) , ((A implies B) and (B implies A)). In other words, A and B are equivalent exactly when both A ) B and its converse are true. -
Lecture 1: Propositional Logic
Lecture 1: Propositional Logic Syntax Semantics Truth tables Implications and Equivalences Valid and Invalid arguments Normal forms Davis-Putnam Algorithm 1 Atomic propositions and logical connectives An atomic proposition is a statement or assertion that must be true or false. Examples of atomic propositions are: “5 is a prime” and “program terminates”. Propositional formulas are constructed from atomic propositions by using logical connectives. Connectives false true not and or conditional (implies) biconditional (equivalent) A typical propositional formula is The truth value of a propositional formula can be calculated from the truth values of the atomic propositions it contains. 2 Well-formed propositional formulas The well-formed formulas of propositional logic are obtained by using the construction rules below: An atomic proposition is a well-formed formula. If is a well-formed formula, then so is . If and are well-formed formulas, then so are , , , and . If is a well-formed formula, then so is . Alternatively, can use Backus-Naur Form (BNF) : formula ::= Atomic Proposition formula formula formula formula formula formula formula formula formula formula 3 Truth functions The truth of a propositional formula is a function of the truth values of the atomic propositions it contains. A truth assignment is a mapping that associates a truth value with each of the atomic propositions . Let be a truth assignment for . If we identify with false and with true, we can easily determine the truth value of under . The other logical connectives can be handled in a similar manner. Truth functions are sometimes called Boolean functions. 4 Truth tables for basic logical connectives A truth table shows whether a propositional formula is true or false for each possible truth assignment. -
Symbolic Logic: Grammar, Semantics, Syntax
Symbolic Logic: Grammar, Semantics, Syntax Logic aims to give a precise method or recipe for determining what follows from a given set of sentences. So we need precise definitions of `sentence' and `follows from.' 1. Grammar: What's a sentence? What are the rules that determine whether a string of symbols is a sentence, and when it is not? These rules are known as the grammar of a particular language. We have actually been operating with two different but very closely related grammars this term: a grammar for propositional logic and a grammar for first-order logic. The grammar for propositional logic (thus far) is simple: 1. There are an indefinite number of propositional variables, which we have been symbolizing as A; B; ::: and P; Q; :::; each of these is a sen- tence. ? is also a sentence. 2. If A; B are sentences, then: •:A is a sentence, • A ^ B is a sentence, and • A _ B is a sentence. 3. Nothing else is a sentence: anything that is neither a member of 1, nor constructable via successive applications of 2 to the members of 1, is not a sentence. The grammar for first-order logic (thus far) is more complex. 2 and 3 remain exactly the same as above, but 1 must be replaced by some- thing more complex. First, a list of all predicates (e.g. Tet or SameShape) and proper names (e.g. max; b) of a particular language L must be specified. Then we can define: 1F OL. A series of symbols s is an atomic sentence = s is an n-place predicate followed by an ordered sequence of n proper names. -
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 . -
On Operator N and Wittgenstein's Logical Philosophy
JOURNAL FOR THE HISTORY OF ANALYTICAL PHILOSOPHY ON OPERATOR N AND WITTGENSTEIN’S LOGICAL VOLUME 5, NUMBER 4 PHILOSOPHY EDITOR IN CHIEF JAMES R. CONNELLY KEVIN C. KLEMENt, UnIVERSITY OF MASSACHUSETTS EDITORIAL BOARD In this paper, I provide a new reading of Wittgenstein’s N oper- ANNALISA COLIVA, UnIVERSITY OF MODENA AND UC IRVINE ator, and of its significance within his early logical philosophy. GaRY EBBS, INDIANA UnIVERSITY BLOOMINGTON I thereby aim to resolve a longstanding scholarly controversy GrEG FROSt-ARNOLD, HOBART AND WILLIAM SMITH COLLEGES concerning the expressive completeness of N. Within the debate HENRY JACKMAN, YORK UnIVERSITY between Fogelin and Geach in particular, an apparent dilemma SANDRA LaPOINte, MCMASTER UnIVERSITY emerged to the effect that we must either concede Fogelin’s claim CONSUELO PRETI, THE COLLEGE OF NEW JERSEY that N is expressively incomplete, or reject certain fundamental MARCUS ROSSBERG, UnIVERSITY OF CONNECTICUT tenets within Wittgenstein’s logical philosophy. Despite their ANTHONY SKELTON, WESTERN UnIVERSITY various points of disagreement, however, Fogelin and Geach MARK TEXTOR, KING’S COLLEGE LonDON nevertheless share several common and problematic assump- AUDREY YAP, UnIVERSITY OF VICTORIA tions regarding Wittgenstein’s logical philosophy, and it is these RICHARD ZACH, UnIVERSITY OF CALGARY mistaken assumptions which are the source of the dilemma. Once we recognize and correct these, and other, associated ex- REVIEW EDITORS pository errors, it will become clear how to reconcile the ex- JULIET FLOYD, BOSTON UnIVERSITY pressive completeness of Wittgenstein’s N operator, with sev- CHRIS PINCOCK, OHIO STATE UnIVERSITY eral commonly recognized features of, and fundamental theses ASSISTANT REVIEW EDITOR within, the Tractarian logical system.