Mathematical Logic Part One
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Logic in Action: Wittgenstein's Logical Pragmatism and the Impotence of Scepticism
This is the final, pre-publication draft. Please cite only from published paper in Philosophical Investigations 26:2 (April 2003), 125-48. LOGIC IN ACTION: WITTGENSTEIN'S LOGICAL PRAGMATISM AND THE IMPOTENCE OF SCEPTICISM DANIÈLE MOYAL-SHARROCK UNIVERSITY OF GENEVA 1. The Many Faces of Certainty: Wittgenstein's Logical Pragmatism So I am trying to say something that sounds like pragmatism. (OC 422) In his struggle to uncover the nature of our basic beliefs, Wittgenstein depicts them variously in On Certainty: he thinks of them in propositional terms, in pictorial terms and in terms of acting. As propositions, they would be of a peculiar sort – a hybrid between a logical and an empirical proposition (OC 136, 309). These are the so-called 'hinge propositions' of On Certainty (OC 341). Wittgenstein also thinks of these beliefs as forming a picture, a World-picture – or Weltbild (OC 167). This is a step in the right (nonpropositional) direction, but not the ultimate step. Wittgenstein's ultimate and crucial depiction of our basic beliefs is in terms of a know-how, an attitude, a way of acting (OC 204). Here, he treads on pragmatist ground. But can Wittgenstein be labelled a pragmatist, having himself rejected the affiliation because of its utility implication? But you aren't a pragmatist? No. For I am not saying that a proposition is true if it is useful. (RPP I, 266) Wittgenstein resists affiliation with pragmatism because he does not want his use of use to be confused with the utility use of use. For him, it is not that a proposition is true if it is useful, but that use gives the proposition its sense. -
Logic Model Workbook
Logic Model Workbook INNOVATION NETWORK, INC. www.innonet.org • [email protected] Logic Model Workbook Table of Contents Page Introduction - How to Use this Workbook .....................................................................2 Before You Begin .................................................................................................................3 Developing a Logic Model .................................................................................................4 Purposes of a Logic Model ............................................................................................... 5 The Logic Model’s Role in Evaluation ............................................................................ 6 Logic Model Components – Step by Step ....................................................................... 6 Problem Statement: What problem does your program address? ......................... 6 Goal: What is the overall purpose of your program? .............................................. 7 Rationale and Assumptions: What are some implicit underlying dynamics? ....8 Resources: What do you have to work with? ......................................................... 9 Activities: What will you do with your resources? ................................................ 11 Outputs: What are the tangible products of your activities? ................................. 13 Outcomes: What changes do you expect to occur as a result of your work?.......... 14 Outcomes Chain ...................................................................................... -
Introduction to Philosophy. Social Studies--Language Arts: 6414.16. INSTITUTION Dade County Public Schools, Miami, Fla
DOCUMENT RESUME ED 086 604 SO 006 822 AUTHOR Norris, Jack A., Jr. TITLE Introduction to Philosophy. Social Studies--Language Arts: 6414.16. INSTITUTION Dade County Public Schools, Miami, Fla. PUB DATE 72 NOTE 20p.; Authorized Course of Instruction for the Quinmester Program EDRS PRICE MF-$0.65 HC-$3.29 DESCRIPTORS Course Objectives; Curriculum Guides; Grade 10; Grade 11; Grade 12; *Language Arts; Learnin4 Activities; *Logic; Non Western Civilization; *Philosophy; Resource Guides; Secondary Grades; *Social Studies; *Social Studies Units; Western Civilization IDENTIFIERS *Quinmester Program ABSTRACT Western and non - western philosophers and their ideas are introduced to 10th through 12th grade students in this general social studies Quinmester course designed to be used as a preparation for in-depth study of the various schools of philosophical thought. By acquainting students with the questions and categories of philosophy, a point of departure for further study is developed. Through suggested learning activities the meaning of philosopky is defined. The Socratic, deductive, inductive, intuitive and eclectic approaches to philosophical thought are examined, as are three general areas of philosophy, metaphysics, epistemology,and axiology. Logical reasoning is applied to major philosophical questions. This course is arranged, as are other quinmester courses, with sections on broad goals, course content, activities, and materials. A related document is ED 071 937.(KSM) FILMED FROM BEST AVAILABLE COPY U S DEPARTMENT EDUCATION OF HEALTH. NAT10N41 -
A Survey of Indian Logic from the Point of View of Computer Science
Sadhana, "Col. 19, Part 6, December 1994, pp 971-983. © Printed in India A survey of Indian logic from the point of view of computer science V V S SARMA Department of Computer Science & Automation, Indian Institute of Science, Bangalore 560012, India Abstract. Indian logic has a long history. It somewhat covers the domains of two of the six schools (darsanas) of Indian philosophy, namely, Nyaya and Vaisesika. The generally accepted definition of In- dian logic over the ages is the science which ascertains valid knowledge either by means of six senses or by means of the five members of the syllogism. In other words, perception and inference constitute the sub- ject matter of logic. The science of logic evolved in India through three ~ges: the ancient, the medieval and the modern, spanning almost thirty centuries. Advances in Computer Science, in particular, in Artificial Intelligence have got researchers in these areas interested in the basic problems of language, logic and cognition in the past three decades. In the 1980s, Artificial Intelligence has evolved into knowledge-based and intelligent system design, and the knowledge base and inference engine have become standard subsystems of an intelligent System. One of the important issues in the design of such systems is knowledge acquisition from humans who are experts in a branch of learning (such as medicine or law) and transferring that knowledge to a computing system. The second important issue in such systems is the validation of the knowl- edge base of the system i.e. ensuring that the knowledge is complete and consistent. -
Deduction (I) Tautologies, Contradictions And
D (I) T, & L L October , Tautologies, contradictions and contingencies Consider the truth table of the following formula: p (p ∨ p) () If you look at the final column, you will notice that the truth value of the whole formula depends on the way a truth value is assigned to p: the whole formula is true if p is true and false if p is false. Contrast the truth table of (p ∨ p) in () with the truth table of (p ∨ ¬p) below: p ¬p (p ∨ ¬p) () If you look at the final column, you will notice that the truth value of the whole formula does not depend on the way a truth value is assigned to p. The formula is always true because of the meaning of the connectives. Finally, consider the truth table table of (p ∧ ¬p): p ¬p (p ∧ ¬p) () This time the formula is always false no matter what truth value p has. Tautology A statement is called a tautology if the final column in its truth table contains only ’s. Contradiction A statement is called a contradiction if the final column in its truth table contains only ’s. Contingency A statement is called a contingency or contingent if the final column in its truth table contains both ’s and ’s. Let’s consider some examples from the book. Can you figure out which of the following sentences are tautologies, which are contradictions and which contingencies? Hint: the answer is the same for all the formulas with a single row. () a. (p ∨ ¬p), (p → p), (p → (q → p)), ¬(p ∧ ¬p) b. -
Sets, Propositional Logic, Predicates, and Quantifiers
COMP 182 Algorithmic Thinking Sets, Propositional Logic, Luay Nakhleh Computer Science Predicates, and Quantifiers Rice University !1 Reading Material ❖ Chapter 1, Sections 1, 4, 5 ❖ Chapter 2, Sections 1, 2 !2 ❖ Mathematics is about statements that are either true or false. ❖ Such statements are called propositions. ❖ We use logic to describe them, and proof techniques to prove whether they are true or false. !3 Propositions ❖ 5>7 ❖ The square root of 2 is irrational. ❖ A graph is bipartite if and only if it doesn’t have a cycle of odd length. ❖ For n>1, the sum of the numbers 1,2,3,…,n is n2. !4 Propositions? ❖ E=mc2 ❖ The sun rises from the East every day. ❖ All species on Earth evolved from a common ancestor. ❖ God does not exist. ❖ Everyone eventually dies. !5 ❖ And some of you might already be wondering: “If I wanted to study mathematics, I would have majored in Math. I came here to study computer science.” !6 ❖ Computer Science is mathematics, but we almost exclusively focus on aspects of mathematics that relate to computation (that can be implemented in software and/or hardware). !7 ❖Logic is the language of computer science and, mathematics is the computer scientist’s most essential toolbox. !8 Examples of “CS-relevant” Math ❖ Algorithm A correctly solves problem P. ❖ Algorithm A has a worst-case running time of O(n3). ❖ Problem P has no solution. ❖ Using comparison between two elements as the basic operation, we cannot sort a list of n elements in less than O(n log n) time. ❖ Problem A is NP-Complete. -
The Etienne Gilson Series 21
The Etienne Gilson Series 21 Remapping Scholasticism by MARCIA L. COLISH 3 March 2000 Pontifical Institute of Mediaeval Studies This lecture and its publication was made possible through the generous bequest of the late Charles J. Sullivan (1914-1999) Note: the author may be contacted at: Department of History Oberlin College Oberlin OH USA 44074 ISSN 0-708-319X ISBN 0-88844-721-3 © 2000 by Pontifical Institute of Mediaeval Studies 59 Queen’s Park Crescent East Toronto, Ontario, Canada M5S 2C4 Printed in Canada nce upon a time there were two competing story-lines for medieval intellectual history, each writing a major role for scholasticism into its script. Although these story-lines were O created independently and reflected different concerns, they sometimes overlapped and gave each other aid and comfort. Both exerted considerable influence on the way historians of medieval speculative thought conceptualized their subject in the first half of the twentieth cen- tury. Both versions of the map drawn by these two sets of cartographers illustrated what Wallace K. Ferguson later described as “the revolt of the medievalists.”1 One was confined largely to the academy and appealed to a wide variety of medievalists, while the other had a somewhat narrower draw and reflected political and confessional, as well as academic, concerns. The first was the anti-Burckhardtian effort to push Renaissance humanism, understood as combining a knowledge and love of the classics with “the discovery of the world and of man,” back into the Middle Ages. The second was inspired by the neo-Thomist revival launched by Pope Leo XIII, and was inhabited almost exclusively by Roman Catholic scholars. -
On Axiomatizations of General Many-Valued Propositional Calculi
On axiomatizations of general many-valued propositional calculi Arto Salomaa Turku Centre for Computer Science Joukahaisenkatu 3{5 B, 20520 Turku, Finland asalomaa@utu.fi Abstract We present a general setup for many-valued propositional logics, and compare truth-table and axiomatic stipulations within this setup. Results are obtained concerning cases, where a finitary axiomatization is (resp. is not) possible. Related problems and examples are discussed. 1 Introduction Many-valued systems of logic are constructed by introducing one or more truth- values between truth and falsity. Truth-functions associated with the logical connectives then operate with more than two truth-values. For instance, the truth-function D associated with the 3-valued disjunction might be defined for the truth-values T;I;F (true, intermediate, false) by D(x; y) = max(x; y); where T > I > F: If the truth-function N associated with negation is defined by N(T ) = F; N(F ) = T;N(I) = I; the law of the excluded middle is not valid, provided \validity" means that the truth-value t results for all assignments of values for the variables. On the other hand, many-valuedness is not so obvious if the axiomatic method is used. As such, an ordinary axiomatization is not many-valued. Truth-tables are essential for the latter. However, in many cases it is possi- ble to axiomatize many-valued logics and, conversely, find many-valued models for axiom systems. In this paper, we will investigate (for propositional log- ics) interconnections between such \truth-value stipulations" and \axiomatic stipulations". A brief outline of the contents of this paper follows. -
Logical Empiricism / Positivism Some Empiricist Slogans
4/13/16 Logical empiricism / positivism Some empiricist slogans o Hume’s 18th century book-burning passage Key elements of a logical positivist /empiricist conception of science o Comte’s mid-19th century rejection of n Motivations for post WW1 ‘scientific philosophy’ ‘speculation after first & final causes o viscerally opposed to speculation / mere metaphysics / idealism o Duhem’s late 19th/early 20th century slogan: o a normative demarcation project: to show why science ‘save the phenomena’ is and should be epistemically authoritative n Empiricist commitments o Hempel’s injunction against ‘detours n Logicism through the realm of unobservables’ Conflicts & Memories: The First World War Vienna Circle Maria Marchant o Debussy: Berceuse héroique, Élégie So - what was the motivation for this “revolutionary, written war-time Paris (1914), heralds the ominous bugle call of war uncompromising empricism”? (Godfrey Smith, Ch. 2) o Rachmaninov: Études-Tableaux Op. 39, No 8, 5 “some of the most impassioned, fervent work the composer wrote” Why the “massive intellectual housecleaning”? (Godfrey Smith) o Ireland: Rhapsody, London Nights, London Pieces a “turbulant, virtuosic work… Consider the context: World War I / the interwar period o Prokofiev: Visions Fugitives, Op. 22 written just before he fled as a fugitive himself to the US (1917); military aggression & sardonic irony o Ravel: Le Tombeau de Couperin each of six movements dedicated to a friend who died in the war x Key problem (1): logicism o Are there, in fact, “rules” governing inference -
12 Propositional Logic
CHAPTER 12 ✦ ✦ ✦ ✦ Propositional Logic In this chapter, we introduce propositional logic, an algebra whose original purpose, dating back to Aristotle, was to model reasoning. In more recent times, this algebra, like many algebras, has proved useful as a design tool. For example, Chapter 13 shows how propositional logic can be used in computer circuit design. A third use of logic is as a data model for programming languages and systems, such as the language Prolog. Many systems for reasoning by computer, including theorem provers, program verifiers, and applications in the field of artificial intelligence, have been implemented in logic-based programming languages. These languages generally use “predicate logic,” a more powerful form of logic that extends the capabilities of propositional logic. We shall meet predicate logic in Chapter 14. ✦ ✦ ✦ ✦ 12.1 What This Chapter Is About Section 12.2 gives an intuitive explanation of what propositional logic is, and why it is useful. The next section, 12,3, introduces an algebra for logical expressions with Boolean-valued operands and with logical operators such as AND, OR, and NOT that Boolean algebra operate on Boolean (true/false) values. This algebra is often called Boolean algebra after George Boole, the logician who first framed logic as an algebra. We then learn the following ideas. ✦ Truth tables are a useful way to represent the meaning of an expression in logic (Section 12.4). ✦ We can convert a truth table to a logical expression for the same logical function (Section 12.5). ✦ The Karnaugh map is a useful tabular technique for simplifying logical expres- sions (Section 12.6). -
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.