An Introduction to Formal Logic, Version 1.28
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Tt-Satisfiable
CMPSCI 601: Recall From Last Time Lecture 6 Boolean Syntax: ¡ ¢¤£¦¥¨§¨£ © §¨£ § Boolean variables: A boolean variable represents an atomic statement that may be either true or false. There may be infinitely many of these available. Boolean expressions: £ atomic: , (“top”), (“bottom”) § ! " # $ , , , , , for Boolean expressions Note that any particular expression is a finite string, and thus may use only finitely many variables. £ £ A literal is an atomic expression or its negation: , , , . As you may know, the choice of operators is somewhat arbitary as long as we have a complete set, one that suf- fices to simulate all boolean functions. On HW#1 we ¢ § § ! argued that is already a complete set. 1 CMPSCI 601: Boolean Logic: Semantics Lecture 6 A boolean expression has a meaning, a truth value of true or false, once we know the truth values of all the individual variables. ¢ £ # ¡ A truth assignment is a function ¢ true § false , where is the set of all variables. An as- signment is appropriate to an expression ¤ if it assigns a value to all variables used in ¤ . ¡ The double-turnstile symbol ¥ (read as “models”) de- notes the relationship between a truth assignment and an ¡ ¥ ¤ expression. The statement “ ” (read as “ models ¤ ¤ ”) simply says “ is true under ”. 2 ¡ ¤ ¥ ¤ If is appropriate to , we define when is true by induction on the structure of ¤ : is true and is false for any , £ A variable is true iff says that it is, ¡ ¡ ¡ ¡ " ! ¥ ¤ ¥ ¥ If ¤ , iff both and , ¡ ¡ ¡ ¡ " ¥ ¤ ¥ ¥ If ¤ , iff either or or both, ¡ ¡ ¡ ¡ " # ¥ ¤ ¥ ¥ If ¤ , unless and , ¡ ¡ ¡ ¡ $ ¥ ¤ ¥ ¥ If ¤ , iff and are both true or both false. 3 Definition 6.1 A boolean expression ¤ is satisfiable iff ¡ ¥ ¤ there exists . -
Application: Digital Logic Circuits
SECTION 2.4 Application: Digital Logic Circuits Copyright © Cengage Learning. All rights reserved. Application: Digital Logic Circuits Switches “in series” Switches “in parallel” Change closed and on are replaced by T, open and off are replaced by F? Application: Digital Logic Circuits • More complicated circuits correspond to more complicated logical expressions. • This correspondence has been used extensively in design and study of circuits. • Electrical engineers use language of logic when refer to values of signals produced by an electronic switch as being “true” or “false.” • Only that symbols 1 and 0 are used • symbols 0 and 1 are called bits, short for binary digits. • This terminology was introduced in 1946 by the statistician John Tukey. Black Boxes and Gates Black Boxes and Gates • Circuits: transform combinations of signal bits (1’s and 0’s) into other combinations of signal bits (1’s and 0’s). • Computer engineers and digital system designers treat basic circuits as black boxes. • Ignore inside of a black box (detailed implementation of circuit) • focused on the relation between the input and the output signals. • Operation of a black box is completely specified by constructing an input/output table that lists all its possible input signals together with their corresponding output signals. Black Boxes and Gates One possible correspondence of input to output signals is as follows: An Input/Output Table Black Boxes and Gates An efficient method for designing more complicated circuits is to build them by connecting less complicated black box circuits. Gates can be combined into circuits in a variety of ways. If the rules shown on the next page are obeyed, the result is a combinational circuit, one whose output at any time is determined entirely by its input at that time without regard to previous inputs. -
Chapter 9: Initial Theorems About Axiom System
Initial Theorems about Axiom 9 System AS1 1. Theorems in Axiom Systems versus Theorems about Axiom Systems ..................................2 2. Proofs about Axiom Systems ................................................................................................3 3. Initial Examples of Proofs in the Metalanguage about AS1 ..................................................4 4. The Deduction Theorem.......................................................................................................7 5. Using Mathematical Induction to do Proofs about Derivations .............................................8 6. Setting up the Proof of the Deduction Theorem.....................................................................9 7. Informal Proof of the Deduction Theorem..........................................................................10 8. The Lemmas Supporting the Deduction Theorem................................................................11 9. Rules R1 and R2 are Required for any DT-MP-Logic........................................................12 10. The Converse of the Deduction Theorem and Modus Ponens .............................................14 11. Some General Theorems About ......................................................................................15 12. Further Theorems About AS1.............................................................................................16 13. Appendix: Summary of Theorems about AS1.....................................................................18 2 Hardegree, -
Shalack V.I. Semiotic Foundations of Logic
Semiotic foundations of logic Vladimir I. Shalack abstract. The article offers a look at the combinatorial logic as the logic of signs operating in the most general sense. For this it is proposed slightly reformulate it in terms of introducing and replacement of the definitions. Keywords: combinatory logic, semiotics, definition, logic founda- tions 1 Language selection Let’s imagine for a moment what would be like the classical logic, if we had not studied it in the language of negation, conjunction, dis- junction and implication, but in the language of the Sheffer stroke. I recall that it can be defined with help of negation and conjunction as follows A j B =Df :(A ^ B): In turn, all connectives can be defined with help of the Sheffer stroke in following manner :A =Df (A j A) A ^ B =Df (A j B) j (A j B) A _ B =Df (A j A) j (B j B) A ⊃ B =Df A j (B j B): Modus ponens rule takes the following form A; A j (B j B) . B 226 Vladimir I. Shalack We can go further and following the ideas of M. Sch¨onfinkel to define two-argument infix quantifier ‘jx’ x A j B =Df 8x(A j B): Now we can use it to define Sheffer stroke and quantifiers. x A j B =Df A j B where the variable x is not free in the formulas A and B; y x y 8xA =Df (A j A) j (A j A) where the variable y is not free in the formula A; x y x 9xA =Df (A j A) j (A j A) where the variable y is not free in the formula A. -
Inference Versus Consequence* Göran Sundholm Leyden University
To appear in LOGICA Yearbook, 1998, Czech Acad. Sc., Prague. Inference versus Consequence* Göran Sundholm Leyden University The following passage, hereinafter "the passage", could have been taken from a modern textbook.1 It is prototypical of current logical orthodoxy: The inference (*) A1, …, Ak. Therefore: C is valid if and only if whenever all the premises A1, …, Ak are true, the conclusion C is true also. When (*) is valid, we also say that C is a logical consequence of A1, …, Ak. We write A1, …, Ak |= C. It is my contention that the passage does not properly capture the nature of inference, since it does not distinguish between valid inference and logical consequence. The view that the validity of inference is reducible to logical consequence has been made famous in our century by Tarski, and also by Wittgenstein in the Tractatus and by Quine, who both reduced valid inference to the logical truth of a suitable implication.2 All three were anticipated by Bolzano.3 Bolzano considered Urteile (judgements) of the form A is true where A is a Satz an sich (proposition in the modern sense).4 Such a judgement is correct (richtig) when the proposition A, that serves as the judgemental content, really is true.5 A correct judgement is an Erkenntnis, that is, a piece of knowledge.6 Similarly, for Bolzano, the general form I of inference * I am indebted to my colleague Dr. E. P. Bos who read an early version of the manuscript and offered valuable comments. 1 Could have been so taken and almost was; cf. -
CS 173: Discrete Structures, Spring 2012 Homework 1 Solutions
CS 173: Discrete Structures, Spring 2012 Homework 1 Solutions This homework contains 3 problems worth a total of 25 points. 1. [1 point] Finding information on Piazza How many pet rats does Margaret’s family have? (Hint: see Piazza.) Solution: Margaret’s family has six pet rats. 2. [4 points] Demographic Survey 3. [20 points] Logic operators The late 19th century philosopher Charles Peirce (rhymes with ‘hearse,’ not ‘fierce’) wrote about a set of logically dual operators and, in his writings, coined the term ‘Ampheck’ to describe them. The two most common Ampheck operators, the Peirce arrow (written ↓ or ⊥ or ∨ by different people) and the Sheffer stroke (written ↑ or | or ∧ by different people), are defined by the following truth table: p q p ↑ q p ↓ q T T F F T F T F F T T F F F T T (a) (4 points) The set of operators {∧, ∨, ¬} is functionally complete, which means that every logical statement can be expressed using only these three operators. Is the smaller set of operators {∨, ¬} also functionally complete? Explain why or why not. Solution: By De Morgan’s laws, ¬(¬p∨¬q) ≡ ¬¬p∧¬¬q ≡ p∧q So every logical statement using the ∧ operator can be rewritten in terms of the ∨ and ¬ operators. Since every logical statement can be expressed in terms of the ∧, ∨, and ¬ operators, this implies that every logical statement can be expressed in terms of the ∨ and ¬ operators, and so {∨, ¬} is functionally complete. (b) (4 points) Express ¬p using only the Sheffer stroke operation ↑. Solution: Note that ¬p is true if and only if p is false. -
Boolean Logic
Boolean logic Lecture 12 Contents . Propositions . Logical connectives and truth tables . Compound propositions . Disjunctive normal form (DNF) . Logical equivalence . Laws of logic . Predicate logic . Post's Functional Completeness Theorem Propositions . A proposition is a statement that is either true or false. Whichever of these (true or false) is the case is called the truth value of the proposition. ‘Canberra is the capital of Australia’ ‘There are 8 day in a week.’ . The first and third of these propositions are true, and the second and fourth are false. The following sentences are not propositions: ‘Where are you going?’ ‘Come here.’ ‘This sentence is false.’ Propositions . Propositions are conventionally symbolized using the letters Any of these may be used to symbolize specific propositions, e.g. :, Manchester, , … . is in Scotland, : Mammoths are extinct. The previous propositions are simple propositions since they make only a single statement. Logical connectives and truth tables . Simple propositions can be combined to form more complicated propositions called compound propositions. .The devices which are used to link pairs of propositions are called logical connectives and the truth value of any compound proposition is completely determined by the truth values of its component simple propositions, and the particular connective, or connectives, used to link them. ‘If Brian and Angela are not both happy, then either Brian is not happy or Angela is not happy.’ .The sentence about Brian and Angela is an example of a compound proposition. It is built up from the atomic propositions ‘Brian is happy’ and ‘Angela is happy’ using the words and, or, not and if-then. -
Propositional Logic
Mathematical Logic (Based on lecture slides by Stan Burris) George Voutsadakis1 1Mathematics and Computer Science Lake Superior State University LSSU Math 300 George Voutsadakis (LSSU) Logic January 2013 1 / 86 Outline 1 Propositional Logic Connectives, Formulas and Truth Tables Equivalences, Tautologies and Contradictions Substitution Replacement Adequate Sets of Connectives Disjunctive and Conjunctive Forms Valid Arguments, Tautologies and Satisfiability Compactness Epilogue: Other Propositional Logics George Voutsadakis (LSSU) Logic January 2013 2 / 86 Propositional Logic Connectives, Formulas and Truth Tables Subsection 1 Connectives, Formulas and Truth Tables George Voutsadakis (LSSU) Logic January 2013 3 / 86 Propositional Logic Connectives, Formulas and Truth Tables The Alphabet: Connectives and Variables The following are the basic logical connectives that we use to connect logical statements: Symbol Name Symbol Name 1 true ∧ and 0 false ∨ or ¬ not → implies ↔ iff In the same way that in algebra we use x, y, z,... to stand for unknown or varying numbers, in logic we use the propositional variables P, Q, R,... to stand for unknown or varying propositions or statements; Using the connectives and variables we can construct propositional formulas like ((P → (Q ∨ R)) ∧ ((¬Q) ↔ (1 ∨ P))). George Voutsadakis (LSSU) Logic January 2013 4 / 86 Propositional Logic Connectives, Formulas and Truth Tables Inductive (Recursive) Definition of Propositional Formulas Propositional formulas are formally built as follows: Every propositional variable P is a propositional formula; the constants 0 and 1 are propositional formulas; if F is a propositional formula, then (¬F ) is a propositional formula; if F and G are propositional formulas, then (F ∧ G), (F ∨ G), (F → G) and (F ↔ G) are propositional formulas. -
The Family of Lodato Proximities Compatible with a Given Topological Space
Can. J. Math., Vol. XXVI, No. 2, 1974, pp. 388-404 THE FAMILY OF LODATO PROXIMITIES COMPATIBLE WITH A GIVEN TOPOLOGICAL SPACE W. J. THRON AND R. H. WARREN Compendium. Let (X, $~) be a topological space. By 99?i we denote the family of all Lodato proximities on X which induced". We show that 99? i is a complete distributive lattice under set inclusion as ordering. Greatest lower bound and least upper bound are characterized. A number of techniques for constructing elements of SDîi are developed. By means of one of these construc tions, all covers of any member of 99? i can be obtained. Several examples are given which relate 9D?i to the lattice 99? of all compatible proximities of Cech and the family 99?2 of all compatible proximities of Efremovic. The paper concludes with a chart which summarizes many of the structural properties of a», a»! and a»2. 1. Preliminaries and notation. M. W. Lodato in [51 and [6] has studied a symmetric generalized proximity structure (see Definition 1.2). Naimpally and Warrack [8] have called such a structure a Lodato proximity. We shall also use this name. The closure operator induced by a Lodato proximity satisfies the four Kuratowski closure conditions. This paper is primarily concerned with a study of the order structure of the family 99?i of all Lodato proximities which induce the same closure operator on a given set. Lodato characterized the least element in 99?i and those topo logical spaces for which 99?i ^ 0. Sharma and Naimpally [9] described the greatest member of 99? 1 and have given two methods for constructing members of 2»i. -
Combinational Circuits
Combinational Circuits Jason Filippou CMSC250 @ UMCP 06-02-2016 Jason Filippou (CMSC250 @ UMCP) Circuits 06-02-2016 1 / 1 Outline Jason Filippou (CMSC250 @ UMCP) Circuits 06-02-2016 2 / 1 Hardware design levels Hardware design levels Jason Filippou (CMSC250 @ UMCP) Circuits 06-02-2016 3 / 1 Hardware design levels Levels of abstraction for ICs Small Scale Integration: ≈ 10 boolean gates Medium Scale Integration: > 10; ≤ 100 Large Scale Integration: Anywhere between 100 and 30; 000. Very Large Scale Integration: Up to 150; 000. Very Very Large Scale Integration: > 150; 000. Jason Filippou (CMSC250 @ UMCP) Circuits 06-02-2016 4 / 1 Hardware design levels Example schematic Figure 1: VLSI schematic for a professional USB interface for Macintosh PCs. Jason Filippou (CMSC250 @ UMCP) Circuits 06-02-2016 5 / 1 Hardware design levels SSI Consists of circuits that contain about 10 gates. 16-bit adders. Encoders / Decoders. MUX/DEMUX. ::: All our examples will be at an SSI level. Logic Design is the branch of Computer Science that essentially analyzes the kinds of circuits and optimizations done at an SSI/MSI level. We do not have such a course in the curriculum, but you can expect to be exposed to it if you ever take 411. Jason Filippou (CMSC250 @ UMCP) Circuits 06-02-2016 6 / 1 Combinational Circuit Design Combinational Circuit Design Jason Filippou (CMSC250 @ UMCP) Circuits 06-02-2016 7 / 1 A sequential circuit is one where this constraint can be violated. Example: Flip-flops (yes, seriously). In this course, we will only touch upon combinational circuits. Combinational Circuit Design Combinational vs Sequential circuits A combinational circuit is one where the output of a gate is never used as an input into it. -
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 ............................................ -
Iso/Iec Jtc 1/Sc 2 N 3769/Wg2 N2866 Date: 2004-11-12
ISO/IEC JTC 1/SC 2 N 3769/WG2 N2866 DATE: 2004-11-12 ISO/IEC JTC 1/SC 2 Coded Character Sets Secretariat: Japan (JISC) DOC. TYPE Summary of Voting/Table of Replies Summary of Voting on ISO/IEC JTC 1/SC 2 N 3758 : ISO/IEC 14651/FPDAM 2, Information technology -- International string ordering TITLE and comparison -- Method for comparing character strings and description of the common template tailorable ordering -- AMENDMENT 2 SOURCE SC 2 Secretariat PROJECT JTC1.02.14651.00.02 This document is forwarded to Project Editor for resolution of comments. STATUS The Project Editor is requested to prepare a draft disposition of comments report, revised text and a recommendation for further processing. ACTION ID FYI DUE DATE P, O and L Members of ISO/IEC JTC 1/SC 2 ; ISO/IEC JTC 1 Secretariat; DISTRIBUTION ISO/IEC ITTF ACCESS LEVEL Def ISSUE NO. 202 NAME 02n3769.pdf SIZE FILE (KB) 24 PAGES Secretariat ISO/IEC JTC 1/SC 2 - IPSJ/ITSCJ *(Information Processing Society of Japan/Information Technology Standards Commission of Japan) Room 308-3, Kikai-Shinko-Kaikan Bldg., 3-5-8, Shiba-Koen, Minato-ku, Tokyo 105- 0011 Japan *Standard Organization Accredited by JISC Telephone: +81-3-3431-2808; Facsimile: +81-3-3431-6493; E-mail: [email protected] Summary of Voting on ISO/IEC JTC 1/SC 2 N 3758 : ISO/IEC 14651/FPDAM 2, Information technology -- International string ordering and comparison -- Method for comparing character strings and description of the common template tailorable ordering AMENDMENT 2 Q1 : FPDAM Consideration Q1 Not yet Comments Approve