Foundations of Logic Mathematical Logic is a tool for working with elaborate compound statements. It includes: A formal language for expressing them.

Slides:



Advertisements
Similar presentations
Af2 Introduction. What’s the course about? Discrete Mathematics The mathematics that underpins computer science and other sciences as well.
Advertisements

Grading Lecture attendance: -1% per 2 unexcused absences
1. Propositions A proposition is a declarative sentence that is either true or false. Examples of propositions: The Moon is made of green cheese. Trenton.
Syllabus Every Week: 2 Hourly Exams +Final - as noted on Syllabus
From Chapter 4 Formal Specification using Z David Lightfoot
1 Section 1.1 Logic. 2 Proposition Statement that is either true or false –can’t be both –in English, must contain a form of “to be” Examples: –Cate Sheller.
Discrete Mathematics Math 6A Instructor: M. Welling.
Propositional Calculus Math Foundations of Computer Science.
Adapted from Discrete Math
Lecture 8 Introduction to Logic CSCI – 1900 Mathematics for Computer Science Fall 2014 Bill Pine.
The Foundations: Logic and Proofs
Discrete Mathematics Goals of a Discrete Mathematics Learn how to think mathematically 1. Mathematical Reasoning Foundation for discussions of methods.
Intro to Discrete Structures
Propositions and Truth Tables
2009/9 1 Logic and Proofs §1.1 Introduction §1.2 Propositional Equivalences §1.3 Predicates and Quantifiers §1.4 Nested Quantifiers §1.5~7 Methods of Proofs.
Discrete Maths 2. Propositional Logic Objective
Discrete Mathematics and Its Applications
Discrete Mathematics CS 285. Lecture 12 Section 1.1: Logic Axiomatic concepts in math: Equals Opposite Truth and falsehood Statement Objects Collections.
CompSci 102 Discrete Math for Computer Science January 17, 2012 Prof. Rodger.
2009/9 1 Logic and Proofs §1.1 Introduction §1.2 Propositional Equivalences §1.3 Predicates and Quantifiers §1.4 Nested Quantifiers §1.5~7 Methods of.
© by Kenneth H. Rosen, Discrete Mathematics & its Applications, Sixth Edition, Mc Graw-Hill, 2007 Ch.1 (Part 1): The Foundations: Logic and Proofs Introduction.
1 Propositional Logic Rosen 5 th ed., § Foundations of Logic: Overview Propositional logic:Propositional logic: –Basic definitions. –Equivalence.
Propositional Logic Foundations of Logic: Overview Propositional logic (§ ): – Basic definitions. (§1.1) – Equivalence rules & derivations. (§1.2)
CS 285- Discrete Mathematics Lecture 2. Section 1.1 Propositional Logic Propositions Conditional Statements Truth Tables of Compound Propositions Translating.
Chapter 1: The Foundations: Logic and Proofs
CompSci Welcome! Discrete Mathematics for Computer Science CompSci 102 D243 LSRC M, W 10:05-11:20 Professor: Jeffrey Forbes.
Lecture 4. CONDITIONAL STATEMENTS: Consider the statement: "If you earn an A in Math, then I'll buy you a computer." This statement is made up of two.
1 CMSC 250 Discrete Structures CMSC 250 Lecture 1.
Propositional Calculus CS 270: Mathematical Foundations of Computer Science Jeremy Johnson.
LOGIC Lesson 2.1. What is an on-the-spot Quiz  This quiz is defined by me.  While I’m having my lectures, you have to be alert.  Because there are.
Discrete Mathematics CS 285. Lecture 12 Quick Overview The conceptual center of computer science is the ALGORITHM.
Chapter 1: The Foundations: Logic and Proofs
Section 1.1. Section Summary Propositions Connectives Negation Conjunction Disjunction Implication; contrapositive, inverse, converse Biconditional Truth.
Mathematics for Comter I Lecture 2: Logic (1) Basic definitions Logical operators Translating English sentences.
رياضيات متقطعة لعلوم الحاسب MATH 226. Text books: (Discrete Mathematics and its applications) Kenneth H. Rosen, seventh Edition, 2012, McGraw- Hill.
Section 1.1. Propositions A proposition is a declarative sentence that is either true or false. Examples of propositions: a) The Moon is made of green.
1 Georgia Tech, IIC, GVU, 2006 MAGIC Lab Rossignac Lecture 01: Boolean Logic Sections 1.1 and 1.2 Jarek Rossignac.
CS104 The Foundations: Logic and Proof 1. 2 What is Discrete Structure?  Discrete Objects  Separated from each other (Opposite of continuous)  e.g.,
Chapter 1. Chapter Summary  Propositional Logic  The Language of Propositions (1.1)  Logical Equivalences (1.3)  Predicate Logic  The Language of.
Module #1 - Logic 2016/7/91 Module #1: Logic (Textbook: §1.1~1.4) Dr. Chih-Wei Yi Department of Computer Science National Chiao Tung University.
Propositional Logic. Logic Logic: the science of reasoning, proof, thinking or inference. Logic allows us to analyze a piece of reasoning and determine.
Logic I 권태경 To do so, it should include a language to express statements, a notation to simplify expressions. Logic Mathematical Logic.
Simple Logic.
Discrete Structures for Computer Science Presented By: Andrew F. Conn Slides adapted from: Adam J. Lee Lecture #1: Introduction, Propositional Logic August.
Chapter 1 Propositional Logic
Propositional Calculus: Boolean Functions and Expressions
Discrete Mathematics Lecture 1 Logic of Compound Statements
CSNB 143 Discrete Mathematical Structures
Lecture 1 – Formal Logic.
CS 202, Spring 2008 Epp, sections 1.1 and 1.2
Niu Kun Discrete Mathematics Chapter 1 The Foundations: Logic and Proof, Sets, and Functions Niu Kun 离散数学.
6/20/2018 Discrete Math A word about organization: Since different courses have different lengths of lecture periods, and different instructors go at different.
6/20/2018 Arab Open University Faculty of Computer Studies M131 - Discrete Mathematics 6/20/2018.
COT 3100, Spr Applications of Discrete Structures
Ch.1 (Part 1): The Foundations: Logic and Proofs
Propositional Logic (§1.1)
Propositional Calculus: Boolean Functions and Expressions
The Foundations: Logic and Proofs
Principles of Computing – UFCFA3-30-1
Information Technology Department
Discrete Mathematics and its Applications
MAT 3100 Introduction to Proof
Cs Discrete Mathematics
The Foundations: Logic and Proofs
Logic Logic is a discipline that studies the principles and methods used to construct valid arguments. An argument is a related sequence of statements.
Logic of Informatics Introduction.
Discrete Structures Prepositional Logic 2
The Foundations: Logic and Proofs
Starting out with formal logic
Presentation transcript:

Foundations of Logic Mathematical Logic is a tool for working with elaborate compound statements. It includes: A formal language for expressing them. A concise notation for writing them. A methodology for objectively reasoning about their truth or falsity. It is the foundation for expressing formal proofs in all branches of mathematics.

Foundations of Logic: Overview Propositional logic (§ ): –Basic definitions. (§1.1) –Equivalence rules & derivations. (§1.2) Predicate logic (§ ) –Predicates. –Quantified predicate expressions. –Equivalences & derivations.

Propositional Logic (§1.1) Propositional Logic is the logic of compound statements built from simpler statements using so-called Boolean connectives. Some applications in computer science: Design of digital electronic circuits. Expressing conditions in programs. Queries to databases & search engines. Topic #1 – Propositional Logic George Boole ( ) Chrysippus of Soli (ca. 281 B.C. – 205 B.C.)

Definition of a Proposition Definition: A proposition (denoted p, q, r, …) is simply: a statement (i.e., a declarative sentence) –with some definite meaning, (not vague or ambiguous) having a truth value that’s either true (T) or false (F) –it is never both, neither, or somewhere “in between!” However, you might not know the actual truth value, and, the value might depend on the situation or context. Later, we will study probability theory, in which we assign degrees of certainty (“between” T and F) to propositions. –But for now: think True/False only! Topic #1 – Propositional Logic

Examples of Propositions “It is raining.” (In a given situation.) “Beijing is the capital of China.” “1 + 2 = 3” But, the following are NOT propositions: “Who’s there?” (interrogative, question) “La la la la la.” (meaningless interjection) “Just do it!” (imperative, command) “Yeah, I sorta dunno, whatever...” (vague) “1 + 2” (expression with a non-true/false value) Topic #1 – Propositional Logic

An operator or connective combines one or more operand expressions into a larger expression. (E.g., “+” in numeric exprs.) Unary operators take 1 operand (e.g., −3); binary operators take 2 operands (eg 3  4). Propositional or Boolean operators operate on propositions (or their truth values) instead of on numbers. Operators / Connectives Topic #1.0 – Propositional Logic: Operators

Some Popular Boolean Operators Formal NameNicknameAritySymbol Negation operatorNOTUnary¬ Conjunction operatorANDBinary  Disjunction operatorORBinary  Exclusive-OR operatorXORBinary  Implication operatorIMPLIESBinary  Biconditional operatorIFFBinary↔ Topic #1.0 – Propositional Logic: Operators

The Negation Operator The unary negation operator “¬” (NOT) transforms a prop. into its logical negation. E.g. If p = “I have brown hair.” then ¬p = “I do not have brown hair.” The truth table for NOT: T :≡ True; F :≡ False “:≡” means “is defined as” Operand column Result column Topic #1.0 – Propositional Logic: Operators

The Conjunction Operator The binary conjunction operator “  ” (AND) combines two propositions to form their logical conjunction. E.g. If p=“I will have salad for lunch.” and q=“I will have steak for dinner.”, then p  q=“I will have salad for lunch and I will have steak for dinner.”  ” points up like an “A”, and it means “  ND ” Remember: “  ” points up like an “A”, and it means “  ND ”  ND Topic #1.0 – Propositional Logic: Operators

Note that a conjunction p 1  p 2  …  p n of n propositions will have 2 n rows in its truth table. Also: ¬ and  operations together are suffi- cient to express any Boolean truth table! Conjunction Truth Table Operand columns Topic #1.0 – Propositional Logic: Operators

The Disjunction Operator The binary disjunction operator “  ” (OR) combines two propositions to form their logical disjunction. p=“My car has a bad engine.” q=“My car has a bad carburetor.” p  q=“Either my car has a bad engine, or my car has a bad carburetor.”  ” splits the wood, you can take 1 piece OR the other, or both. After the downward- pointing “axe” of “  ” splits the wood, you can take 1 piece OR the other, or both.  Topic #1.0 – Propositional Logic: Operators Meaning is like “and/or” in English.

Note that p  q means that p is true, or q is true, or both are true! So, this operation is also called inclusive or, because it includes the possibility that both p and q are true. “¬” and “  ” together are also universal. Disjunction Truth Table Note difference from AND Topic #1.0 – Propositional Logic: Operators

Nested Propositional Expressions Use parentheses to group sub-expressions: “I just saw my old friend, and either he’s grown or I’ve shrunk.” = f  (g  s) – (f  g)  s would mean something different – f  g  s would be ambiguous By convention, “¬” takes precedence over both “  ” and “  ”. – ¬s  f means (¬s)  f, not ¬ (s  f) Topic #1.0 – Propositional Logic: Operators

A Simple Exercise Let p=“It rained last night”, q=“The sprinklers came on last night,” r=“The lawn was wet this morning.” Translate each of the following into English: ¬p = r  ¬p = ¬ r  p  q = “It didn’t rain last night.” “The lawn was wet this morning, and it didn’t rain last night.” “Either the lawn wasn’t wet this morning, or it rained last night, or the sprinklers came on last night.” Topic #1.0 – Propositional Logic: Operators

The Exclusive Or Operator The binary exclusive-or operator “  ” (XOR) combines two propositions to form their logical “exclusive or” (exjunction?). p = “I will earn an A in this course,” q = “I will drop this course,” p  q = “I will either earn an A in this course, or I will drop it (but not both!)” Topic #1.0 – Propositional Logic: Operators

Note that p  q means that p is true, or q is true, but not both! This operation is called exclusive or, because it excludes the possibility that both p and q are true. “¬” and “  ” together are not universal. Exclusive-Or Truth Table Note difference from OR. Topic #1.0 – Propositional Logic: Operators

Note that English “or” can be ambiguous regarding the “both” case! “Pat is a singer or Pat is a writer.” - “Pat is a man or Pat is a woman.” - Need context to disambiguate the meaning! For this class, assume “or” means inclusive. Natural Language is Ambiguous   Topic #1.0 – Propositional Logic: Operators

The Implication Operator The implication p  q states that p implies q. I.e., If p is true, then q is true; but if p is not true, then q could be either true or false. E.g., let p = “You study hard.” q = “You will get a good grade.” p  q = “If you study hard, then you will get a good grade.” (else, it could go either way) Topic #1.0 – Propositional Logic: Operators antecedentconsequent

Examples of Implications “If this lecture ends, then the sun will rise tomorrow.” True or False? “If Tuesday is a day of the week, then I am a penguin.” True or False? “If 1+1=6, then Bush is president.” True or False? “If the moon is made of green cheese, then I am richer than Bill Gates.” True or False? Topic #1.0 – Propositional Logic: Operators

Why does this seem wrong? Consider a sentence like, –“If I wear a red shirt tomorrow, then Osama bin Laden will be captured!” In logic, we consider the sentence True so long as either I don’t wear a red shirt, or Osama is caught. But, in normal English conversation, if I were to make this claim, you would think that I was lying. –Why this discrepancy between logic & language?

Resolving the Discrepancy In English, a sentence “if p then q” usually really implicitly means something like, –“In all possible situations, if p then q.” That is, “For p to be true and q false is impossible.” Or, “I guarantee that no matter what, if p, then q.” This can be expressed in predicate logic as: –“For all situations s, if p is true in situation s, then q is also true in situation s” –Formally, we could write:  s, P(s) → Q(s) That sentence is logically False in our example, because for me to wear a red shirt and for Osama to stay free is a possible (even if not actual) situation. –Natural language and logic then agree with each other.

English Phrases Meaning p  q “p implies q” “if p, then q” “if p, q” “when p, q” “whenever p, q” “q if p” “q when p” “q whenever p” “p only if q” “p is sufficient for q” “q is necessary for p” “q follows from p” “q is implied by p” We will see some equivalent logic expressions later. Topic #1.0 – Propositional Logic: Operators

Converse, Inverse, Contrapositive Some terminology, for an implication p  q: Its converse is: q  p. Its inverse is: ¬p  ¬q. Its contrapositive:¬q  ¬ p. One of these three has the same meaning (same truth table) as p  q. Can you figure out which? Topic #1.0 – Propositional Logic: Operators

How do we know for sure? Proving the equivalence of p  q and its contrapositive using truth tables: Topic #1.0 – Propositional Logic: Operators

The biconditional operator The biconditional p  q states that p is true if and only if (IFF) q is true. p = “Bush wins the 2004 election.” q = “Bush will be president for all of 2005.” p  q = “If, and only if, Bush wins the 2004 election, Bush will be president for all of 2005.” Topic #1.0 – Propositional Logic: Operators 2004 I’m still here! 2005

Biconditional Truth Table p  q means that p and q have the same truth value. Note this truth table is the exact opposite of  ’s! Thus, p  q means ¬(p  q) p  q does not imply that p and q are true, or cause each other. Topic #1.0 – Propositional Logic: Operators

Boolean Operations Summary We have seen 1 unary operator (out of the 4 possible) and 5 binary operators (out of the 16 possible). Their truth tables are below. Topic #1.0 – Propositional Logic: Operators

Some Alternative Notations Topic #1.0 – Propositional Logic: Operators

Bit Strings A Bit string of length n is an ordered series or sequence of n  0 bits. –More on sequences in §3.2. By convention, bit strings are written left to right: e.g. the first bit of “ ” is 1. When a bit string represents a base-2 number, by convention the first bit is the most significant bit. Ex =8+4+1=13. Topic #2 – Bits

Counting in Binary Did you know that you can count to 1,023 just using two hands? –How? Count in binary! Each finger (up/down) represents 1 bit. To increment: Flip the rightmost (low-order) bit. –If it changes 1→0, then also flip the next bit to the left, If that bit changes 1→0, then flip the next one, etc , , , … …, , , Topic #2 – Bits

End of §1.1 You have learned about: Propositions: What they are. Propositional logic operators’ –Symbolic notations. –English equivalents. –Logical meaning. –Truth tables. Atomic vs. compound propositions. Alternative notations. Bits and bit-strings. Next section: §1.2 –Propositional equivalences. –How to prove them.