Propositional Logic: Semantics

Similar documents
Propositional Logic: Equivalence

Logic and Proofs. Jan COT3100: Applications of Discrete Structures Jan 2007

Definition 2. Conjunction of p and q

Chapter 1: The Logic of Compound Statements. January 7, 2008

CSC Discrete Math I, Spring Propositional Logic

Chapter Summary. Propositional Logic. Predicate Logic. Proofs. The Language of Propositions (1.1) Applications (1.2) Logical Equivalences (1.

Compound Propositions

Lecture 2. Logic Compound Statements Conditional Statements Valid & Invalid Arguments Digital Logic Circuits. Reading (Epp s textbook)

Chapter 1, Part I: Propositional Logic. With Question/Answer Animations

CSE 20: Discrete Mathematics

Learning Goals of CS245 Logic and Computation

Warm-Up Problem. Is the following true or false? 1/35

COM S 330 Homework 02 Solutions. Type your answers to the following questions and submit a PDF file to Blackboard. One page per problem.

Propositional Language - Semantics

Tautologies, Contradictions, and Contingencies

CHAPTER 1 - LOGIC OF COMPOUND STATEMENTS

Proofs. Joe Patten August 10, 2018

The Logic of Compound Statements cont.

Section 1.1: Logical Form and Logical Equivalence

Logic as a Tool Chapter 1: Understanding Propositional Logic 1.1 Propositions and logical connectives. Truth tables and tautologies

Announcements. CS311H: Discrete Mathematics. Propositional Logic II. Inverse of an Implication. Converse of a Implication

Discrete Mathematics and Its Applications

MACM 101 Discrete Mathematics I. Exercises on Propositional Logic. Due: Tuesday, September 29th (at the beginning of the class)

Logic, Sets, and Proofs

Propositional Logic 1

Chapter 1, Part I: Propositional Logic. With Question/Answer Animations

COMP Intro to Logic for Computer Scientists. Lecture 3

Discrete Mathematics and Its Applications

Truth-Functional Logic

Midterm: Sample 3. ECS20 (Fall 2017) 1) Using truth tables, establish for each of the two propositions below if it is a tautology, a contradiction

Propositional Equivalence

What is Logic? Introduction to Logic. Simple Statements. Which one is statement?

The Foundations: Logic and Proofs. Part I

Section 1.2 Propositional Equivalences. A tautology is a proposition which is always true. A contradiction is a proposition which is always false.

Chapter 4: Classical Propositional Semantics

CS1021. Why logic? Logic about inference or argument. Start from assumptions or axioms. Make deductions according to rules of reasoning.

Announcements. CS243: Discrete Structures. Propositional Logic II. Review. Operator Precedence. Operator Precedence, cont. Operator Precedence Example

A statement is a sentence that is definitely either true or false but not both.

Natural Deduction for Propositional Logic

Propositional logic ( ): Review from Mat 1348

We last time we began introducing equivalency laws.

Introduction to Decision Sciences Lecture 2

2.2: Logical Equivalence: The Laws of Logic

2. The Logic of Compound Statements Summary. Aaron Tan August 2017

Logic. Def. A Proposition is a statement that is either true or false.

Example. Logic. Logical Statements. Outline of logic topics. Logical Connectives. Logical Connectives

Review CHAPTER. 2.1 Definitions in Chapter Sample Exam Questions. 2.1 Set; Element; Member; Universal Set Partition. 2.

CSE 311: Foundations of Computing. Lecture 3: Digital Circuits & Equivalence

Math.3336: Discrete Mathematics. Applications of Propositional Logic

Sec$on Summary. Tautologies, Contradictions, and Contingencies. Logical Equivalence. Normal Forms (optional, covered in exercises in text)

1.1 Statements and Compound Statements

Logic Overview, I. and T T T T F F F T F F F F

Propositional Logic: Methods of Proof (Part II)

Homework assignment 1: Solutions

Normal Forms of Propositional Logic

Propositional Logic and Semantics

CS250: Discrete Math for Computer Science. L6: CNF and Natural Deduction for PropCalc

15414/614 Optional Lecture 1: Propositional Logic

CS100: DISCRETE STRUCTURES. Lecture 5: Logic (Ch1)

Announcements CompSci 102 Discrete Math for Computer Science

Packet #1: Logic & Proofs. Applied Discrete Mathematics

EECS 1028 M: Discrete Mathematics for Engineers

CSE 311: Foundations of Computing. Lecture 2: More Logic, Equivalence & Digital Circuits

Propositional Logic. Fall () Propositional Logic Fall / 30

Discrete Mathematics and Applications COT3100

PROBLEM SET 3: PROOF TECHNIQUES

Mathematical Logic Part One

HW1 graded review form? HW2 released CSE 20 DISCRETE MATH. Fall

For all For every For each For any There exists at least one There exists There is Some

PUZZLE. You meet A, B, and C in the land of knights and knaves. A says Either B and I are both knights or we are both knaves.

Unit 1. Propositional Logic Reading do all quick-checks Propositional Logic: Ch. 2.intro, 2.2, 2.3, 2.4. Review 2.9

University of California, San Diego Department of Computer Science and Engineering CSE 20. Solutions to Midterm Exam Winter 2018

An Introduction to Logic 1.1 ~ 1.4 6/21/04 ~ 6/23/04

Chapter 4, Logic using Propositional Calculus Handout

Boolean Logic. CS 231 Dianna Xu

DISCRETE STRUCTURES WEEK5 LECTURE1

Logic. Part I: Propositional Logic. Max Schäfer. Formosan Summer School on Logic, Language, and Computation 2010

Math 10850, fall 2017, University of Notre Dame

Note: The area of logic that deals with propositions is called the propositional calculus or propositional logic.

PROPOSITIONAL CALCULUS

Proposition/Statement. Boolean Logic. Boolean variables. Logical operators: And. Logical operators: Not 9/3/13. Introduction to Logical Operators

CS 220: Discrete Structures and their Applications. Propositional Logic Sections in zybooks

Topic 1: Propositional logic

Why Learning Logic? Logic. Propositional Logic. Compound Propositions

Logic. Definition [1] A logic is a formal language that comes with rules for deducing the truth of one proposition from the truth of another.

Tecniche di Verifica. Introduction to Propositional Logic

Lecture 5 : Proofs DRAFT

Discrete Mathematical Structures. Chapter 1 The Foundation: Logic

1 The Foundation: Logic and Proofs

1 The Foundations. 1.1 Logic. A proposition is a declarative sentence that is either true or false, but not both.

First Order Logic: Syntax and Semantics

Natural Deduction. Formal Methods in Verification of Computer Systems Jeremy Johnson

Propositional Logic Basics Propositional Equivalences Normal forms Boolean functions and digital circuits. Propositional Logic.

Artificial Intelligence: Knowledge Representation and Reasoning Week 2 Assessment 1 - Answers

CSCE 222 Discrete Structures for Computing. Propositional Logic. Dr. Hyunyoung Lee. !!!!!! Based on slides by Andreas Klappenecker

Propositional Logic: Syntax

Assignment 3 Logic and Reasoning KEY

AMTH140 Lecture 8. Symbolic Logic

Equivalence and Implication

cis32-ai lecture # 18 mon-3-apr-2006

Transcription:

Propositional Logic: Semantics Alice Gao Lecture 4, September 19, 2017 Semantics 1/56

Announcements Semantics 2/56

The roadmap of propositional logic Semantics 3/56

FCC spectrum auction an application of propositional logic To repurpose radio spectrums 2 auctions: one to buy back spectrums from broadcasters the other to sell spectrums to telecoms A computational problem in the buy back auction: If I pay these broadcasters to go off air, could I repackage the spectrums and sell to telecoms? Could I lower your price and still manage to get useful spectrums to sell to telecoms? The problem comes down to, how many satisfiability problems can I solve in a very short amount of time? (determine that a formula is satisfiable or determine that it is unsatisfiable.) Talk by Kevin Leyton-Brown https://www.youtube.com/watch?v=u1-jjoivp70 Semantics 4/56

Learning goals By the end of this lecture, you should be able to Evaluate the truth value of a formula Define a (truth) valuation. Determine the truth value of a formula by using truth tables. Determine the truth value of a formula by using valuation trees. Determine and prove whether a formula has a particular property Define tautology, contradiction, and satisfiable formula. Compare and contrast the three properties (tautology, contradiction, and satisfiable formula). Prove whether a formula is a tautology, a contradiction, or satisfiable, using a truth table and/or a valuation tree. Describe strategies to prove whether a formula is a tautology, a contradiction or a satisfiable formula. Semantics 5/56

The meaning of well-formed formulas To interpret a formula, we have to give meanings to the propositional variables and the connectives. A propositional variable has no intrinsic meaning; it gets a meaning via a valuation. A (truth) valuation is a function F T from the set of all proposition variables to F T. It assigns true/false to every propositional variable. Two notations: and both denote the truth value of under the truth valuation. Semantics 6/56

Truth tables for connectives The unary connective : T F F T The binary connectives,,, and : F F F F T T F T F T T F T F F T F F T T T T T T Semantics 7/56

Truth value of a formula Fix a truth valuation. Every formula has a value under, denoted, determined as follows. 1.. 2. T if F F if T 3. T if T F otherwise 4. T if T or T F otherwise 5. T if F or T F otherwise 6. T if F otherwise Semantics 8/56

Evaluating a formula using a truth table Example. The truth table of. F F F F F T F F T F F T F T F T F F F T T T T T T F F T F F T F T T F F T T F T F F T T T T T T Semantics 9/56

Evaluating a formula using a truth table Build the truth table of. Semantics 10/56

Understanding the disjunction and the biconditional Exclusive OR Biconditional F F F F T F T T T F T F T T F T T T F T What is the difference between an inclusive OR (the disjunction) and an exclusive OR? What is the relationship between the exclusive OR and the biconditional? Semantics 11/56

Understanding the conditional Assume that proposition defined below is true. : If Alice is rich, she will pay your tuition. If Alice is rich, will she pay your tuition? a. Yes b. No c. Maybe If Alice is not rich, will she pay your tuition? a. Yes b. No c. Maybe Semantics 12/56

Understanding the conditional Alice is rich Alice will pay your tuition. If Alice is rich, she will pay your t F F T F T T T F F T T T Suppose that the implication is a promise that I made. How can you show that I broke my promise? If the premise is false, is the statement true or false? (Will the statement ever be contradicted?) When the conclusion is true, is the statement true or false? When the premise is true, how does the truth value of the statement compare to the truth value of the conclusion? Convert into a logically equivalent formula which only uses the connectives, and. Does this alternative formula make sense? Semantics 13/56

Another example of structural induction Theorem: Fix a truth valuation. Every formula has a value in F T. Proof: The property for is has a value in F T. 1. If is a propositional variable, then assigns it a value of T or F (by the definition of a truth valuation). 2. If has a value in F T, then also does, as shown by the truth table of. 3. If and each has a value in F T, then also does for every binary connective, as shown by the corresponding truth tables. By the principle of structural induction, every formula has a value. By the unique readability of formulas, we have proved that a formula has only one truth value under any truth valuation. QED Semantics 14/56

Tautology, Contradiction, Satisfiable A formula is a tautology if and only if for every truth valuation, T. A formula is a contradiction if and only if for every truth valuation, F. A formula is satisfiable if and only if there exists a truth valuation such that T. Semantics Properties of formulas 15/56

Relationships among the properties Divide the set of all formulas into 3 mutually exclusive and exhaustive sets. We know two things about these sets: A formula is in set 1 if and only if the formula is true in every row of the formula s truth table. A formula is in set 3 if and only if it is a contradiction. Which of the following statements is true? a. In set 3, every formula is false in every row of the formula s truth table. b. In set 2, every formula is true in at least one row and false in at least one row of the formula s truth table. c. Sets 2 and 3 contain exactly the set of satisfiable formulas. d. Two of (a), (b), and (c) are true. e. All of (a), (b), and (c) are true. Semantics Properties of formulas 16/56

Examples 1. 2. 3. 4. Semantics Properties of formulas 17/56

How to determine the properties of a formula Truth table Valuation tree Reasoning Semantics Properties of formulas 18/56

Valuation Tree Rather than fill out an entire truth table, we can analyze what happens if we plug in a truth value for one variable. T F F T T F F T F T T F T F T T T We can evaluate a formula by using these rules to construct a valuation tree. Semantics Properties of formulas 19/56

Example of a valuation tree Example. Show that is a tautology by using a valuation tree. Suppose T. We put T in for : T T T. Based on the truth tables for the connectives, the formula becomes. If T, this yields and then T. (Check!). If F, it yields F and then T. (Check!). Suppose F. We get F F F, Simplification yields F T T and eventually T. Thus every valuation makes the formula true, as required. Semantics Properties of formulas 20/56

Reasoning about the properties I found a valuation for which the formula is true. Does the formula have each property below? Tautology YES NO MAYBE Contradiction YES NO MAYBE Satisfiable YES NO MAYBE I found a valuation for which the formula is false. Does the formula have each property below? Tautology YES NO MAYBE Contradiction YES NO MAYBE Satisfiable YES NO MAYBE Semantics Properties of formulas 21/56

Examples 1. 2. 3. 4. Semantics Properties of formulas 22/56

A logic puzzle Each of the four cards has a number on one side and a color on the other side. How many cards do you have to turn over to test whether this statement is true: if a card has an even number on one side, then its opposite side is red? Your answer is (a) 0 (b) 1 (c) 2 (d) 3 (e) 4. Semantics Equivalence 23/56

Propositional Logic: Semantics Alice Gao Lecture 5, September 21, 2017 Semantics Equivalence 24/56

Announcements Semantics Equivalence 25/56

Clickers What are they for? Active learning, engagement Why do you ask us to answer twice? Peer instruction If you choose to be here, please participate! Semantics Equivalence 26/56

Outline for today How can we prove that two formulas have the same meaning? (Logical equivalence) Which set of connectives is sufficient to express all possible formulas? (Adequate set of connectives) Semantics Equivalence 27/56

Logical equivalence of formulas: Learning goals Prove that the logical equivalence of formulas using truth tables and/or logical identities. Describe strategies to prove logical equivalence using logical identities. Translate a condition in a block of code into a propositional logic formula. Simplify code using truth tables and logical identities. Determine whether a piece of code is live or dead using truth tables and logical identities. Adequate set of connectives: Prove that a set of connectives is an adequate set for propositional logic by using truth tables and logical identities. Prove that a set of connectives is not an adequate set for propositional logic. Semantics Equivalence 28/56

Definition of logical equivalence Two formulas and are logically equivalent if and only if they have the same value under any valuation., for every valuation. and must have the same final column in their truth tables. is a tautology. Semantics Equivalence 29/56

Why do we care about logical equivalence? Will I lose marks if I provide a solution that is syntactically different but logically equivalent to the provided solution? Do these two circuits behave the same way? Do these two pieces of code fragments behave the same way? Semantics Equivalence 30/56

You already know one way of proving logical equivalent. What is it? Theorem:. Semantics Equivalence 31/56

Logical Identities Commutativity Associativity Distributivity Idempotence Double Negation De Morgan s Laws Semantics Equivalence 32/56

Logical Identities, cont d Simplification I (Absorbtion) T T T F F F Simplification II Implication Contrapositive Equivalence Excluded Middle T Contradiction F Semantics Equivalence 33/56

A logical equivalence proof Theorem:. Proof:... to be filled in... Distributivity Simplification I Commutativity QED Semantics Equivalence 34/56

What is missing from the proof? A logical equivalence proof a. b. F c. d. None of these, but I know what it is. e. None of these, and there s not enough information to tell. Theorem:. Proof:... to be filled in... QED Distributivity Simplification I Commutativity Semantics Equivalence 35/56

A practice problem If it is sunny, I will play golf, provided that I am relaxed. : it is sunny. : I will play golf. : I am relaxed. A few translations: 1. 2. 3. Theorem:. Proof:... to be filled in... QED Semantics Equivalence 36/56

How do you prove non-equivalence? If it snows then I won t go to class, but I will do my assignment. : it snows. : I will go to class. : I will do my assignment. 2 possible translations: 1. 2. Theorem: and are not logically equivalent. Which valuation can we use to prove this theorem? a. F, F, F b. F, T, F c. T, T, T d. Two of these. e. All of these. Semantics Equivalence 37/56

Collected Wisdom Try getting rid of and. Try moving negations inward.. Work from the more complex side first, BUT Switch to different strategies/sides when you get stuck. In the end, write the proof in clean one-side-to-the-other form and double-check steps. Semantics Equivalence 38/56

A piece of pseudo code if ( (input > 0) or (not output) ) { if ( not (output and (queuelength < 100) ) ) { } else if ( output and (not (queuelength < 100)) ) { } else { } } else { } When does each piece of code get executed? Let : input > 0, : output, : queuelength < 100. Semantics Conditional Code 39/56

Simplifying the piece of pseudo code if ( i or (not u) ) { if ( not (u and q) ) { } else if ( u and (not q) ) { } else { } } else { } Which one of the following is incorrect? a. is executed when is true. b. is executed when is true. c. is executed when is true. d. is executed when is false and is true. e. All of them are correct. Semantics Conditional Code 40/56

A Code Example, cont d T T T T F F T T F T T T F T T T T F F T T F T T F F T F F F F T T T F F F T T Semantics Conditional Code 41/56

Finding Dead Code Prove that is dead code. That is, the conditions leading to is logically equivalent to F.... to be filled in... F Simplifying the above condition to F will necessarily use the following logical identities. a. Simplification I b. Excluded Middle c. Contradiction d. Two of the above e. All of the above Semantics Conditional Code 42/56

Finding Live Code Prove that is live code. That is, the conditions leading to is satisfiable. Theorem: Proof: QED... to be filled in... Semantics Conditional Code 43/56

Two pieces of code: Are they equivalent? Fragment 1: if ( i or (not u) ) { if ( not (u and q) ) { } else if ( u and (not q) ) { } else { } } else { } Fragment 2: if ( (i and u) and q ) { } else if ( (not i) and u ) { } else { } Semantics Conditional Code 44/56

Simplifying Code To prove that the two fragments are equivalent, show that each block of code,,, and is executed under equivalent conditions. Block Fragment 1 Fragment 2 F Semantics Conditional Code 45/56

The solution to the last logic puzzle Each of the four cards has a number on one side and a color on the other side. How many cards do you have to turn over to test whether this statement is true: if a card has an even number on one side, then its opposite side is red? Solution: You need to turn over 2 cards. If a card has an even number on one side, then you need to check that its opposite side is red. Also, if a card is NOT red, you need to check that its opposite side has an ODD number (this is the contrapositive of the given statement). Thus, you need to turn over the second card from the left and the first card from the right. Semantics Conditional Code 46/56

Another logic puzzle A very special island is inhabited only by knights and knaves. Knights always tell the truth, and knaves always lie. You meet three inhabitants: Alice, Rex and Bob. Alice says, Rex is a knave. Rex says, it s false that Bob is a knave. Bob claims, I am a knight or Alice is a knight. Can you determine who is a knight and who is a knave? Semantics Conditional Code 47/56

Adequate sets of connectives Semantics Adequate Sets of Connectives 48/56

Learning goals Prove that a set of connectives is an adequate set for propositional logic by using truth tables and logical identities. Prove that a set of connectives is not an adequate set for propositional logic. Semantics Adequate Sets of Connectives 49/56

Some questions first We started propositional logic by learning these connectives,,, and. Why did we learn these connectives? Using these connectives, can we express every propositional logic formula that we ever want to write? Are there any connectives in this set that are not necessary? Are there other connectives that we could define and use? Is there another set of connectives that we should have studied instead? Semantics Adequate Sets of Connectives 50/56

Some answers Is every connective we learned necessary? Nope! Recall that. We don t need at all. (We say that is definable in terms of and.) Are there other connectives that we could define and use? Yep! Let s take a look. Semantics Adequate Sets of Connectives 51/56

Adequate Sets of Connectives Which set of connectives is sufficient to express every possible propositional formula? This is called an adequate set of connectives. Any other connective connective is definable in terms of the ones in such a set. Theorem 1. is an adequate set of connectives. Theorem 2. Each of the sets,, and is adequate. Theorem 3. The set is not an adequate set of connectives. Semantics Adequate Sets of Connectives 52/56

An adequate set to start with Theorem 1. is an adequate set of connectives. Hint: use truth tables. How many people know a way to prove this theorem? Semantics Adequate Sets of Connectives 53/56

A reduction problem Theorem 1. is an adequate set of connectives. Now we can assume that theorem 1 holds. Theorem 2. Each of the sets,, and is adequate. By Theorem 1, the set is adequate. To prove that is adequate, we need to show that is definable in terms of and. To prove that is adequate, we need to show that is definable in terms of and. To prove that is adequate, we need to show that each of and is definable in terms of and. Semantics Adequate Sets of Connectives 54/56

A non-adequate set Theorem 3. The set is not an adequate set of connectives. Consider any formula which uses only and as connectives. Assume that every variable in the formula is true. What is the truth value of the formula? a. Always true b. Always false c. Sometimes true and sometimes false d. Not enough information to tell Semantics Adequate Sets of Connectives 55/56

A non-adequate set Theorem 3. The set is not an adequate set of connectives. Lemma: For any formula which uses only and as connectives, if every variable in the formula is true, then the formula is true. This lemma means that it is impossible to negate a formula using only and. We can prove the lemma using structural induction. Semantics Adequate Sets of Connectives 56/56