Chapter 2 Logic
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CSE Yet, Please Do Well! Logical Connectives
administrivia Course web: http://www.cs.washington.edu/311 Office hours: 12 office hours each week Me/James: MW 10:30-11:30/2:30-3:30pm or by appointment TA Section: Start next week Call me: Shayan Don’t: Actually call me. Homework #1: Will be posted today, due next Friday by midnight (Oct 9th) Gradescope! (stay tuned) Extra credit: Not required to get a 4.0. Counts separately. In total, may raise grade by ~0.1 Don’t be shy (raise your hand in the back)! Do space out your participation. If you are not CSE yet, please do well! logical connectives p q p q p p T T T T F T F F F T F T F NOT F F F AND p q p q p q p q T T T T T F T F T T F T F T T F T T F F F F F F OR XOR 푝 → 푞 • “If p, then q” is a promise: p q p q F F T • Whenever p is true, then q is true F T T • Ask “has the promise been broken” T F F T T T If it’s raining, then I have my umbrella. related implications • Implication: p q • Converse: q p • Contrapositive: q p • Inverse: p q How do these relate to each other? How to see this? 푝 ↔ 푞 • p iff q • p is equivalent to q • p implies q and q implies p p q p q Let’s think about fruits A fruit is an apple only if it is either red or green and a fruit is not red and green. -
Conditional Statement/Implication Converse and Contrapositive
Conditional Statement/Implication CSCI 1900 Discrete Structures •"ifp then q" • Denoted p ⇒ q – p is called the antecedent or hypothesis Conditional Statements – q is called the consequent or conclusion Reading: Kolman, Section 2.2 • Example: – p: I am hungry q: I will eat – p: It is snowing q: 3+5 = 8 CSCI 1900 – Discrete Structures Conditional Statements – Page 1 CSCI 1900 – Discrete Structures Conditional Statements – Page 2 Conditional Statement/Implication Truth Table Representing Implication (continued) • In English, we would assume a cause- • If viewed as a logic operation, p ⇒ q can only be and-effect relationship, i.e., the fact that p evaluated as false if p is true and q is false is true would force q to be true. • This does not say that p causes q • If “it is snowing,” then “3+5=8” is • Truth table meaningless in this regard since p has no p q p ⇒ q effect at all on q T T T • At this point it may be easiest to view the T F F operator “⇒” as a logic operationsimilar to F T T AND or OR (conjunction or disjunction). F F T CSCI 1900 – Discrete Structures Conditional Statements – Page 3 CSCI 1900 – Discrete Structures Conditional Statements – Page 4 Examples where p ⇒ q is viewed Converse and contrapositive as a logic operation •Ifp is false, then any q supports p ⇒ q is • The converse of p ⇒ q is the implication true. that q ⇒ p – False ⇒ True = True • The contrapositive of p ⇒ q is the –False⇒ False = True implication that ~q ⇒ ~p • If “2+2=5” then “I am the king of England” is true CSCI 1900 – Discrete Structures Conditional Statements – Page 5 CSCI 1900 – Discrete Structures Conditional Statements – Page 6 1 Converse and Contrapositive Equivalence or biconditional Example Example: What is the converse and •Ifp and q are statements, the compound contrapositive of p: "it is raining" and q: I statement p if and only if q is called an get wet? equivalence or biconditional – Implication: If it is raining, then I get wet. -
Logical Connectives Good Problems: March 25, 2008
Logical Connectives Good Problems: March 25, 2008 Mathematics has its own language. As with any language, effective communication depends on logically connecting components. Even the simplest “real” mathematical problems require at least a small amount of reasoning, so it is very important that you develop a feeling for formal (mathematical) logic. Consider, for example, the two sentences “There are 10 people waiting for the bus” and “The bus is late.” What, if anything, is the logical connection between these two sentences? Does one logically imply the other? Similarly, the two mathematical statements “r2 + r − 2 = 0” and “r = 1 or r = −2” need to be connected, otherwise they are merely two random statements that convey no useful information. Warning: when mathematicians talk about implication, it means that one thing must be true as a consequence of another; not that it can be true, or might be true sometimes. Words and symbols that tie statements together logically are called logical connectives. They allow you to communicate the reasoning that has led you to your conclusion. Possibly the most important of these is implication — the idea that the next statement is a logical consequence of the previous one. This concept can be conveyed by the use of words such as: therefore, hence, and so, thus, since, if . then . , this implies, etc. In the middle of mathematical calculations, we can represent these by the implication symbol (⇒). For example 3 − x x + 7y2 = 3 ⇒ y = ± ; (1) r 7 x ∈ (0, ∞) ⇒ cos(x) ∈ [−1, 1]. (2) Converse Note that “statement A ⇒ statement B” does not necessarily mean that the logical converse — “statement B ⇒ statement A” — is also true. -
2-2 Statements, Conditionals, and Biconditionals
2-2 Statements, Conditionals, and Biconditionals Use the following statements to write a 3. compound statement for each conjunction or SOLUTION: disjunction. Then find its truth value. Explain your reasoning. is a disjunction. A disjunction is true if at least p: A week has seven days. one of the statements is true. q is false, since there q: There are 20 hours in a day. are 24 hours in a day, not 20 hours. r is true since r: There are 60 minutes in an hour. there are 60 minutes in an hour. Thus, is true, 1. p and r because r is true. SOLUTION: ANSWER: p and r is a conjunction. A conjunction is true only There are 20 hours in a day, or there are 60 minutes when both statements that form it are true. p is true in an hour. since a week has seven day. r is true since there are is true, because r is true. 60 minutes in an hour. Then p and r is true, 4. because both p and r are true. SOLUTION: ANSWER: ~p is a negation of statement p, or the opposite of A week has seven days, and there are 60 minutes in statement p. The or in ~p or q indicates a an hour. p and r is true, because p is true and r is disjunction. A disjunction is true if at least one of the true. statements is true. ~p would be : A week does not have seven days, 2. which is false. q is false since there are 24 hours in SOLUTION: a day, not 20 hours in a day. -
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. -
New Approaches for Memristive Logic Computations
Portland State University PDXScholar Dissertations and Theses Dissertations and Theses 6-6-2018 New Approaches for Memristive Logic Computations Muayad Jaafar Aljafar Portland State University Let us know how access to this document benefits ouy . Follow this and additional works at: https://pdxscholar.library.pdx.edu/open_access_etds Part of the Electrical and Computer Engineering Commons Recommended Citation Aljafar, Muayad Jaafar, "New Approaches for Memristive Logic Computations" (2018). Dissertations and Theses. Paper 4372. 10.15760/etd.6256 This Dissertation is brought to you for free and open access. It has been accepted for inclusion in Dissertations and Theses by an authorized administrator of PDXScholar. For more information, please contact [email protected]. New Approaches for Memristive Logic Computations by Muayad Jaafar Aljafar A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Electrical and Computer Engineering Dissertation Committee: Marek A. Perkowski, Chair John M. Acken Xiaoyu Song Steven Bleiler Portland State University 2018 © 2018 Muayad Jaafar Aljafar Abstract Over the past five decades, exponential advances in device integration in microelectronics for memory and computation applications have been observed. These advances are closely related to miniaturization in integrated circuit technologies. However, this miniaturization is reaching the physical limit (i.e., the end of Moore’s Law). This miniaturization is also causing a dramatic problem of heat dissipation in integrated circuits. Additionally, approaching the physical limit of semiconductor devices in fabrication process increases the delay of moving data between computing and memory units hence decreasing the performance. The market requirements for faster computers with lower power consumption can be addressed by new emerging technologies such as memristors. -
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. -
Immediate Inference
Immediate Inference Dr Desh Raj Sirswal, Assistant Professor (Philosophy) P.G. Govt. College for Girls, Sector-11, Chandigarh http://drsirswal.webs.com . Inference Inference is the act or process of deriving a conclusion based solely on what one already knows. Inference has two types: Deductive Inference and Inductive Inference. They are deductive, when we move from the general to the particular and inductive where the conclusion is wider in extent than the premises. Immediate Inference Deductive inference may be further classified as (i) Immediate Inference (ii) Mediate Inference. In immediate inference there is one and only one premise and from this sole premise conclusion is drawn. Immediate inference has two types mentioned below: Square of Opposition Eduction Here we will know about Eduction in details. Eduction The second form of Immediate Inference is Eduction. It has three types – Conversion, Obversion and Contraposition. These are not part of the square of opposition. They involve certain changes in their subject and predicate terms. The main concern is to converse logical equivalence. Details are given below: Conversion An inference formed by interchanging the subject and predicate terms of a categorical proposition. Not all conversions are valid. Conversion grounds an immediate inference for both E and I propositions That is, the converse of any E or I proposition is true if and only if the original proposition was true. Thus, in each of the pairs noted as examples either both propositions are true or both are false. Steps for Conversion Reversing the subject and the predicate terms in the premise. Valid Conversions Convertend Converse A: All S is P. -
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. -
Mathematical Logic Part One
Mathematical Logic Part One An Important Question How do we formalize the logic we've been using in our proofs? Where We're Going ● Propositional Logic (Today) ● Basic logical connectives. ● Truth tables. ● Logical equivalences. ● First-Order Logic (Today/Friday) ● Reasoning about properties of multiple objects. Propositional Logic A proposition is a statement that is, by itself, either true or false. Some Sample Propositions ● Puppies are cuter than kittens. ● Kittens are cuter than puppies. ● Usain Bolt can outrun everyone in this room. ● CS103 is useful for cocktail parties. ● This is the last entry on this list. More Propositions ● I came in like a wrecking ball. ● I am a champion. ● You're going to hear me roar. ● We all just entertainers. Things That Aren't Propositions CommandsCommands cannotcannot bebe truetrue oror false.false. Things That Aren't Propositions QuestionsQuestions cannotcannot bebe truetrue oror false.false. Things That Aren't Propositions TheThe firstfirst halfhalf isis aa validvalid proposition.proposition. I am the walrus, goo goo g'joob JibberishJibberish cannotcannot bebe truetrue oror false. false. Propositional Logic ● Propositional logic is a mathematical system for reasoning about propositions and how they relate to one another. ● Every statement in propositional logic consists of propositional variables combined via logical connectives. ● Each variable represents some proposition, such as “You liked it” or “You should have put a ring on it.” ● Connectives encode how propositions are related, such as “If you liked it, then you should have put a ring on it.” Propositional Variables ● Each proposition will be represented by a propositional variable. ● Propositional variables are usually represented as lower-case letters, such as p, q, r, s, etc. -
Introduction to Logic CIS008-2 Logic and Foundations of Mathematics
Introduction to Logic CIS008-2 Logic and Foundations of Mathematics David Goodwin [email protected] 11:00, Tuesday 15th Novemeber 2011 Outline 1 Propositions 2 Conditional Propositions 3 Logical Equivalence Propositions Conditional Propositions Logical Equivalence The Wire \If you play with dirt you get dirty." Propositions Conditional Propositions Logical Equivalence True or False? 1 The only positive integers that divide 7 are 1 and 7 itself. 2 For every positive integer n, there is a prime number larger than n. 3 x + 4 = 6. 4 Write a pseudo-code to solve a linear diophantine equation. Propositions Conditional Propositions Logical Equivalence True or False? 1 The only positive integers that divide 7 are 1 and 7 itself. True. 2 For every positive integer n, there is a prime number larger than n. True 3 x + 4 = 6. The truth depends on the value of x. 4 Write a pseudo-code to solve a linear diophantine equation. Neither true or false. Propositions Conditional Propositions Logical Equivalence Propositions A sentence that is either true or false, but not both, is called a proposition. The following two are propositions 1 The only positive integers that divide 7 are 1 and 7 itself. True. 2 For every positive integer n, there is a prime number larger than n. True whereas the following are not propositions 3 x + 4 = 6. The truth depends on the value of x. 4 Write a pseudo-code to solve a linear diophantine equation. Neither true or false. Propositions Conditional Propositions Logical Equivalence Notation We will use the notation p : 2 + 2 = 5 to define p to be the proposition 2 + 2 = 5. -
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).