1-3 Predicates and Quantifiers

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1.4 Nested Quantifiers

1.4 Nested Quantifiers

Translating Sentences into Logical Expressions
Example 13:
Use quantifiers to express the statement “There is a woman who has taken a flight on every airline in the world.” Let P(w,f) be “w has taken f” and Q(f,a) be “f is a flight on a.” ∃w∀a∃f(P(w,f) ∧Q(f,a)) where the universes of discourse for w,f and a consist of all the women in the world, all airplane flights, and all airlines, respectively. ∃w∀a∃f R(w,f,a) where R(w,f,a) is “w has taken f on a.”
Translating Statements Involving Nested Quantifiers
Example 9:
Translate the statement ∀ ∀x(C(x)∨∃y(C(y)∧F(x,y))) ∃ Into English, where C(x) is “x has a computer,” F(x,y) is “x and y are friends,” and the universe of discourse for both x and y consists of all students in your school. The statement says that for every student x in your school x has a computer or there is a student y such that y has a computer and x and y are friends.

一阶语言逻辑符号

一阶语言逻辑符号

一阶语言逻辑符号
一阶语言逻辑(First-Order Language)也称为一阶谓词逻辑(First-Order Predicate Logic),它是一种用于形式化推理和表达数学、哲学等领域中的语言。

一阶语言逻辑使用了一些基本的符号来表示逻辑关系和量词。

以下是一阶语言逻辑中常见的符号:
1. 常量符号(Constants):用小写字母表示,如a, b, c等,表示特定的个体或对象。

2. 变量符号(Variables):用小写字母或字母组合表示,如x, y, z等,表示任意个体或对象。

3. 谓词符号(Predicates):用大写字母或字母组合表示,如P, Q, R等,表示关系或性质。

4. 逻辑连接词(Logical Connectives):包括否定(¬)、合取(∧)、析取(∨)、蕴含(→)和双向蕴含(↔),用于构建复杂的逻辑表达式。

5. 量词符号(Quantifiers):包括全称量词(∀)和存在量词(∃),用于描述对象集合的范围。

6. 等于符号(Equality):用"="表示,表示两个个体相等。

7. 括号(Parentheses):用于分组和界定逻辑表达式的优先级。

以上是一阶语言逻辑中常见的符号,它们可以通过组合使用来构建复杂的逻辑表达式,用于描述关系、性质、量化等概念。

1。

离散数学 Predicates and Quantifiers(期望与量词)共31页

离散数学 Predicates and Quantifiers(期望与量词)共31页

-----predicate logic: predicate, quantifiers
2020/1/7
the Foundations:Logic and Proof Guo Jian
1
1.predicate (1) Consider the statement
“x is greater than 3”.
P(x) is also said to be the value of propositional function P at x.
2020/1/7
the Foundations:Logic and Proof Guo-----”x is greater than 3”, propositional function P(4)---------proposition ,true P(2)--------proposition, false
logic that deals with predicate and quantifiers.
2020/1/7
the Foundations:Logic and Proof Guo Jian
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2. Universal Quantifier
(1) domain (or Universe of Discourse )个体域 -----a set containing all the values of a variable
(3)Example2(p31) A(x)---”Computer x is under attack by an
intruder.” CS2, MATH1 are under attack. A(CS1)----false A(CS2)----true A(MATH1)----true (4) Statements can involve more than 1 variable. Example 3 (page 31): Q(x,y)--------”x=y+3” Q(1,2)--------false Q(3,0)--------true

离散数学 Predicates and Quantifiers(期望与量词)

离散数学 Predicates and Quantifiers(期望与量词)
P(x) is also said to be the value of propositional function P at x.
2019/8/21
the Foundations:Logic and Proof Guo Jian
2
(3) P(x)--------”x is greater than 3”, propositional function P(4)---------proposition ,true P(2)--------proposition, false
2019/8/21
the Foundations:Logic and Proof Guo Jian
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(3) Example 8(page 34) P(x)-----”x+1>x” the domain-----all real numbers How about ∀x P(x) ? Answer: ∀x P(x) ------true (4) Example 9 (page 35) Q(x)--------”x<2”
the domain-----all real numbers
How about ∀x Q(x) ? Answer: ∀x Q(x) ------false
2019/8/21
the Foundations:Logic and Proof Guo Jian
7
(5)Example 10 Let P(x) be “x2>0”. the domain ----- integers Show ∀x P(x) is false
logic that deals with predicate and quantifiers.

中山大学计算机学院离散数学基础教学大纲(2019)

中山大学计算机学院离散数学基础教学大纲(2019)

中山大学本科教学大纲Undergraduate Course Syllabus学院(系):数据科学与计算机学院School (Department):School of Data and Computer Science课程名称:离散数学基础Course Title:Discrete Mathematics二〇二〇年离散数学教学大纲Course Syllabus: Discreate Mathematics(编写日期:2020 年12 月)(Date: 19/12/2020)一、课程基本说明I. Basic Information二、课程基本内容 II. Course Content(一)课程内容i. Course Content1、逻辑与证明(22学时) Logic and Proofs (22 hours)1.1 命题逻辑的语法和语义(4学时) Propositional Logic (4 hours)命题的概念、命题逻辑联结词和复合命题,命题的真值表和命题运算的优先级,自然语言命题的符号化Propositional Logic, logic operators (negation, conjunction, disjunction, implication, bicondition), compound propositions, truth table, translating sentences into logic expressions1.2 命题公式等值演算(2学时) Logical Equivalences (2 hours)命题之间的关系、逻辑等值和逻辑蕴含,基本等值式,等值演算Logical equivalence, basic laws of logical equivalences, constructing new logical equivalences1.3 命题逻辑的推理理论(2学时)论断模式,论断的有效性及其证明,推理规则,命题逻辑中的基本推理规则(假言推理、假言易位、假言三段论、析取三段论、附加律、化简律、合取律),构造推理有效性的形式证明方法Argument forms, validity of arguments, inference rules, formal proofs1.4 谓词逻辑的语法和语义 (4学时) Predicates and Quantifiers (4 hours)命题逻辑的局限,个体与谓词、量词、全程量词与存在量词,自由变量与约束变量,谓词公式的真值,带量词的自然语言命题的符号化Limitations of propositional logic, individuals and predicates, quantifiers, the universal quantification and conjunction, the existential quantification and disjunction, free variables and bound variables, logic equivalences involving quantifiers, translating sentences into quantified expressions.1.4 谓词公式等值演算(2学时) Nested Quantifiers (2 hours)谓词公式之间的逻辑蕴含与逻辑等值,带嵌套量词的自然语言命题的符号化,嵌套量词与逻辑等值Understanding statements involving nested quantifiers, the order of quantifiers, translating sentences into logical expressions involving nested quantifiers, logical equivalences involving nested quantifiers.1.5谓词逻辑的推理规则和有效推理(4学时) Rules of Inference (4 hours)证明的基本含和证明的形式结构,带量词公式的推理规则(全程量词实例化、全程量词一般化、存在量词实例化、存在量词一般化),证明的构造Arguments, argument forms, validity of arguments, rules of inference for propositional logic (modus ponens, modus tollens, hypothetical syllogism, disjunctive syllogism, addition, simplication, conjunction), using rules of inference to build arguments, rules of inference for quantified statements (universal instantiation, universal generalization, existential instantiation, existential generalization)1.6 数学证明简介(2学时) Introduction to Proofs (2 hours)数学证明的相关术语、直接证明、通过逆反命题证明、反证法、证明中常见的错误Terminology of proofs, direct proofs, proof by contraposition, proof by contradiction, mistakes in proofs1.7 数学证明方法与策略初步(2学时) Proof Methods and Strategy (2 hours)穷举法、分情况证明、存在命题的证明、证明策略(前向与后向推理)Exhaustive proof, proof by cases, existence proofs, proof strategies (forward and backward reasoning)2、集合、函数和关系(18学时)Sets, Functions and Relations(18 hours)2.1 集合及其运算(3学时) Sets (3 hours)集合与元素、集合的表示、集合相等、文氏图、子集、幂集、笛卡尔积Set and its elements, set representations, set identities, Venn diagrams, subsets, power sets, Cartesian products.集合基本运算(并、交、补)、广义并与广义交、集合基本恒等式Unions, intersections, differences, complements, generalized unions and intersections, basic laws for set identities.2.2函数(3学时) Functions (3 hours)函数的定义、域和共域、像和原像、函数相等、单函数与满函数、函数逆与函数复合、函数图像Functions, domains and codomains, images and pre-images, function identity, one-to-one and onto functions, inverse functions and compositions of functions.2.3. 集合的基数(1学时)集合等势、有穷集、无穷集、可数集和不可数集Set equinumerous, finite set, infinite set, countable set, uncountable set.2.4 集合的归纳定义、归纳法和递归(3学时)Inductive sets, inductions and recursions (3 hours)自然数的归纳定义,自然数上的归纳法和递归函数;数学归纳法(第一数学归纳法)及应用举例、强归纳法(第二数学归纳法)及应用举例;集合一般归纳定义模式、结构归纳法和递归函数。

2015离散数学谓词量词、变元的约束、翻译

2015离散数学谓词量词、变元的约束、翻译

(1)
2 是无理数 .
(2) x是有理数. (3) 小王与小李同岁. (4) x 与y具有同学关系.
(1) 凡人都呼吸 . (2) 所有的人都长着黑头发. (3) 兔子比乌龟跑得快. (4) ቤተ መጻሕፍቲ ባይዱ美国留学的学生未必都是亚洲人.
Universal Quantifier
The universal quantification of P(x) is the statement
定义1:约束变元 谓词公式中 , ,后面所跟的 x ,称为相应 量词的指导变元或作用变元或约束变元。 定义2:量词作用域(量词辖域)
给 定 谓 词 公 式 中 , 形 式 为 (x)P(x) , (x) P(x)中的P(x)称为相应量词的作用域(辖域)。
定义3:自由变元 在谓词公式中,除去约束变元以外所出现的 变元,称作自由变元。
with a certain property. Such statements are expressed using existential quantification. With existential quantification, we form a proposition that is true if and only if P(x) is true for at least one value of x in the domain.
Truth value?
We read ∀xP(x) as “for all xP(x)” or “for every xP(x).”An
element for which P(x) is false is called a counterexample of ∀xP(x).

离散数学及其应用英文版第八版课程设计

离散数学及其应用英文版第八版课程设计

Discrete Mathematics and Its Applications, 8th Edition CourseDesignBackgroundDiscrete mathematics is a foundation for many computer science and mathematics-related fields. It deals with objects that can only take distinct values, such as integers, graphs, and propositions. The applications of discrete mathematicsare diverse and important, including cryptography, computer algorithms, and database systems.The book Discrete Mathematics and Its Applications,written by Kenneth H. Rosen, is a widely accepted textbook on the subject. In this course design, we will use the book’s8th edition, which covers a vast range of topics in discrete mathematics.Course DescriptionThe course ms to provide students with a comprehensive understanding of discrete mathematics and its applications. The course will cover major topics in the field, including:1.Propositional logic and predicate logic2.Set theory and relationsbinatorics and discrete probability4.Graph theory5.Trees, spanning trees, and graph traversals6.Boolean algebra and switching circuits7.The theory of computation and formal languages8.Number theory and cryptographySpecial emphasis will be placed on developing problem-solving skills, logical reasoning, and mathematical maturity. Students will learn to apply the tools and techniques learned in this course to real-world problems.Course GoalsUpon completion of this course, students should be able to:1.Understand and apply the fundamental principles ofdiscrete mathematics2.Identify and solve problems involving logic, sets,and relations3.Analyze and solve problems in combinatorics anddiscrete probability4.Understand the properties and applications ofgraphs, trees, and circuits5.Understand the principles and applications of thetheory of computation and formal languages6.Demonstrate knowledge of number theory and itsapplications to cryptographyCourse OutlineThe course will be delivered through lectures, problem-solving sessions, and assignments. The course outline is as follows:Week 1: Propositional Logic and Predicate Logic•Introduction to logic•Propositional logic–Logical connectives and truth tables–Tautologies, contradictions, and logical equivalence–Logical inference and proof techniques •Predicate logic–Predicates and quantifiers–Universal and existential quantifiers–Translating English statements into predicate logicWeek 2: Set Theory and Relations•Introduction to sets and set operations•Relations–Binary relations and their properties–Equivalence relations and partitions–Partial orders and Hasse diagramsWeek 3: Combinatorics and Discrete Probability•Counting principles–The multiplication rule–The addition rule–Permutations and combinations•Discrete probability–Probability spaces and events–Conditional probability and independence–Random variables and their distributions Week 4: Graph Theory•Introduction to graphs and their representations •Basic terminology•Walks, paths, and cycles•Connectivity and components•Directed graphsWeek 5: Trees, Spanning Trees, and Graph Traversals •Trees and their properties•Spanning trees and their properties•Minimum spanning trees and algorithms•Graph traversals–Breadth-first search–Depth-first searchWeek 6: Boolean Algebra and Switching Circuits •Boolean algebra and its operations•Boolean functions and their representations•Canonical forms and minimization•Switching circuits and their designWeek 7: The Theory of Computation and Formal Languages •Introduction to automata theory•Finite automata and regular languages•Regular expressions•Pushdown automata and context-free languages Week 8: Number Theory and Cryptography•Principles of number theory–Divisibility and prime numbers–Modular arithmetic and congruences •Cryptography–Cryptographic algorithms and protocols–Public-key cryptography and RSAAssessmentAssessment will be based on a combination of quizzes, assignments, and exams. The final grade will be determined based on the following:•Quizzes: 20%•Assignments: 40%•Midterm exam: 20%•Final exam: 20%ConclusionThis course design provides a comprehensive overview of the topics covered in the book Discrete Mathematics and Its Applications, 8th edition. The course ms to develop problem-solving skills, logical reasoning, and mathematical maturity. Students will learn to apply discrete mathematics to real-world problems, with a focus on computer science and mathematics-related fields.。

2015离散数学谓词演算与前束范式

2015离散数学谓词演算与前束范式

prenex normal form
Any expression can be converted into prenex normal form. To
do this, the following steps are needed:
1. Eliminate all occurrences of and from the formula in
消去下列公式的量词
设个体域D ={a,b}
a) xF ( x) yG( y) b) xy( F ( x) G( y)) c) xy( F ( x) G( x, y)) d) x( F ( x, y) yG( y))
量词否定等值式
Negation:
¬ ∀xP(x) ∃x ¬ P(x). ¬ ∃xQ(x) ∀x ¬ Q(x).
Predicates and Quantifiers
谓词和量词
将下列命题符号化
(1)兔子比乌龟跑得快 (2)有的兔子比乌龟跑得快 (3)并不是所有的兔子都比乌龟跑得快 (4)不存在跑得同样快的两只兔子
将下列命题符号化
(1)有的汽车比有的火车跑得快 (2)有的火车比所有的汽车跑得快 (3)说所有的火车比所有汽车都跑得快是不对的 (4)说有的飞机比有的汽车慢也是不对的
斯柯伦范式skolem
每个存在量词均在全称量词之前
AI型斯柯伦范式
e) xF ( x) xG( x) f ) xF ( x) xG( x) g) xF ( x) xG( x) L( x, y) h) (xF ( x) xG( x))
Basic Rules about Quantification
US: xP(x)P(c)
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Logo Meaning of Quantified Expressions
∃x P(x) means there exist x in the u.d. (that is, 1 or more) such that P(x) is true. ∃x P(x) is read as “There is an x such that P(x),” “There is at least x such that P(x),” or “For some x P(x) ”
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Logo Example 2
Let Q(x,y) denote the statement “x=y+3.” What are the truth values of the propositions Q(1,2) and Q(3,0)? Q(1,2): “1=2+3” is false Q(3,0): “3=0+3” is True
10
Logo
Quantifiers
11ቤተ መጻሕፍቲ ባይዱ
Logo
Quantifier Expressions Quantifiers provide a notation that allows us to quantify (count) how many objects in the u.d. satisfy a given predicate. “∀” is the FOR ALL or universal quantifier. “∃” is the EXISTS or existential quantifier. For example, ∀x P(x) and ∃x P(x) are propositions
9
Logo Propositional Function
In general, a statement involving the n variables x1, x2,…, xn can be denoted by P(x1, x2,…, xn ). A statement of the form P(x1, x2,…, xn ) is the value of the propositional function P at the n-tuple (x1, x2,…, xn ), and P is also called a predicate.
If it’s cold then it snows. If it snows there are accidents There are no accidents. Therefore: It’s not cold
In propositional logic:
((c→s ∧s→a ∧¬a) →¬c) is a tautology
Let P(x) denote the statement “x > 3.” What is the truth value ∃x P(x), where x is real number. Solution: Since “x > 3” is true, for instance, when x=4. Thus, ∃x P(x) is true.
13
Logo
Example: ∀ Let the u.d. be parking spaces at UF. Let P(x) be the prop. form “x is occupied” Then the universal quantification of P(x), ∀x P(x), is the proposition:
5
Logo Predicate
Statement involving variables, such as “x>3,” “x=y+3,” and “x+y=z” These statement are neither true nor false when the values of the variables are not specified.
8
Logo Example 3
What are the truth values of the propositions R(1,2,3) and R(0,0,1), where R(x,y,z) denotes “x+y=z”? R(1,2,3): “1+2=3” is True.R(0,0,1): “0+0=1” is False. Example 4 P(x): If x>0 then x=x+1.
19
Logo Existential Quantifier
With existential quantification, we form a proposition that is true if and if only for P(x) is true for at least one value of x in the universe of discourse. Definition 2: “There exists an element x in the universe of discourse such that P(x) is true.” ∃ is called existential quantifier.
18
Logo Example 7
What is the truth value of ∀x (x^2>=x) if the universe of discourse consists of all real numbers and what is its truth value if the universe of discourse consists of all integers? Solution: ∀x (x^2>=x) is false if the universe of discourse consists of all real numbers (since it is false for 0<x<1). ∀x (x^2>=x) is true if the universe of discourse consists of all real integers.
12
Logo Universal Quantification
Definition 1: The universal quantification of P(x) is the proposition “P(x) is true for all values of x in the universe or discourse”. universal quantification of x is denoted as ∀x . The proposition ∀x P(x) is read as “for all x P(x) ” or “for every x P(x) ” Universe of Discourse or Domain
“Some parking space(s) at UF is/are full.” “There is a parking space at UF that is full.” “At least one parking space at UF is full.”
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Logo Example 8
“All parking spaces at UF are occupied.”
“For each parking space at UF, that space is full.”
Before proceeding, we need to distinguish between two kinds of variables
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Logo Counterexample
To show that a statement of the form ¬∀x P(x) is a propositional function, we need only find one value of x in the universe of discourse for P(x) is false. Such value of x is called a counterexample to the statement ∀x P(x).
Logo
Discrete Mathematics
Dr. Han Huang
South China University of Technology
1
Logo
Chapter 1. Logic and Proof, Sets, and Function
Section 1.3
2
Logo
Contents
17
Logo Example 6
What dose the statement ∀x T(x) means if T(x) is “x has two parents” and the universe of discourse consists of all people? Solution: The statement ∀x T(x) means “Every person has two parents.” This statement is true (except for clones).
16
Logo Example 5
Let Q(x) be the statement “x<2.” What is the truth value of the quantification ∀x Q(x) where the universe of discourse consists of all real number? Solution: Q(x) is not true for every real number x, since, for stance, Q(3) is false. Thus, ∀x Q(x) is false.
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