Logic Chapter 10
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Lecture 1: Informal Logic
Lecture 1: Informal Logic 1 Sentential/Propositional Logic Definition 1.1 (Statement). A statement is anything we can say, write, or otherwise express that can be either true or false. Remark 1. Veracity of a statement doesn't depend on one's ability to verify it's truth or falsity. Example 1.2. The expression \Venkatesh is twenty years old" is a statement, because it is either true or false. We will be making following two assumptions when dealing with statements. Assumptions 1.3 (Bivalence). Every statement is either true or false. Assumptions 1.4. No statement is both true and false. One of the consequences of the bivalence assumption is that if a statement is not true, then it must be false. Hence, to prove that something is true, it would suffice to prove that it is not false. 1.1 Combination of Statements In this subsection, we would look at five basic ways of combining two statements P and Q to form new statements. We can form more complicated compound statements by using combinations of these basic operations. Definition 1.5 (Conjunction). We define conjunction of statements P and Q to be the statement that is true if both P and Q are true, and is false otherwise. Conjunction of of P and Q is denoted P ^ Q, and read \P and Q." Remark 2. Logical and is different from it's colloquial usages for therefore or for relations. 1 Definition 1.6 (Disjunction). We define disjunction of statements P and Q to be the statement that is true if either P is true or Q is true or both are true, and is false otherwise. -
Section 1.4: Predicate Logic
Section 1.4: Predicate Logic January 22, 2021 Abstract We now consider the logic associated with predicate wffs, including a new set of derivation rules for demonstrating validity (the analogue of tautology in the propositional calculus) – that is, for proving theorems! 1 Derivation rules • First of all, all the rules of propositional logic still hold. Whew! Propositional wffs are simply boring, variable-less predicate wffs. • Our author suggests the following “general plan of attack”: – strip off the quantifiers – work with the separate wffs – insert quantifiers as necessary Now, how may we legitimately do so? Consider the classic syllo- gism: a. (All) Humans are mortal. b. Socrates is human. Therefore Socrates is mortal. The way we reason is that the rule “Humans are mortal” applies to the specific example “Socrates”; hence this Socrates is mortal. We might write this as a. (∀x)(H(x) → M(x)) b. H(s) Therefore M(s). It seems so obvious! But how do we justify that in a proof se- quence? • New rules for predicate logic: in the following, you should un- derstand by the symbol x in P (x) an expression with free variable x, possibly containing other (quantified) variables: e.g. P (x) ≡ (∀y)(∃z)Q(x,y,z) (1) – Universal Instantiation: from (∀x)P (x) deduce P (t). Caveat: t must not already appear as a variable in the ex- pression for P (x): in the equation above, (1), it would not do to deduce P (y) or P (z), as those variables appear in the expression (in a quantified fashion) already. -
1 Lecture 13: Quantifier Laws1 1. Laws of Quantifier Negation There
Ling 409 lecture notes, Lecture 13 Ling 409 lecture notes, Lecture 13 October 19, 2005 October 19, 2005 Lecture 13: Quantifier Laws1 true or there is at least one individual that makes φ(x) true (or both). Those are also equivalent statements. 1. Laws of Quantifier Negation Laws 2 and 3 suggest a fundamental connection between universal quantification and There are a number of equivalences based on the set-theoretic semantics of predicate logic. conjunction and existential quantification and disjunction: Take for instance a statement of the form (∃x)~ φ(x)2. It asserts that there is at least one individual d which makes ~φ(x) true. That means that d makes ϕ(x) false. That, in turn, (∀x) ψ(x) is true iff ψ(a) and ψ(b) and ψ(c) … (where a, b, c … are the names of the means that (∀x) φ(x) is false, which means that ~(∀x) φ(x) is true. The same reasoning individuals in the domain.) can be applied in the reverse direction and the result is the first quantifier law: ∃ ψ ψ ψ ψ ( x) (x) is true iff (a) or (b) or c) … (where a, b, c … are the names of the (1) Laws of Quantifier Negation individuals in the domain.) Law 1: ~(∀x) φ(x) ⇐⇒ (∃x)~ φ(x) From that point of view, Law 1 resembles a generalized DeMorgan’s Law: (Possible English correspondents: Not everyone passed the test and Someone did not pass (4) ~(ϕ(a) & ϕ(b) & ϕ(c) … ) ⇐⇒ ~ϕ(a) v ~ϕ(b) v ϕ(c) … the test.) (5) Law 4: (∀x) ψ(x) v (∀x)φ(x) ⇒ (∀x)( ψ(x) v φ(x)) ϕ ⇐ ϕ Because of the Law of Double Negation (~~ (x) ⇒ (x)), Law 1 could also be written (6) Law 5: (∃x)( ψ(x) & φ(x)) ⇒ (∃x) ψ(x) & (∃x)φ(x) as follows: These two laws are one-way entailments, NOT equivalences. -
The Incorrect Usage of Propositional Logic in Game Theory
The Incorrect Usage of Propositional Logic in Game Theory: The Case of Disproving Oneself Holger I. MEINHARDT ∗ August 13, 2018 Recently, we had to realize that more and more game theoretical articles have been pub- lished in peer-reviewed journals with severe logical deficiencies. In particular, we observed that the indirect proof was not applied correctly. These authors confuse between statements of propositional logic. They apply an indirect proof while assuming a prerequisite in order to get a contradiction. For instance, to find out that “if A then B” is valid, they suppose that the assumptions “A and not B” are valid to derive a contradiction in order to deduce “if A then B”. Hence, they want to establish the equivalent proposition “A∧ not B implies A ∧ notA” to conclude that “if A then B”is valid. In fact, they prove that a truth implies a falsehood, which is a wrong statement. As a consequence, “if A then B” is invalid, disproving their own results. We present and discuss some selected cases from the literature with severe logical flaws, invalidating the articles. Keywords: Transferable Utility Game, Solution Concepts, Axiomatization, Propositional Logic, Material Implication, Circular Reasoning (circulus in probando), Indirect Proof, Proof by Contradiction, Proof by Contraposition, Cooperative Oligopoly Games 2010 Mathematics Subject Classifications: 03B05, 91A12, 91B24 JEL Classifications: C71 arXiv:1509.05883v1 [cs.GT] 19 Sep 2015 ∗Holger I. Meinhardt, Institute of Operations Research, Karlsruhe Institute of Technology (KIT), Englerstr. 11, Building: 11.40, D-76128 Karlsruhe. E-mail: [email protected] The Incorrect Usage of Propositional Logic in Game Theory 1 INTRODUCTION During the last decades, game theory has encountered a great success while becoming the major analysis tool for studying conflicts and cooperation among rational decision makers. -
Lexical Scoping As Universal Quantification
University of Pennsylvania ScholarlyCommons Technical Reports (CIS) Department of Computer & Information Science March 1989 Lexical Scoping as Universal Quantification Dale Miller University of Pennsylvania Follow this and additional works at: https://repository.upenn.edu/cis_reports Recommended Citation Dale Miller, "Lexical Scoping as Universal Quantification", . March 1989. University of Pennsylvania Department of Computer and Information Science Technical Report No. MS-CIS-89-23. This paper is posted at ScholarlyCommons. https://repository.upenn.edu/cis_reports/785 For more information, please contact [email protected]. Lexical Scoping as Universal Quantification Abstract A universally quantified goal can be interpreted intensionally, that is, the goal ∀x.G(x) succeeds if for some new constant c, the goal G(c) succeeds. The constant c is, in a sense, given a scope: it is introduced to solve this goal and is "discharged" after the goal succeeds or fails. This interpretation is similar to the interpretation of implicational goals: the goal D ⊃ G should succeed if when D is assumed, the goal G succeeds. The assumption D is discharged after G succeeds or fails. An interpreter for a logic programming language containing both universal quantifiers and implications in goals and the body of clauses is described. In its non-deterministic form, this interpreter is sound and complete for intuitionistic logic. Universal quantification can provide lexical scoping of individual, function, and predicate constants. Several examples are presented to show how such scoping can be used to provide a Prolog-like language with facilities for local definition of programs, local declarations in modules, abstract data types, and encapsulation of state. -
46. on the Completeness O F the Leibnizian Modal System with a Restriction by Setsuo SAITO Shibaura Institute of Technology,Tokyo (Comm
198 [Vol. 42, 46. On the Completeness o f the Leibnizian Modal System with a Restriction By Setsuo SAITO Shibaura Institute of Technology,Tokyo (Comm. by Zyoiti SUETUNA,M.J.A., March 12, 1966) § 1. Introduction. The purpose of this paper is to show the completeness of a modal system which will be called Lo in the following. In my previous paper [1], in order to show an example of defence of _.circular definition, the following definition was given: A statement is analytic if and only if it is consistent with every statement that expresses what is possible. This definition, roughly speaking, is materially equivalent to Carnap's definition of L-truth which is suggested by Leibniz' conception that a necessary truth must hold in all possible worlds (cf. Carnap [2], p.10). If "analytic" is replaced by "necessary" in the above definition, this definition becomes as follows: A statement is necessary if and only if it is consistent with every statement that expresses what is possible. This reformed definition is symbolized by modal signs as follows: Opm(q)[Qq~O(p•q)1, where p and q are propositional variables. Let us replace it by the following axiom-schema and rule: Axiom-schema. D a [Q,9 Q(a •,S)], where a, ,9 are arbitrary formulas. Rule of inference. If H Q p Q(a •p), then i- a, where a is an arbitrary formula and p is a propositional variable not contained in a. We call L (the Leibnizian modal system) the system obtained from the usual propositional calculus by adding the above axiom schema and rule and the rule of replacement of material equivalents. -
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. -
Logic and Proof
CS2209A 2017 Applied Logic for Computer Science Lecture 11, 12 Logic and Proof Instructor: Yu Zhen Xie 1 Proofs • What is a theorem? – Lemma, claim, etc • What is a proof? – Where do we start? – Where do we stop? – What steps do we take? – How much detail is needed? 2 The truth 3 Theories and theorems • Theory: axioms + everything derived from them using rules of inference – Euclidean geometry, set theory, theory of reals, theory of integers, Boolean algebra… – In verification: theory of arrays. • Theorem: a true statement in a theory – Proved from axioms (usually, from already proven theorems) Pythagorean theorem • A statement can be a theorem in one theory and false in another! – Between any two numbers there is another number. • A theorem for real numbers. False for integers! 4 Axioms example: Euclid’s postulates I. Through 2 points a line segment can be drawn II. A line segment can be extended to a straight line indefinitely III. Given a line segment, a circle can be drawn with it as a radius and one endpoint as a centre IV. All right angles are congruent V. Parallel postulate 5 Some axioms for propositional logic • For any formulas A, B, C: – A ∨ ¬ – . – . – A • Also, like in arithmetic (with as +, as *) – , – Same holds for ∧. – Also, • And unlike arithmetic – ( ) 6 Counterexamples • To disprove a statement, enough to give a counterexample: a scenario where it is false – To disprove that • Take = ", = #, • Then is false, but B is true. – To disprove that if %& '( ) &, ( , then '( %& ) &, ( , • Set the domain of x and y to be {0,1} • Set P(0,0) and P(1,1) to true, and P(0,1), P(1,0) to false. -
CS 205 Sections 07 and 08 Supplementary Notes on Proof Matthew Stone March 1, 2004 [email protected]
CS 205 Sections 07 and 08 Supplementary Notes on Proof Matthew Stone March 1, 2004 [email protected] 1 Propositional Natural Deduction The proof systems that we have been studying in class are called natural deduction. This is because they permit the same lines of reasoning and the same form of argument that you see in ordinary mathematics. Students generally find it easier to represent their mathematical ideas in natural deduction than in other ways of doing proofs. In these systems the proof is a sequence of lines. Each line has a number, a formula, and a justification that explains why the formula can be introduced into the proof. The simplest kind of justification is that the formula is a premise, and the argument depends on it. Another common justification is modus ponens, which derives the consequent of a conditional in the proof whose antecedent is also part of the proof. Here is a simple proof with these two rules used together. Example 1 1P! QPremise 2Q! RPremise 3P Premise 4 Q Modus ponens 1,3 5 R Modus ponens 2,4 This proof assumes that P is true, that P ! Q,andthatQ ! R. It uses modus ponens to conclude that R must then be true. Some inference rules in natural deduction allow assumptions to be made for the purposes of argument. These inference rules create a subproof. A subproof begins with a new assumption. This assumption can be used just within this subproof. In addition, all the assumption made in outer proofs can be used in the subproof. -
CHAPTER 1 the Main Subject of Mathematical Logic Is Mathematical
CHAPTER 1 Logic The main subject of Mathematical Logic is mathematical proof. In this chapter we deal with the basics of formalizing such proofs and analysing their structure. The system we pick for the representation of proofs is natu- ral deduction as in Gentzen (1935). Our reasons for this choice are twofold. First, as the name says this is a natural notion of formal proof, which means that the way proofs are represented corresponds very much to the way a careful mathematician writing out all details of an argument would go any- way. Second, formal proofs in natural deduction are closely related (via the Curry-Howard correspondence) to terms in typed lambda calculus. This provides us not only with a compact notation for logical derivations (which otherwise tend to become somewhat unmanageable tree-like structures), but also opens up a route to applying the computational techniques which un- derpin lambda calculus. An essential point for Mathematical Logic is to fix the formal language to be used. We take implication ! and the universal quantifier 8 as basic. Then the logic rules correspond precisely to lambda calculus. The additional connectives (i.e., the existential quantifier 9, disjunction _ and conjunction ^) will be added via axioms. Later we will see that these axioms are deter- mined by particular inductive definitions. In addition to the use of inductive definitions as a unifying concept, another reason for that change of empha- sis will be that it fits more readily with the more computational viewpoint adopted there. This chapter does not simply introduce basic proof theory, but in addi- tion there is an underlying theme: to bring out the constructive content of logic, particularly in regard to the relationship between minimal and classical logic. -
Chapter 10: Symbolic Trails and Formal Proofs of Validity, Part 2
Essential Logic Ronald C. Pine CHAPTER 10: SYMBOLIC TRAILS AND FORMAL PROOFS OF VALIDITY, PART 2 Introduction In the previous chapter there were many frustrating signs that something was wrong with our formal proof method that relied on only nine elementary rules of validity. Very simple, intuitive valid arguments could not be shown to be valid. For instance, the following intuitively valid arguments cannot be shown to be valid using only the nine rules. Somalia and Iran are both foreign policy risks. Therefore, Iran is a foreign policy risk. S I / I Either Obama or McCain was President of the United States in 2009.1 McCain was not President in 2010. So, Obama was President of the United States in 2010. (O v C) ~(O C) ~C / O If the computer networking system works, then Johnson and Kaneshiro will both be connected to the home office. Therefore, if the networking system works, Johnson will be connected to the home office. N (J K) / N J Either the Start II treaty is ratified or this landmark treaty will not be worth the paper it is written on. Therefore, if the Start II treaty is not ratified, this landmark treaty will not be worth the paper it is written on. R v ~W / ~R ~W 1 This or statement is obviously exclusive, so note the translation. 427 If the light is on, then the light switch must be on. So, if the light switch in not on, then the light is not on. L S / ~S ~L Thus, the nine elementary rules of validity covered in the previous chapter must be only part of a complete system for constructing formal proofs of validity. -
Philosophy 109, Modern Logic Russell Marcus
Philosophy 240: Symbolic Logic Hamilton College Fall 2014 Russell Marcus Reference Sheeet for What Follows Names of Languages PL: Propositional Logic M: Monadic (First-Order) Predicate Logic F: Full (First-Order) Predicate Logic FF: Full (First-Order) Predicate Logic with functors S: Second-Order Predicate Logic Basic Truth Tables - á á @ â á w â á e â á / â 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 0 0 1 1 0 1 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 Rules of Inference Modus Ponens (MP) Conjunction (Conj) á e â á á / â â / á A â Modus Tollens (MT) Addition (Add) á e â á / á w â -â / -á Simplification (Simp) Disjunctive Syllogism (DS) á A â / á á w â -á / â Constructive Dilemma (CD) (á e â) Hypothetical Syllogism (HS) (ã e ä) á e â á w ã / â w ä â e ã / á e ã Philosophy 240: Symbolic Logic, Prof. Marcus; Reference Sheet for What Follows, page 2 Rules of Equivalence DeMorgan’s Laws (DM) Contraposition (Cont) -(á A â) W -á w -â á e â W -â e -á -(á w â) W -á A -â Material Implication (Impl) Association (Assoc) á e â W -á w â á w (â w ã) W (á w â) w ã á A (â A ã) W (á A â) A ã Material Equivalence (Equiv) á / â W (á e â) A (â e á) Distribution (Dist) á / â W (á A â) w (-á A -â) á A (â w ã) W (á A â) w (á A ã) á w (â A ã) W (á w â) A (á w ã) Exportation (Exp) á e (â e ã) W (á A â) e ã Commutativity (Com) á w â W â w á Tautology (Taut) á A â W â A á á W á A á á W á w á Double Negation (DN) á W --á Six Derived Rules for the Biconditional Rules of Inference Rules of Equivalence Biconditional Modus Ponens (BMP) Biconditional DeMorgan’s Law (BDM) á / â -(á / â) W -á / â á / â Biconditional Modus Tollens (BMT) Biconditional Commutativity (BCom) á / â á / â W â / á -á / -â Biconditional Hypothetical Syllogism (BHS) Biconditional Contraposition (BCont) á / â á / â W -á / -â â / ã / á / ã Philosophy 240: Symbolic Logic, Prof.