1 the Foundations: Logic and Proofs
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Section 2.1: Proof Techniques
Section 2.1: Proof Techniques January 25, 2021 Abstract Sometimes we see patterns in nature and wonder if they hold in general: in such situations we are demonstrating the appli- cation of inductive reasoning to propose a conjecture, which may become a theorem which we attempt to prove via deduc- tive reasoning. From our work in Chapter 1, we conceive of a theorem as an argument of the form P → Q, whose validity we seek to demonstrate. Example: A student was doing a proof and suddenly specu- lated “Couldn’t we just say (A → (B → C)) ∧ B → (A → C)?” Can she? It’s a theorem – either we prove it, or we provide a counterexample. This section outlines a variety of proof techniques, including direct proofs, proofs by contraposition, proofs by contradiction, proofs by exhaustion, and proofs by dumb luck or genius! You have already seen each of these in Chapter 1 (with the exception of “dumb luck or genius”, perhaps). 1 Theorems and Informal Proofs The theorem-forming process is one in which we • make observations about nature, about a system under study, etc.; • discover patterns which appear to hold in general; • state the rule; and then • attempt to prove it (or disprove it). This process is formalized in the following definitions: • inductive reasoning - drawing a conclusion based on experi- ence, which one might state as a conjecture or theorem; but al- mostalwaysas If(hypotheses)then(conclusion). • deductive reasoning - application of a logic system to investi- gate a proposed conclusion based on hypotheses (hence proving, disproving, or, failing either, holding in limbo the conclusion). -
Automated Unbounded Verification of Stateful Cryptographic Protocols
Automated Unbounded Verification of Stateful Cryptographic Protocols with Exclusive OR Jannik Dreier Lucca Hirschi Sasaˇ Radomirovic´ Ralf Sasse Universite´ de Lorraine Department of School of Department of CNRS, Inria, LORIA Computer Science Science and Engineering Computer Science F-54000 Nancy ETH Zurich University of Dundee ETH Zurich France Switzerland UK Switzerland [email protected] [email protected] [email protected] [email protected] Abstract—Exclusive-or (XOR) operations are common in cryp- on widening the scope of automated protocol verification tographic protocols, in particular in RFID protocols and elec- by extending the class of properties that can be verified to tronic payment protocols. Although there are numerous appli- include, e.g., equivalence properties [19], [24], [27], [51], cations, due to the inherent complexity of faithful models of XOR, there is only limited tool support for the verification of [14], extending the adversary model with complex forms of cryptographic protocols using XOR. compromise [13], or extending the expressiveness of protocols, The TAMARIN prover is a state-of-the-art verification tool e.g., by allowing different sessions to update a global, mutable for cryptographic protocols in the symbolic model. In this state [6], [43]. paper, we improve the underlying theory and the tool to deal with an equational theory modeling XOR operations. The XOR Perhaps most significant is the support for user-specified theory can be freely combined with all equational theories equational theories allowing for the modeling of particular previously supported, including user-defined equational theories. cryptographic primitives [21], [37], [48], [24], [35]. -
'The Denial of Bivalence Is Absurd'1
On ‘The Denial of Bivalence is Absurd’1 Francis Jeffry Pelletier Robert J. Stainton University of Alberta Carleton University Edmonton, Alberta, Canada Ottawa, Ontario, Canada [email protected] [email protected] Abstract: Timothy Williamson, in various places, has put forward an argument that is supposed to show that denying bivalence is absurd. This paper is an examination of the logical force of this argument, which is found wanting. I. Introduction Let us being with a word about what our topic is not. There is a familiar kind of argument for an epistemic view of vagueness in which one claims that denying bivalence introduces logical puzzles and complications that are not easily overcome. One then points out that, by ‘going epistemic’, one can preserve bivalence – and thus evade the complications. James Cargile presented an early version of this kind of argument [Cargile 1969], and Tim Williamson seemingly makes a similar point in his paper ‘Vagueness and Ignorance’ [Williamson 1992] when he says that ‘classical logic and semantics are vastly superior to…alternatives in simplicity, power, past success, and integration with theories in other domains’, and contends that this provides some grounds for not treating vagueness in this way.2 Obviously an argument of this kind invites a rejoinder about the puzzles and complications that the epistemic view introduces. Here are two quick examples. First, postulating, as the epistemicist does, linguistic facts no speaker of the language could possibly know, and which have no causal link to actual or possible speech behavior, is accompanied by a litany of disadvantages – as the reader can imagine. -
Three Ways of Being Non-Material
Three Ways of Being Non-Material Vincenzo Crupi, Andrea Iacona May 2019 This paper presents a novel unified account of three distinct non-material inter- pretations of `if then': the suppositional interpretation, the evidential interpre- tation, and the strict interpretation. We will spell out and compare these three interpretations within a single formal framework which rests on fairly uncontro- versial assumptions, in that it requires nothing but propositional logic and the probability calculus. As we will show, each of the three intrerpretations exhibits specific logical features that deserve separate consideration. In particular, the evidential interpretation as we understand it | a precise and well defined ver- sion of it which has never been explored before | significantly differs both from the suppositional interpretation and from the strict interpretation. 1 Preliminaries Although it is widely taken for granted that indicative conditionals as they are used in ordinary language do not behave as material conditionals, there is little agreement on the nature and the extent of such deviation. Different theories tend to privilege different intuitions about conditionals, and there is no obvious answer to the question of which of them is the correct theory. In this paper, we will compare three interpretations of `if then': the suppositional interpretation, the evidential interpretation, and the strict interpretation. These interpretations may be regarded either as three distinct meanings that ordinary speakers attach to `if then', or as three ways of explicating a single indeterminate meaning by replacing it with a precise and well defined counterpart. Here is a rough and informal characterization of the three interpretations. According to the suppositional interpretation, a conditional is acceptable when its consequent is credible enough given its antecedent. -
CS 50010 Module 1
CS 50010 Module 1 Ben Harsha Apr 12, 2017 Course details ● Course is split into 2 modules ○ Module 1 (this one): Covers basic data structures and algorithms, along with math review. ○ Module 2: Probability, Statistics, Crypto ● Goal for module 1: Review basics needed for CS and specifically Information Security ○ Review topics you may not have seen in awhile ○ Cover relevant topics you may not have seen before IMPORTANT This course cannot be used on a plan of study except for the IS Professional Masters program Administrative details ● Office: HAAS G60 ● Office Hours: 1:00-2:00pm in my office ○ Can also email for an appointment, I’ll be in there often ● Course website ○ cs.purdue.edu/homes/bharsha/cs50010.html ○ Contains syllabus, homeworks, and projects Grading ● Module 1 and module are each 50% of the grade for CS 50010 ● Module 1 ○ 55% final ○ 20% projects ○ 20% assignments ○ 5% participation Boolean Logic ● Variables/Symbols: Can only be used to represent 1 or 0 ● Operations: ○ Negation ○ Conjunction (AND) ○ Disjunction (OR) ○ Exclusive or (XOR) ○ Implication ○ Double Implication ● Truth Tables: Can be defined for all of these functions Operations ● Negation (¬p, p, pC, not p) - inverts the symbol. 1 becomes 0, 0 becomes 1 ● Conjunction (p ∧ q, p && q, p and q) - true when both p and q are true. False otherwise ● Disjunction (p v q, p || q, p or q) - True if at least one of p or q is true ● Exclusive Or (p xor q, p ⊻ q, p ⊕ q) - True if exactly one of p or q is true ● Implication (p → q) - True if p is false or q is true (q v ¬p) ● -
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. -
Conundrums of Conditionals in Contraposition
Dale Jacquette CONUNDRUMS OF CONDITIONALS IN CONTRAPOSITION A previously unnoticed metalogical paradox about contrapo- sition is formulated in the informal metalanguage of propositional logic, where it exploits a reflexive self-non-application of the truth table definition of the material conditional to achieve semantic di- agonalization. Three versions of the paradox are considered. The main modal formulation takes as its assumption a conditional that articulates the truth table conditions of conditional propo- sitions in stating that if the antecedent of a true conditional is false, then it is possible for its consequent to be true. When this true conditional is contraposed in the conclusion of the inference, it produces the false conditional conclusion that if it is not the case that the consequent of a true conditional can be true, then it is not the case that the antecedent of the conditional is false. 1. The Logic of Conditionals A conditional sentence is the literal contrapositive of another con- ditional if and only if the antecedent of one is the negation of the consequent of the other. The sentence q p is thus ordinarily un- derstood as the literal contrapositive of: p⊃ :q. But the requirement presupposes that the unnegated antecedents⊃ of the conditionals are identical in meaning to the unnegated consequents of their contrapos- itives. The univocity of ‘p’ and ‘q’ in p q and q p can usually be taken for granted within a single context⊃ of: application⊃ : in sym- bolic logic, but in ordinary language the situation is more complicated. To appreciate the difficulties, consider the use of potentially equivo- cal terms in the following conditionals whose reference is specified in particular speech act contexts: (1.1) If the money is in the bank, then the money is safe. -
Least Sensitive (Most Robust) Fuzzy “Exclusive Or” Operations
Need for Fuzzy . A Crisp \Exclusive Or" . Need for the Least . Least Sensitive For t-Norms and t- . Definition of a Fuzzy . (Most Robust) Main Result Interpretation of the . Fuzzy \Exclusive Or" Fuzzy \Exclusive Or" . Operations Home Page Title Page 1 2 Jesus E. Hernandez and Jaime Nava JJ II 1Department of Electrical and J I Computer Engineering 2Department of Computer Science Page1 of 13 University of Texas at El Paso Go Back El Paso, TX 79968 [email protected] Full Screen [email protected] Close Quit Need for Fuzzy . 1. Need for Fuzzy \Exclusive Or" Operations A Crisp \Exclusive Or" . Need for the Least . • One of the main objectives of fuzzy logic is to formalize For t-Norms and t- . commonsense and expert reasoning. Definition of a Fuzzy . • People use logical connectives like \and" and \or". Main Result • Commonsense \or" can mean both \inclusive or" and Interpretation of the . \exclusive or". Fuzzy \Exclusive Or" . Home Page • Example: A vending machine can produce either a coke or a diet coke, but not both. Title Page • In mathematics and computer science, \inclusive or" JJ II is the one most frequently used as a basic operation. J I • Fact: \Exclusive or" is also used in commonsense and Page2 of 13 expert reasoning. Go Back • Thus: There is a practical need for a fuzzy version. Full Screen • Comment: \exclusive or" is actively used in computer Close design and in quantum computing algorithms Quit Need for Fuzzy . 2. A Crisp \Exclusive Or" Operation: A Reminder A Crisp \Exclusive Or" . Need for the Least . -
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. -
Logic, Proofs
CHAPTER 1 Logic, Proofs 1.1. Propositions A proposition is a declarative sentence that is either true or false (but not both). For instance, the following are propositions: “Paris is in France” (true), “London is in Denmark” (false), “2 < 4” (true), “4 = 7 (false)”. However the following are not propositions: “what is your name?” (this is a question), “do your homework” (this is a command), “this sentence is false” (neither true nor false), “x is an even number” (it depends on what x represents), “Socrates” (it is not even a sentence). The truth or falsehood of a proposition is called its truth value. 1.1.1. Connectives, Truth Tables. Connectives are used for making compound propositions. The main ones are the following (p and q represent given propositions): Name Represented Meaning Negation p “not p” Conjunction p¬ q “p and q” Disjunction p ∧ q “p or q (or both)” Exclusive Or p ∨ q “either p or q, but not both” Implication p ⊕ q “if p then q” Biconditional p → q “p if and only if q” ↔ The truth value of a compound proposition depends only on the value of its components. Writing F for “false” and T for “true”, we can summarize the meaning of the connectives in the following way: 6 1.1. PROPOSITIONS 7 p q p p q p q p q p q p q T T ¬F T∧ T∨ ⊕F →T ↔T T F F F T T F F F T T F T T T F F F T F F F T T Note that represents a non-exclusive or, i.e., p q is true when any of p, q is true∨ and also when both are true. -
On the Analysis of Indirect Proofs: Contradiction and Contraposition
On the analysis of indirect proofs: Contradiction and contraposition Nicolas Jourdan & Oleksiy Yevdokimov University of Southern Queensland [email protected] [email protected] roof by contradiction is a very powerful mathematical technique. Indeed, Premarkable results such as the fundamental theorem of arithmetic can be proved by contradiction (e.g., Grossman, 2009, p. 248). This method of proof is also one of the oldest types of proof early Greek mathematicians developed. More than two millennia ago two of the most famous results in mathematics: The irrationality of 2 (Heath, 1921, p. 155), and the infinitude of prime numbers (Euclid, Elements IX, 20) were obtained through reasoning by contradiction. This method of proof was so well established in Greek mathematics that many of Euclid’s theorems and most of Archimedes’ important results were proved by contradiction. In the 17th century, proofs by contradiction became the focus of attention of philosophers and mathematicians, and the status and dignity of this method of proof came into question (Mancosu, 1991, p. 15). The debate centred around the traditional Aristotelian position that only causality could be the base of true scientific knowledge. In particular, according to this traditional position, a mathematical proof must proceed from the cause to the effect. Starting from false assumptions a proof by contradiction could not reveal the cause. As Mancosu (1996, p. 26) writes: “There was thus a consensus on the part of these scholars that proofs by contradiction were inferior to direct Australian Senior Mathematics Journal vol. 30 no. 1 proofs on account of their lack of causality.” More recently, in the 20th century, the intuitionists went further and came to regard proof by contradiction as an invalid method of reasoning. -
Hardware Abstract the Logic Gates References Results Transistors Through the Years Acknowledgements
The Practical Applications of Logic Gates in Computer Science Courses Presenters: Arash Mahmoudian, Ashley Moser Sponsored by Prof. Heda Samimi ABSTRACT THE LOGIC GATES Logic gates are binary operators used to simulate electronic gates for design of circuits virtually before building them with-real components. These gates are used as an instrumental foundation for digital computers; They help the user control a computer or similar device by controlling the decision making for the hardware. A gate takes in OR GATE AND GATE NOT GATE an input, then it produces an algorithm as to how The OR gate is a logic gate with at least two An AND gate is a consists of at least two A NOT gate, also known as an inverter, has to handle the output. This process prevents the inputs and only one output that performs what inputs and one output that performs what is just a single input with rather simple behavior. user from having to include a microprocessor for is known as logical disjunction, meaning that known as logical conjunction, meaning that A NOT gate performs what is known as logical negation, which means that if its input is true, decision this making. Six of the logic gates used the output of this gate is true when any of its the output of this gate is false if one or more of inputs are true. If all the inputs are false, the an AND gate's inputs are false. Otherwise, if then the output will be false. Likewise, are: the OR gate, AND gate, NOT gate, XOR gate, output of the gate will also be false.