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Gibbardian Collapse and Trivalent Conditionals
Gibbardian Collapse and Trivalent Conditionals Paul Égré* Lorenzo Rossi† Jan Sprenger‡ Abstract This paper discusses the scope and significance of the so-called triviality result stated by Allan Gibbard for indicative conditionals, showing that if a conditional operator satisfies the Law of Import-Export, is supraclassical, and is stronger than the material conditional, then it must collapse to the material conditional. Gib- bard’s result is taken to pose a dilemma for a truth-functional account of indicative conditionals: give up Import-Export, or embrace the two-valued analysis. We show that this dilemma can be averted in trivalent logics of the conditional based on Reichenbach and de Finetti’s idea that a conditional with a false antecedent is undefined. Import-Export and truth-functionality hold without triviality in such logics. We unravel some implicit assumptions in Gibbard’s proof, and discuss a recent generalization of Gibbard’s result due to Branden Fitelson. Keywords: indicative conditional; material conditional; logics of conditionals; triva- lent logic; Gibbardian collapse; Import-Export 1 Introduction The Law of Import-Export denotes the principle that a right-nested conditional of the form A → (B → C) is logically equivalent to the simple conditional (A ∧ B) → C where both antecedentsare united by conjunction. The Law holds in classical logic for material implication, and if there is a logic for the indicative conditional of ordinary language, it appears Import-Export ought to be a part of it. For instance, to use an example from (Cooper 1968, 300), the sentences “If Smith attends and Jones attends then a quorum *Institut Jean-Nicod (CNRS/ENS/EHESS), Département de philosophie & Département d’études cog- arXiv:2006.08746v1 [math.LO] 15 Jun 2020 nitives, Ecole normale supérieure, PSL University, 29 rue d’Ulm, 75005, Paris, France. -
Technical Report TR-2020-10
Simulation-Based Engineering Lab University of Wisconsin-Madison Technical Report TR-2020-10 CryptoEmu: An Instruction Set Emulator for Computation Over Ciphers Xiaoyang Gong and Dan Negrut December 28, 2020 Abstract Fully homomorphic encryption (FHE) allows computations over encrypted data. This technique makes privacy-preserving cloud computing a reality. Users can send their encrypted sensitive data to a cloud server, get encrypted results returned and decrypt them, without worrying about data breaches. This project report presents a homomorphic instruction set emulator, CryptoEmu, that enables fully homomorphic computation over encrypted data. The software-based instruction set emulator is built upon an open-source, state-of-the-art homomorphic encryption library that supports gate-level homomorphic evaluation. The instruction set architecture supports multiple instructions that belong to the subset of ARMv8 instruction set architecture. The instruction set emulator utilizes parallel computing techniques to emulate every functional unit for minimum latency. This project re- port includes details on design considerations, instruction set emulator architecture, and datapath and control unit implementation. We evaluated and demonstrated the instruction set emulator's performance and scalability on a 48-core workstation. Cryp- toEmu shown a significant speed up in homomorphic computation performance when compared with HELib, a state-of-the-art homomorphic encryption library. Keywords: Fully Homomorphic Encryption, Parallel Computing, Homomorphic Instruction Set, Homomorphic Processor, Computer Architecture 1 Contents 1 Introduction 3 2 Background 4 3 TFHE Library 5 4 CryptoEmu Architecture Overview 7 4.1 Data Processing . .8 4.2 Branch and Control Flow . .9 5 Data Processing Units 9 5.1 Load/Store Unit . .9 5.2 Adder . -
Glossary for Logic: the Language of Truth
Glossary for Logic: The Language of Truth This glossary contains explanations of key terms used in the course. (These terms appear in bold in the main text at the point at which they are first used.) To make this glossary more easily searchable, the entry headings has ‘::’ (two colons) before it. So, for example, if you want to find the entry for ‘truth-value’ you should search for ‘:: truth-value’. :: Ambiguous, Ambiguity : An expression or sentence is ambiguous if and only if it can express two or more different meanings. In logic, we are interested in ambiguity relating to truth-conditions. Some sentences in natural languages express more than one claim. Read one way, they express a claim which has one set of truth-conditions. Read another way, they express a different claim with different truth-conditions. :: Antecedent : The first clause in a conditional is its antecedent. In ‘(P ➝ Q)’, ‘P’ is the antecedent. In ‘If it is raining, then we’ll get wet’, ‘It is raining’ is the antecedent. (See ‘Conditional’ and ‘Consequent’.) :: Argument : An argument is a set of claims (equivalently, statements or propositions) made up from premises and conclusion. An argument can have any number of premises (from 0 to indefinitely many) but has only one conclusion. (Note: This is a somewhat artificially restrictive definition of ‘argument’, but it will help to keep our discussions sharp and clear.) We can consider any set of claims (with one claim picked out as conclusion) as an argument: arguments will include sets of claims that no-one has actually advanced or put forward. -
UNIT-I Mathematical Logic Statements and Notations
UNIT-I Mathematical Logic Statements and notations: A proposition or statement 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. Connectives: 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” Truth Tables: Logical identity Logical identity is an operation on one logical value, typically the value of a proposition that produces a value of true if its operand is true and a value of false if its operand is false. The truth table for the logical identity operator is as follows: Logical Identity p p T T F F Logical negation Logical negation is an operation on one logical value, typically the value of a proposition that produces a value of true if its operand is false and a value of false if its operand is true. -
Introduction to Logic
IntroductionI Introduction to Logic Propositional calculus (or logic) is the study of the logical Christopher M. Bourke relationship between objects called propositions and forms the basis of all mathematical reasoning. Definition A proposition is a statement that is either true or false, but not both (we usually denote a proposition by letters; p, q, r, s, . .). Computer Science & Engineering 235 Introduction to Discrete Mathematics [email protected] IntroductionII ExamplesI Example (Propositions) Definition I 2 + 2 = 4 I The derivative of sin x is cos x. The value of a proposition is called its truth value; denoted by T or I 6 has 2 factors 1 if it is true and F or 0 if it is false. Opinions, interrogative and imperative sentences are not Example (Not Propositions) propositions. I C++ is the best language. I When is the pretest? I Do your homework. ExamplesII Logical Connectives Connectives are used to create a compound proposition from two Example (Propositions?) or more other propositions. I Negation (denoted or !) ¬ I 2 + 2 = 5 I And (denoted ) or Logical Conjunction ∧ I Every integer is divisible by 12. I Or (denoted ) or Logical Disjunction ∨ I Microsoft is an excellent company. I Exclusive Or (XOR, denoted ) ⊕ I Implication (denoted ) → I Biconditional; “if and only if” (denoted ) ↔ Negation Logical And A proposition can be negated. This is also a proposition. We usually denote the negation of a proposition p by p. ¬ The logical connective And is true only if both of the propositions are true. It is also referred to as a conjunction. Example (Negated Propositions) Example (Logical Connective: And) I Today is not Monday. -
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]. -
Chapter 1 Logic and Set Theory
Chapter 1 Logic and Set Theory To criticize mathematics for its abstraction is to miss the point entirely. Abstraction is what makes mathematics work. If you concentrate too closely on too limited an application of a mathematical idea, you rob the mathematician of his most important tools: analogy, generality, and simplicity. – Ian Stewart Does God play dice? The mathematics of chaos In mathematics, a proof is a demonstration that, assuming certain axioms, some statement is necessarily true. That is, a proof is a logical argument, not an empir- ical one. One must demonstrate that a proposition is true in all cases before it is considered a theorem of mathematics. An unproven proposition for which there is some sort of empirical evidence is known as a conjecture. Mathematical logic is the framework upon which rigorous proofs are built. It is the study of the principles and criteria of valid inference and demonstrations. Logicians have analyzed set theory in great details, formulating a collection of axioms that affords a broad enough and strong enough foundation to mathematical reasoning. The standard form of axiomatic set theory is denoted ZFC and it consists of the Zermelo-Fraenkel (ZF) axioms combined with the axiom of choice (C). Each of the axioms included in this theory expresses a property of sets that is widely accepted by mathematicians. It is unfortunately true that careless use of set theory can lead to contradictions. Avoiding such contradictions was one of the original motivations for the axiomatization of set theory. 1 2 CHAPTER 1. LOGIC AND SET THEORY A rigorous analysis of set theory belongs to the foundations of mathematics and mathematical logic. -
Folktale Documentation Release 1.0
Folktale Documentation Release 1.0 Quildreen Motta Nov 05, 2017 Contents 1 Guides 3 2 Indices and tables 5 3 Other resources 7 3.1 Getting started..............................................7 3.2 Folktale by Example........................................... 10 3.3 API Reference.............................................. 12 3.4 How do I................................................... 63 3.5 Glossary................................................. 63 Python Module Index 65 i ii Folktale Documentation, Release 1.0 Folktale is a suite of libraries for generic functional programming in JavaScript that allows you to write elegant modular applications with fewer bugs, and more reuse. Contents 1 Folktale Documentation, Release 1.0 2 Contents CHAPTER 1 Guides • Getting Started A series of quick tutorials to get you up and running quickly with the Folktale libraries. • API reference A quick reference of Folktale’s libraries, including usage examples and cross-references. 3 Folktale Documentation, Release 1.0 4 Chapter 1. Guides CHAPTER 2 Indices and tables • Global Module Index Quick access to all modules. • General Index All functions, classes, terms, sections. • Search page Search this documentation. 5 Folktale Documentation, Release 1.0 6 Chapter 2. Indices and tables CHAPTER 3 Other resources • Licence information 3.1 Getting started This guide will cover everything you need to start using the Folktale project right away, from giving you a brief overview of the project, to installing it, to creating a simple example. Once you get the hang of things, the Folktale By Example guide should help you understanding the concepts behind the library, and mapping them to real use cases. 3.1.1 So, what’s Folktale anyways? Folktale is a suite of libraries for allowing a particular style of functional programming in JavaScript. -
X86 Assembly Language Syllabus for Subject: Assembly (Machine) Language
VŠB - Technical University of Ostrava Department of Computer Science, FEECS x86 Assembly Language Syllabus for Subject: Assembly (Machine) Language Ing. Petr Olivka, Ph.D. 2021 e-mail: [email protected] http://poli.cs.vsb.cz Contents 1 Processor Intel i486 and Higher – 32-bit Mode3 1.1 Registers of i486.........................3 1.2 Addressing............................6 1.3 Assembly Language, Machine Code...............6 1.4 Data Types............................6 2 Linking Assembly and C Language Programs7 2.1 Linking C and C Module....................7 2.2 Linking C and ASM Module................... 10 2.3 Variables in Assembly Language................ 11 3 Instruction Set 14 3.1 Moving Instruction........................ 14 3.2 Logical and Bitwise Instruction................. 16 3.3 Arithmetical Instruction..................... 18 3.4 Jump Instructions........................ 20 3.5 String Instructions........................ 21 3.6 Control and Auxiliary Instructions............... 23 3.7 Multiplication and Division Instructions............ 24 4 32-bit Interfacing to C Language 25 4.1 Return Values from Functions.................. 25 4.2 Rules of Registers Usage..................... 25 4.3 Calling Function with Arguments................ 26 4.3.1 Order of Passed Arguments............... 26 4.3.2 Calling the Function and Set Register EBP...... 27 4.3.3 Access to Arguments and Local Variables....... 28 4.3.4 Return from Function, the Stack Cleanup....... 28 4.3.5 Function Example.................... 29 4.4 Typical Examples of Arguments Passed to Functions..... 30 4.5 The Example of Using String Instructions........... 34 5 AMD and Intel x86 Processors – 64-bit Mode 36 5.1 Registers.............................. 36 5.2 Addressing in 64-bit Mode.................... 37 6 64-bit Interfacing to C Language 37 6.1 Return Values.......................... -
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) ● -
Bitwise Operators in C Examples
Bitwise Operators In C Examples Alphonse misworships discommodiously. Epigastric Thorvald perishes changefully while Oliver always intercut accusatively.his anthology plumps bravely, he shown so cheerlessly. Baillie argufying her lashkar coweringly, she mass it Find the program below table which is c operators associate from star from the positive Left shift shifts each bit in its left operand to the left. Tying up some Arduino loose ends before moving on. The next example shows you how to do this. We can understand this better using the following Example. These operators move each bit either left or right a specified number of times. Amazon and the Amazon logo are trademarks of Amazon. Binary form of these values are given below. Shifting the bits of the string of bitwise operators in c examples and does not show the result of this means the truth table for making. Mommy, security and web. When integers are divided, it shifts the bits to the right. Operators are the basic concept of any programming language, subtraction, we are going to see how to use bitwise operators for counting number of trailing zeros in the binary representation of an integer? Adding a negative and positive number together never means the overflow indicates an exception! Not valid for string or complex operands. Les cookies essentiels sont absolument necessaires au bon fonctionnement du site. Like the assembly in C language, unlike other magazines, you may treat this as true. Bitwise OR operator is used to turn bits ON. To me this looks clearer as is. We will talk more about operator overloading in a future section, and the second specifies the number of bit positions by which the first operand is to be shifted. -
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 .