Categorical Foundations of Quantum Logics and Their Truth Values Structures
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An Axiomatic Approach to Physical Systems
' An Axiomatic Approach $ to Physical Systems & % Januari 2004 ❦ ' Summary $ Mereology is generally considered as a formal theory of the part-whole relation- ship concerning material bodies, such as planets, pickles and protons. We argue that mereology can be considered more generally as axiomatising the concept of a physical system, such as a planet in a gravitation-potential, a pickle in heart- burn and a proton in an electro-magnetic field. We design a theory of sets and physical systems by extending standard set-theory (ZFC) with mereological axioms. The resulting theory deductively extends both `Mereology' of Tarski & L`esniewski as well as the well-known `calculus of individuals' of Leonard & Goodman. We prove a number of theorems and demonstrate that our theory extends ZFC con- servatively and hence equiconsistently. We also erect a model of our theory in ZFC. The lesson to be learned from this paper reads that not only is a marriage between standard set-theory and mereology logically respectable, leading to a rigorous vin- dication of how physicists talk about physical systems, but in addition that sets and physical systems interact at the formal level both quite smoothly and non- trivially. & % Contents 0 Pre-Mereological Investigations 1 0.0 Overview . 1 0.1 Motivation . 1 0.2 Heuristics . 2 0.3 Requirements . 5 0.4 Extant Mereological Theories . 6 1 Mereological Investigations 8 1.0 The Language of Physical Systems . 8 1.1 The Domain of Mereological Discourse . 9 1.2 Mereological Axioms . 13 1.2.0 Plenitude vs. Parsimony . 13 1.2.1 Subsystem Axioms . 15 1.2.2 Composite Physical Systems . -
On the Boundary Between Mereology and Topology
On the Boundary Between Mereology and Topology Achille C. Varzi Istituto per la Ricerca Scientifica e Tecnologica, I-38100 Trento, Italy [email protected] (Final version published in Roberto Casati, Barry Smith, and Graham White (eds.), Philosophy and the Cognitive Sciences. Proceedings of the 16th International Wittgenstein Symposium, Vienna, Hölder-Pichler-Tempsky, 1994, pp. 423–442.) 1. Introduction Much recent work aimed at providing a formal ontology for the common-sense world has emphasized the need for a mereological account to be supplemented with topological concepts and principles. There are at least two reasons under- lying this view. The first is truly metaphysical and relates to the task of charac- terizing individual integrity or organic unity: since the notion of connectedness runs afoul of plain mereology, a theory of parts and wholes really needs to in- corporate a topological machinery of some sort. The second reason has been stressed mainly in connection with applications to certain areas of artificial in- telligence, most notably naive physics and qualitative reasoning about space and time: here mereology proves useful to account for certain basic relation- ships among things or events; but one needs topology to account for the fact that, say, two events can be continuous with each other, or that something can be inside, outside, abutting, or surrounding something else. These motivations (at times combined with others, e.g., semantic transpar- ency or computational efficiency) have led to the development of theories in which both mereological and topological notions play a pivotal role. How ex- actly these notions are related, however, and how the underlying principles should interact with one another, is still a rather unexplored issue. -
A Translation Approach to Portable Ontology Specifications
Knowledge Systems Laboratory September 1992 Technical Report KSL 92-71 Revised April 1993 A Translation Approach to Portable Ontology Specifications by Thomas R. Gruber Appeared in Knowledge Acquisition, 5(2):199-220, 1993. KNOWLEDGE SYSTEMS LABORATORY Computer Science Department Stanford University Stanford, California 94305 A Translation Approach to Portable Ontology Specifications Thomas R. Gruber Knowledge System Laboratory Stanford University 701 Welch Road, Building C Palo Alto, CA 94304 [email protected] Abstract To support the sharing and reuse of formally represented knowledge among AI systems, it is useful to define the common vocabulary in which shared knowledge is represented. A specification of a representational vocabulary for a shared domain of discourse — definitions of classes, relations, functions, and other objects — is called an ontology. This paper describes a mechanism for defining ontologies that are portable over representation systems. Definitions written in a standard format for predicate calculus are translated by a system called Ontolingua into specialized representations, including frame-based systems as well as relational languages. This allows researchers to share and reuse ontologies, while retaining the computational benefits of specialized implementations. We discuss how the translation approach to portability addresses several technical problems. One problem is how to accommodate the stylistic and organizational differences among representations while preserving declarative content. Another is how -
Semantics of First-Order Logic
CSC 244/444 Lecture Notes Sept. 7, 2021 Semantics of First-Order Logic A notation becomes a \representation" only when we can explain, in a formal way, how the notation can make true or false statements about some do- main; this is what model-theoretic semantics does in logic. We now have a set of syntactic expressions for formalizing knowledge, but we have only talked about the meanings of these expressions in an informal way. We now need to provide a model-theoretic semantics for this syntax, specifying precisely what the possible ways are of using a first-order language to talk about some domain of interest. Why is this important? Because, (1) that is the only way that we can verify that the facts we write down in the representation actually can mean what we intuitively intend them to mean; representations without formal semantics have often turned out to be incoherent when examined from this perspective; and (2) that is the only way we can judge whether proposed methods of making inferences are reasonable { i.e., that they give conclusions that are guaranteed to be true whenever the premises are, or at least are probably true, or at least possibly true. Without such guarantees, we will probably end up with an irrational \intelligent agent"! Models Our goal, then, is to specify precisely how all the terms, predicates, and formulas (sen- tences) of a first-order language can be interpreted so that terms refer to individuals, predicates refer to properties and relations, and formulas are either true or false. So we begin by fixing a domain of interest, called the domain of discourse: D. -
Solutions to Inclass Problems Week 2, Wed
Massachusetts Institute of Technology 6.042J/18.062J, Fall ’05: Mathematics for Computer Science September 14 Prof. Albert R. Meyer and Prof. Ronitt Rubinfeld revised September 13, 2005, 1279 minutes Solutions to InClass Problems Week 2, Wed. Problem 1. For each of the logical formulas, indicate whether or not it is true when the domain of discourse is N (the natural numbers 0, 1, 2, . ), Z (the integers), Q (the rationals), R (the real numbers), and C (the complex numbers). ∃x (x2 =2) ∀x ∃y (x2 =y) ∀y ∃x (x2 =y) ∀x�= 0∃y (xy =1) ∃x ∃y (x+ 2y=2)∧ (2x+ 4y=5) Solution. Statement N Z Q R √ C ∃x(x2= 2) f f f t(x= 2) t ∀x∃y(x2=y) t t t t(y=x2) t ∀y∃x(x2=y) f f f f(take y <0)t ∀x�=∃ 0y(xy= 1) f f t t(y=/x 1 ) t ∃x∃y(x+ 2y= 2)∧ (2x+ 4y=5)f f f f f � Problem 2. The goal of this problem is to translate some assertions about binary strings into logic notation. The domain of discourse is the set of all finitelength binary strings: λ, 0, 1, 00, 01, 10, 11, 000, 001, . (Here λdenotes the empty string.) In your translations, you may use all the ordinary logic symbols (including =), variables, and the binary symbols 0, 1 denoting 0, 1. A string like 01x0yof binary symbols and variables denotes the concatenation of the symbols and the binary strings represented by the variables. For example, if the value of xis 011 and the value of yis 1111, then the value of 01x0yis the binary string 0101101111. -
Discrete Mathematics for Computer Science I
University of Hawaii ICS141: Discrete Mathematics for Computer Science I Dept. Information & Computer Sci., University of Hawaii Originals slides by Dr. Baek and Dr. Still, adapted by J. Stelovsky Based on slides Dr. M. P. Frank and Dr. J.L. Gross Provided by McGraw-Hill ICS 141: Discrete Mathematics I – Fall 2011 4-1 University of Hawaii Lecture 4 Chapter 1. The Foundations 1.3 Predicates and Quantifiers ICS 141: Discrete Mathematics I – Fall 2011 4-2 Topic #3 – Predicate Logic Previously… University of Hawaii In predicate logic, a predicate is modeled as a proposional function P(·) from subjects to propositions. P(x): “x is a prime number” (x: any subject) P(3): “3 is a prime number.” (proposition!) Propositional functions of any number of arguments, each of which may take any grammatical role that a noun can take P(x,y,z): “x gave y the grade z” P(Mike,Mary,A): “Mike gave Mary the grade A.” ICS 141: Discrete Mathematics I – Fall 2011 4-3 Topic #3 – Predicate Logic Universe of Discourse (U.D.) University of Hawaii The power of distinguishing subjects from predicates is that it lets you state things about many objects at once. e.g., let P(x) = “x + 1 x”. We can then say, “For any number x, P(x) is true” instead of (0 + 1 0) (1 + 1 1) (2 + 1 2) ... The collection of values that a variable x can take is called x’s universe of discourse or the domain of discourse (often just referred to as the domain). ICS 141: Discrete Mathematics I – Fall 2011 4-4 Topic #3 – Predicate Logic Quantifier Expressions University of Hawaii Quantifiers provide a notation that allows us to quantify (count) how many objects in the universe of discourse satisfy the given predicate. -
1.1 Logic 1.1.1
Section 1.1 Logic 1.1.1 1.1 LOGIC Mathematics is used to predict empirical reality, and is therefore the foundation of engineering. Logic gives precise meaning to mathematical statements. PROPOSITIONS def: A proposition is a statement that is either true (T) or false (F), but not both. Example 1.1.1: 1+1=2.(T) 2+2=5.(F) Example 1.1.2: A fact-based declaration is a proposition, even if no one knows whether it is true. 11213 is prime. 1isprime. There exists an odd perfect number. Coursenotes by Prof. Jonathan L. Gross for use with Rosen: Discrete Math and Its Applic., 5th Ed. Chapter 1 FOUNDATIONS 1.1.2 Example 1.1.3: Logical analysis of rhetoric begins with the modeling of fact-based natural language declarations by propositions. Portland is the capital of Oregon. Columbia University was founded in 1754 by Romulus and Remus. If 2+2 = 5, then you are the pope. (a conditional fact-based declaration). Example 1.1.4: A statement cannot be true or false unless it is declarative. This excludes commands and questions. Go directly to jail. What time is it? Example 1.1.5: Declarations about semantic tokens of non-constant value are NOT proposi- tions. x+2=5. Coursenotes by Prof. Jonathan L. Gross for use with Rosen: Discrete Math and Its Applic., 5th Ed. Section 1.1 Logic 1.1.3 TRUTH TABLES def: The boolean domain is the set {T,F}. Either of its elements is called a boolean value. An n-tuple (p1,...,pn)ofboolean values is called a boolean n-tuple. -
Leibniz on Providence, Foreknowledge and Freedom
University of Massachusetts Amherst ScholarWorks@UMass Amherst Doctoral Dissertations 1896 - February 2014 1-1-1994 Leibniz on providence, foreknowledge and freedom. Jack D. Davidson University of Massachusetts Amherst Follow this and additional works at: https://scholarworks.umass.edu/dissertations_1 Recommended Citation Davidson, Jack D., "Leibniz on providence, foreknowledge and freedom." (1994). Doctoral Dissertations 1896 - February 2014. 2221. https://scholarworks.umass.edu/dissertations_1/2221 This Open Access Dissertation is brought to you for free and open access by ScholarWorks@UMass Amherst. It has been accepted for inclusion in Doctoral Dissertations 1896 - February 2014 by an authorized administrator of ScholarWorks@UMass Amherst. For more information, please contact [email protected]. LEIBNIZ ON PROVIDENCE, FOREKNOWLEDGE AND FREEDOM A Dissertation Presented by JACK D. DAVIDSON Submitted to the Graduate School of the University of Massachusetts Amherst in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY September 1994 Department of Philosophy Copyright by Jack D. Davidson 1994 All Rights Reserved ^ LEIBNIZ ON PROVIDENCE, FOREKNOWLEDGE AND FREEDOM A Dissertation Presented by JACK D. DAVIDSON Approved as to style and content by: \J J2SU2- Vere Chappell, Member Vincent Cleary, Membie r Member oe Jobln Robison, Department Head Department of Philosophy ACKNOWLEDGEMENTS I want to thank Vere Chappell for encouraging my work in early modern philosophy. From him I have learned a great deal about the intricate business of exegetical history. His careful work is, and will remain, an inspiration. I also thank Gary Matthews for providing me with an example of a philosopher who integrates his work with his life. Much of my interest in ancient and medieval philosophy has been inspired by his work. -
Exclusive Or from Wikipedia, the Free Encyclopedia
New features Log in / create account Article Discussion Read Edit View history Exclusive or From Wikipedia, the free encyclopedia "XOR" redirects here. For other uses, see XOR (disambiguation), XOR gate. Navigation "Either or" redirects here. For Kierkegaard's philosophical work, see Either/Or. Main page The logical operation exclusive disjunction, also called exclusive or (symbolized XOR, EOR, Contents EXOR, ⊻ or ⊕, pronounced either / ks / or /z /), is a type of logical disjunction on two Featured content operands that results in a value of true if exactly one of the operands has a value of true.[1] A Current events simple way to state this is "one or the other but not both." Random article Donate Put differently, exclusive disjunction is a logical operation on two logical values, typically the values of two propositions, that produces a value of true only in cases where the truth value of the operands differ. Interaction Contents About Wikipedia Venn diagram of Community portal 1 Truth table Recent changes 2 Equivalencies, elimination, and introduction but not is Contact Wikipedia 3 Relation to modern algebra Help 4 Exclusive “or” in natural language 5 Alternative symbols Toolbox 6 Properties 6.1 Associativity and commutativity What links here 6.2 Other properties Related changes 7 Computer science Upload file 7.1 Bitwise operation Special pages 8 See also Permanent link 9 Notes Cite this page 10 External links 4, 2010 November Print/export Truth table on [edit] archived The truth table of (also written as or ) is as follows: Venn diagram of Create a book 08-17094 Download as PDF No. -
Technology Mapping for Vlsi Circuits Exploiting Boolean Properties and Operations
TECHNOLOGY MAPPING FOR VLSI CIRCUITS EXPLOITING BOOLEAN PROPERTIES AND OPERATIONS disserttion sumi ttedtothe deprtmentofeletrilengi neering ndtheommitteeongrdutestudies ofstnforduniversi ty in prtilfulfillmentoftherequirements forthedegreeof dotorofphilosophy By Fr´ed´eric Mailhot December 1991 c Copyright 1991 by Fr´ed´eric Mailhot ii I certify that I have read this thesis and that in my opinion it is fully adequate, in scope and in quality, as a dissertation for the degree of Doctor of Philosophy. Giovanni De Micheli (Principal Advisor) I certify that I have read this thesis and that in my opinion it is fully adequate, in scope and in quality, as a dissertation for the degree of Doctor of Philosophy. Mark A. Horowitz I certify that I have read this thesis and that in my opinion it is fully adequate, in scope and in quality, as a dissertation for the degree of Doctor of Philosophy. Robert W. Dutton Approved for the University Committee on Graduate Stud- ies: Dean of Graduate Studies & Research iii Abstract Automatic synthesis of digital circuits has gained increasing importance. The synthesis process consists of transforming an abstract representation of a system into an implemen- tation in a target technology. The set of transformations has traditionally been broken into three steps: high-level synthesis, logic synthesis and physical design. This dissertation is concerned with logic synthesis. More specifically, we study tech- nology mapping, which is the link between logic synthesis and physical design. The object of technology mapping is to transform a technology-independent logic description into an implementation in a target technology. One of the key operations during tech- nology mapping is to recognize logic equivalence between a portion of the initial logic description and an element of the target technology. -
First-Order Logic in a Nutshell Syntax
First-Order Logic in a Nutshell 27 numbers is empty, and hence cannot be a member of itself (otherwise, it would not be empty). Now, call a set x good if x is not a member of itself and let C be the col- lection of all sets which are good. Is C, as a set, good or not? If C is good, then C is not a member of itself, but since C contains all sets which are good, C is a member of C, a contradiction. Otherwise, if C is a member of itself, then C must be good, again a contradiction. In order to avoid this paradox we have to exclude the collec- tion C from being a set, but then, we have to give reasons why certain collections are sets and others are not. The axiomatic way to do this is described by Zermelo as follows: Starting with the historically grown Set Theory, one has to search for the principles required for the foundations of this mathematical discipline. In solving the problem we must, on the one hand, restrict these principles sufficiently to ex- clude all contradictions and, on the other hand, take them sufficiently wide to retain all the features of this theory. The principles, which are called axioms, will tell us how to get new sets from already existing ones. In fact, most of the axioms of Set Theory are constructive to some extent, i.e., they tell us how new sets are constructed from already existing ones and what elements they contain. However, before we state the axioms of Set Theory we would like to introduce informally the formal language in which these axioms will be formulated. -
Leibniz's Theory of Propositional Terms: a Reply to Massimo
Leibniz’s Theory of Propositional Terms: A Reply to Massimo Mugnai Marko Malink, New York University Anubav Vasudevan, University of Chicago n his contribution to this volume of the Leibniz Review, Massimo Mugnai provides a very helpful review of our paper “The Logic of Leibniz’s Generales IInquisitiones de Analysi Notionum et Veritatum.” Mugnai’s review, which contains many insightful comments and criticisms, raises a number of issues that are of central importance for a proper understanding of Leibniz’s logical theory. We are grateful for the opportunity to explain our position on these issues in greater depth than we did in the paper. In his review, Mugnai puts forward two main criticisms of our reconstruction of the logical calculus developed by Leibniz in the Generales Inquisitiones. Both of these criticisms relate to Leibniz’s theory of propositional terms. The first concerns certain extensional features that we ascribe to the relation of conceptual containment as it applies to propositional terms. The second concerns the syntactic distinction we draw between propositions and propositional terms in the language of Leibniz’s calculus. In what follows, we address each of these criticisms in turn, beginning with the second. Propositions and Propositional Terms One of the most innovative aspects of the Generales Inquisitiones is Leibniz’s in- troduction into his logical theory of the device of propositional terms. By means of this device, Leibniz proposed to represent propositions of the form A is B by terms such as A’s being B. Leibniz regarded these propositional terms as abstract terms (abstracti termini, A VI 4 987), with the important qualification that they are merely “logical” or “notional” abstracts (A VI 4 740; cf.