The Theory of Form Logic
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Indexed Induction-Recursion
Indexed Induction-Recursion Peter Dybjer a;? aDepartment of Computer Science and Engineering, Chalmers University of Technology, 412 96 G¨oteborg, Sweden Email: [email protected], http://www.cs.chalmers.se/∼peterd/, Tel: +46 31 772 1035, Fax: +46 31 772 3663. Anton Setzer b;1 bDepartment of Computer Science, University of Wales Swansea, Singleton Park, Swansea SA2 8PP, UK, Email: [email protected], http://www.cs.swan.ac.uk/∼csetzer/, Tel: +44 1792 513368, Fax: +44 1792 295651. Abstract An indexed inductive definition (IID) is a simultaneous inductive definition of an indexed family of sets. An inductive-recursive definition (IRD) is a simultaneous inductive definition of a set and a recursive definition of a function from that set into another type. An indexed inductive-recursive definition (IIRD) is a combination of both. We present a closed theory which allows us to introduce all IIRDs in a natural way without much encoding. By specialising it we also get a closed theory of IID. Our theory of IIRDs includes essentially all definitions of sets which occur in Martin-L¨of type theory. We show in particular that Martin-L¨of's computability predicates for dependent types and Palmgren's higher order universes are special kinds of IIRD and thereby clarify why they are constructively acceptable notions. We give two axiomatisations. The first and more restricted one formalises a prin- ciple for introducing meaningful IIRD by using the data-construct in the original version of the proof assistant Agda for Martin-L¨of type theory. The second one admits a more general form of introduction rule, including the introduction rule for the intensional identity relation, which is not covered by the restricted one. -
Terms First-Order Logic: Syntax - Formulas
First-order logic FOL Query Evaluation Giuseppe De Giacomo • First-order logic (FOL) is the logic to speak about object, which are the domain of discourse or universe. Universita` di Roma “La Sapienza” • FOL is concerned about Properties of these objects and Relations over objects (resp. unary and n-ary Predicates) • FOL also has Functions including Constants that denote objects. Corso di Seminari di Ingegneria del Software: Data and Service Integration Laurea Specialistica in Ingegneria Informatica Universita` degli Studi di Roma “La Sapienza” A.A. 2005-06 G. De Giacomo FOL queries 1 First-order logic: syntax - terms First-order logic: syntax - formulas Ter ms : defined inductively as follows Formulas: defined inductively as follows k • Vars: A set {x1,...,xn} of individual variables (variables that denote • if t1,...,tk ∈ Ter ms and P is a k-ary predicate, then k single objects) P (t1,...,tk) ∈ Formulas (atomic formulas) • Function symbols (including constants: a set of functions symbols of given • φ ∈ Formulas and ψ ∈ Formulas then arity > 0. Functions of arity 0 are called constants. – ¬φ ∈ Formulas • Vars ⊆ Ter ms – φ ∧ ψ ∈ Formulas k – φ ∨ ψ ∈ Formulas • if t1,...,tk ∈ Ter ms and f is a k-ary function, then k ⊃ ∈ f (t1,...,tk) ∈ Ter ms – φ ψ Formulas • nothing else is in Ter ms . • φ ∈ Formulas and x ∈ Vars then – ∃x.φ ∈ Formulas – ∀x.φ ∈ Formulas G. De Giacomo FOL queries 2 G. De Giacomo FOL queries 3 • nothing else is in Formulas. First-order logic: Semantics - interpretations Note: if a predicate is of arity Pi , then it is a proposition of propositional logic. -
Formal Systems: Combinatory Logic and -Calculus
INTRODUCTION APPLICATIVE SYSTEMS USEFUL INFORMATION FORMAL SYSTEMS:COMBINATORY LOGIC AND λ-CALCULUS Andrew R. Plummer Department of Linguistics The Ohio State University 30 Sept., 2009 INTRODUCTION APPLICATIVE SYSTEMS USEFUL INFORMATION OUTLINE 1 INTRODUCTION 2 APPLICATIVE SYSTEMS 3 USEFUL INFORMATION INTRODUCTION APPLICATIVE SYSTEMS USEFUL INFORMATION COMBINATORY LOGIC We present the foundations of Combinatory Logic and the λ-calculus. We mean to precisely demonstrate their similarities and differences. CURRY AND FEYS (KOREAN FACE) The material discussed is drawn from: Combinatory Logic Vol. 1, (1958) Curry and Feys. Lambda-Calculus and Combinators, (2008) Hindley and Seldin. INTRODUCTION APPLICATIVE SYSTEMS USEFUL INFORMATION FORMAL SYSTEMS We begin with some definitions. FORMAL SYSTEMS A formal system is composed of: A set of terms; A set of statements about terms; A set of statements, which are true, called theorems. INTRODUCTION APPLICATIVE SYSTEMS USEFUL INFORMATION FORMAL SYSTEMS TERMS We are given a set of atomic terms, which are unanalyzed primitives. We are also given a set of operations, each of which is a mode for combining a finite sequence of terms to form a new term. Finally, we are given a set of term formation rules detailing how to use the operations to form terms. INTRODUCTION APPLICATIVE SYSTEMS USEFUL INFORMATION FORMAL SYSTEMS STATEMENTS We are given a set of predicates, each of which is a mode for forming a statement from a finite sequence of terms. We are given a set of statement formation rules detailing how to use the predicates to form statements. INTRODUCTION APPLICATIVE SYSTEMS USEFUL INFORMATION FORMAL SYSTEMS THEOREMS We are given a set of axioms, each of which is a statement that is unconditionally true (and thus a theorem). -
Wittgenstein, Turing and Gödel
Wittgenstein, Turing and Gödel Juliet Floyd Boston University Lichtenberg-Kolleg, Georg August Universität Göttingen Japan Philosophy of Science Association Meeting, Tokyo, Japan 12 June 2010 Wittgenstein on Turing (1946) RPP I 1096. Turing's 'Machines'. These machines are humans who calculate. And one might express what he says also in the form of games. And the interesting games would be such as brought one via certain rules to nonsensical instructions. I am thinking of games like the “racing game”. One has received the order "Go on in the same way" when this makes no sense, say because one has got into a circle. For that order makes sense only in certain positions. (Watson.) Talk Outline: Wittgenstein’s remarks on mathematics and logic Turing and Wittgenstein Gödel on Turing compared Wittgenstein on Mathematics and Logic . The most dismissed part of his writings {although not by Felix Mülhölzer – BGM III} . Accounting for Wittgenstein’s obsession with the intuitive (e.g. pictures, models, aspect perception) . No principled finitism in Wittgenstein . Detail the development of Wittgenstein’s remarks against background of the mathematics of his day Machine metaphors in Wittgenstein Proof in logic is a “mechanical” expedient Logical symbolisms/mathematical theories are “calculi” with “proof machinery” Proofs in mathematics (e.g. by induction) exhibit or show algorithms PR, PG, BB: “Can a machine think?” Language (thought) as a mechanism Pianola Reading Machines, the Machine as Symbolizing its own actions, “Is the human body a thinking machine?” is not an empirical question Turing Machines Turing resolved Hilbert’s Entscheidungsproblem (posed in 1928): Find a definite method by which every statement of mathematics expressed formally in an axiomatic system can be determined to be true or false based on the axioms. -
Warren Goldfarb, Notes on Metamathematics
Notes on Metamathematics Warren Goldfarb W.B. Pearson Professor of Modern Mathematics and Mathematical Logic Department of Philosophy Harvard University DRAFT: January 1, 2018 In Memory of Burton Dreben (1927{1999), whose spirited teaching on G¨odeliantopics provided the original inspiration for these Notes. Contents 1 Axiomatics 1 1.1 Formal languages . 1 1.2 Axioms and rules of inference . 5 1.3 Natural numbers: the successor function . 9 1.4 General notions . 13 1.5 Peano Arithmetic. 15 1.6 Basic laws of arithmetic . 18 2 G¨odel'sProof 23 2.1 G¨odelnumbering . 23 2.2 Primitive recursive functions and relations . 25 2.3 Arithmetization of syntax . 30 2.4 Numeralwise representability . 35 2.5 Proof of incompleteness . 37 2.6 `I am not derivable' . 40 3 Formalized Metamathematics 43 3.1 The Fixed Point Lemma . 43 3.2 G¨odel'sSecond Incompleteness Theorem . 47 3.3 The First Incompleteness Theorem Sharpened . 52 3.4 L¨ob'sTheorem . 55 4 Formalizing Primitive Recursion 59 4.1 ∆0,Σ1, and Π1 formulas . 59 4.2 Σ1-completeness and Σ1-soundness . 61 4.3 Proof of Representability . 63 3 5 Formalized Semantics 69 5.1 Tarski's Theorem . 69 5.2 Defining truth for LPA .......................... 72 5.3 Uses of the truth-definition . 74 5.4 Second-order Arithmetic . 76 5.5 Partial truth predicates . 79 5.6 Truth for other languages . 81 6 Computability 85 6.1 Computability . 85 6.2 Recursive and partial recursive functions . 87 6.3 The Normal Form Theorem and the Halting Problem . 91 6.4 Turing Machines . -
15-819 Homotopy Type Theory Lecture Notes
15-819 Homotopy Type Theory Lecture Notes Nathan Fulton October 9 and 11, 2013 1 Contents These notes summarize and extend two lectures from Bob Harper’s Homotopy Type Theory course. The cumulative hierarchy of type universes, Extensional Type theory, the ∞-groupoid structure of types and iterated identity types are presented. 2 Motivation and Overview Recall from previous lectures the definitions of functionality and transport. Function- ality states that functions preserve identity; that is, domain elements equal in their type map to equal elements in the codomain. Transportation states the same for 0 0 type families. Traditionally, this means that if a =A a , then B[a] true iff B[a ] true. In proof-relevant mathematics, this logical equivalence is generalized to a statement 0 0 about identity in the family: if a =A a , then B[a] =B B[a ]. Transportation can be thought of in terms of functional extensionality. Un- fortunately, extensionality fails in ITT. One way to recover extensionality, which comports with traditional mathematics, is to reduce all identity to reflexivity. This approach, called Extensional Type theory (ETT), provides a natural setting for set-level mathematics. The HoTT perspective on ETT is that the path structure of types need not be limited to that of strict sets. The richer path structure of an ∞-groupoid is induced by the induction principle for identity types. Finding a type-theoretic description of this behavior (that is, introduction, elimination and computation rules which comport with Gentzen’s Inversion Principle) is an open problem. 1 Homotopy Type Theory 3 The Cumulative Hierarchy of Universes In previous formulations of ITT, we used the judgement A type when forming types. -
Formal Systems .1In
Formal systems | University of Edinburgh | PHIL08004 | 1 / 32 January 16, 2020 Puzzle 3 A man was looking at a portrait. Someone asked him, \Whose picture are you looking at?" He replied: \Brothers and sisters have I none, but this man's father is my father's son." Whose picture was the man looking at? 2 / 32 3 / 32 I Is the man in the picture the man himself? I Self-portrait? 4 / 32 I Is the man in the picture the man himself? I Self-portrait? 4 / 32 I Is the man in the picture the man himself? I Self-portrait? 4 / 32 I No. I If the man in the picture is himself, then this father would be his own son! I \this man is my father's son" vs. I \this man's father is my father's son" 5 / 32 I No. I If the man in the picture is himself, then this father would be his own son! I \this man is my father's son" vs. I \this man's father is my father's son" 5 / 32 I No. I If the man in the picture is himself, then this father would be his own son! I \this man is my father's son" vs. I \this man's father is my father's son" 5 / 32 I No. I If the man in the picture is himself, then this father would be his own son! I \this man is my father's son" vs. I \this man's father is my father's son" 5 / 32 I No. -
(Ie a Natural Model) Closed Under a Particular Connec
CONNECTIVES IN SEMANTICS OF TYPE THEORY JONATHAN STERLING Abstract. Some expository notes on the semantics of inductive types in Awodey’s nat- ural models [Awo18]. Many of the ideas explained are drawn from the work of Awodey [Awo18], Streicher [Str14], Gratzer, Kavvos, Nuyts, and Birkedal [Gra+20], and Sterling, Angiuli, and Gratzer [SAG20]. When is a model of type theory (i.e. a natural model) closed under a particular connec- tive? And what is a general notion of connective? Leing C be a small category with a terminal object and E = Pr¹Cº be its logos1 of presheaves, a natural model is a representable natural transformation TÛ τ T : E [Awo18]. j Connectives that commute with the Yoneda embedding C E (such as dependent product and sum) may be specied in a particularly simple way. ! F ! (1) First, one denes an endofunctor Ecart Ecart taking a family (viewed as a uni- verse) to the generic family for that connective. e intuition for this family is that the upstairs part carries the data of its introduction rule, and the downstairs part carries the data of its formation rule. For instance, one may take F to be the endofunctor that takes a map f to the functorial action of the polynomial endofunctor Pf on f itself. In this case, one has the notion of a dependent product type. (2) en, one requires a cartesian mapF¹τº τ, i.e. a pullback square of the following kind: Û @0¹F¹τºº T F¹τº τ @1¹F¹τºº T In the case of our example, the downstairs map becomes a code for the depen- dent product type, and the upstairs map becomes a constructor for λ-abstraction. -
Chapter 6: Translations in Monadic Predicate Logic 223
TRANSLATIONS IN 6 MONADIC PREDICATE LOGIC 1. Introduction ....................................................................................................222 2. The Subject-Predicate Form of Atomic Statements......................................223 3. Predicates........................................................................................................224 4. Singular Terms ...............................................................................................226 5. Atomic Formulas ............................................................................................228 6. Variables And Pronouns.................................................................................230 7. Compound Formulas ......................................................................................232 8. Quantifiers ......................................................................................................232 9. Combining Quantifiers With Negation ..........................................................236 10. Symbolizing The Statement Forms Of Syllogistic Logic ..............................243 11. Summary of the Basic Quantifier Translation Patterns so far Examined ......248 12. Further Translations Involving Single Quantifiers ........................................251 13. Conjunctive Combinations of Predicates.......................................................255 14. Summary of Basic Translation Patterns from Sections 12 and 13.................262 15. ‘Only’..............................................................................................................263 -
15-819 Homotopy Type Theory Lecture Notes
15-819 Homotopy Type Theory Lecture Notes Henry DeYoung and Stephanie Balzer September 9 and 11, 2013 1 Contents These notes summarize the lectures on homotopy type theory (HoTT) given by Professor Robert Harper on September 9 and 11, 2013, at CMU. They start by providing a introduction to HoTT, capturing its main ideas and its connection to other related type theories. Then they present intuitionistic propositional logic (IPL), giving both an proof-theoretic formulation as well an order-theoretic formulation. 2 Introduction to homotopy type theory Homotopy type theory(HoTT) is the subject of a very active research community that gathered at the Institute for Advanced Study (IAS) in 2012 to participate in the Univalent Foundations Program. The results of the program have been recently published in the HoTT Book [1]. 2.1 HoTT in a nutshell HoTT is based on Per Martin-L¨of’s intuitionistic type theory, which provides a foun- dation for intuitionistic mathematics and which is an extension of Brouwer’s program. Brouwer viewed mathematical reasoning as a human activity and mathematics as a language for communicating mathematical concepts. As a result, Brouwer per- ceived the ability of executing a step-by-step procedure or algorithm for performing a construction as a fundamental human faculty. Adopting Brouwer’s constructive viewpoint, intuitionistic theories view proofs as the fundamental forms of construction. The notion of proof relevance is thus a 1 Homotopy Type Theory characteristic feature of an intuitionistic (or constructive1) approach. In the context of HoTT, proof relevance means that proofs become mathematical objects [3]. To fully understand this standpoint, it is necessary to draw a distinction between the notion of a proof and the one of a formal proof [3, 2]. -
Handout 5 – the Semantics of Predicate Logic LX 502 – Semantics I October 17, 2008
Handout 5 – The Semantics of Predicate Logic LX 502 – Semantics I October 17, 2008 1. The Interpretation Function This handout is a continuation of the previous handout and deals exclusively with the semantics of Predicate Logic. When you feel comfortable with the syntax of Predicate Logic, I urge you to read these notes carefully. The business of semantics, as I have stated in class, is to determine the truth-conditions of a proposition and, in so doing, describe the models in which a proposition is true (and those in which it is false). Although we’ve extended our logical language, our goal remains the same. By adopting a more sophisticated logical language with a lexicon that includes elements below the sentence-level, we now need a more sophisticated semantics, one that derives the meaning of the proposition from the meaning of its constituent individuals, predicates, and variables. But the essentials are still the same. Propositions correspond to states of affairs in the outside world (Correspondence Theory of Truth). For example, the proposition in (1) is true if and only if it correctly describes a state of affairs in the outside world in which the object corresponding to the name Aristotle has the property of being a man. (1) MAN(a) Aristotle is a man The semantics of Predicate Logic does two things. It assigns a meaning to the individuals, predicates, and variables in the syntax. It also systematically determines the meaning of a proposition from the meaning of its constituent parts and the order in which those parts combine (Principle of Compositionality). -
A Dictionary of PHILOSOPHICAL LOGIC
a dictionary of a dictionary of PHILOSOPHICAL LOGIC This dictionary introduces undergraduate and graduate students PHILOSOPHICAL LOGIC in philosophy, mathematics, and computer science to the main problems and positions in philosophical logic. Coverage includes not only key figures, positions, terminology, and debates within philosophical logic itself, but issues in related, overlapping disciplines such as set theory and the philosophy of mathematics as well. Entries are extensively cross-referenced, so that each entry can be easily located within the context of wider debates, thereby providing a dictionary of a valuable reference both for tracking the connections between concepts within logic and for examining the manner in which these PHILOSOPHICAL LOGIC concepts are applied in other philosophical disciplines. Roy T. Cook is Assistant Professor in the Department of Philosophy at Roy T. Cook the University of Minnesota and an Associate Fellow at Arché, the Philosophical Research Centre for Logic, Language, Metaphysics and Epistemology at the University of St Andrews. He works primarily in the philosophy of logic, language, and mathematics, and has also Cook Roy T. published papers on seventeenth-century philosophy. ISBN 978 0 7486 2559 8 Edinburgh University Press E 22 George Square dinburgh Edinburgh EH8 9LF www.euppublishing.com Cover image: www.istockphoto.com Cover design: www.paulsmithdesign.com 1004 01 pages i-vi:Layout 1 16/2/09 15:18 Page i A DICTIONARY OF PHILOSOPHICAL LOGIC 1004 01 pages i-vi:Layout 1 16/2/09 15:18 Page ii Dedicated to my mother, Carol C. Cook, who made sure that I got to learn all this stuff, and to George Schumm, Stewart Shapiro, and Neil Tennant, who taught me much of it.