Special Topics on Applied Mathematical Logic

Similar documents
The Language. Elementary Logic. Outline. Well-Formed Formulae (wff s)

Final Exam (100 points)

More Model Theory Notes

First-Order Logic. 1 Syntax. Domain of Discourse. FO Vocabulary. Terms

GÖDEL S COMPLETENESS AND INCOMPLETENESS THEOREMS. Contents 1. Introduction Gödel s Completeness Theorem

Löwenheim-Skolem Theorems, Countable Approximations, and L ω. David W. Kueker (Lecture Notes, Fall 2007)

Herbrand Theorem, Equality, and Compactness

Part I: Propositional Calculus

Basics of Model Theory

Introduction to Model Theory

A MODEL-THEORETIC PROOF OF HILBERT S NULLSTELLENSATZ

2.2 Lowenheim-Skolem-Tarski theorems

Completeness for FOL

Handbook of Logic and Proof Techniques for Computer Science

Handout: Proof of the completeness theorem

First Order Logic (FOL) 1 znj/dm2017

LGIC 310/MATH 570/PHIL 006 Fall, 2010 Scott Weinstein 9

Preliminaries. Introduction to EF-games. Inexpressivity results for first-order logic. Normal forms for first-order logic

10 Propositional logic

Syntax. Notation Throughout, and when not otherwise said, we assume a vocabulary V = C F P.

Propositional and Predicate Logic - VII

PREDICATE LOGIC: UNDECIDABILITY AND INCOMPLETENESS HUTH AND RYAN 2.5, SUPPLEMENTARY NOTES 2

Peano Arithmetic. CSC 438F/2404F Notes (S. Cook) Fall, Goals Now

Harmonious Logic: Craig s Interpolation Theorem and its Descendants. Solomon Feferman Stanford University

0-1 Laws for Fragments of SOL

Incomplete version for students of easllc2012 only. 6.6 The Model Existence Game 99

Section Summary. Section 1.5 9/9/2014

3. Only sequences that were formed by using finitely many applications of rules 1 and 2, are propositional formulas.

Model Theory MARIA MANZANO. University of Salamanca, Spain. Translated by RUY J. G. B. DE QUEIROZ

CS589 Principles of DB Systems Fall 2008 Lecture 4e: Logic (Model-theoretic view of a DB) Lois Delcambre

Predicate Logic: Sematics Part 1

5. Peano arithmetic and Gödel s incompleteness theorem

Notes on Satisfiability-Based Problem Solving. First Order Logic. David Mitchell October 23, 2013

VAUGHT S THEOREM: THE FINITE SPECTRUM OF COMPLETE THEORIES IN ℵ 0. Contents

Mathematics 114L Spring 2018 D.A. Martin. Mathematical Logic

Lecture 2: Syntax. January 24, 2018

Tecniche di Verifica. Introduction to Propositional Logic

PREDICATE LOGIC. Schaum's outline chapter 4 Rosen chapter 1. September 11, ioc.pdf

Computational Logic. Recall of First-Order Logic. Damiano Zanardini

Propositional logic. First order logic. Alexander Clark. Autumn 2014

Classical Propositional Logic

Logical Structures in Natural Language: Propositional Logic II (Truth Tables and Reasoning

Reasoning Under Uncertainty: Introduction to Probability

FINITE MODEL THEORY (MATH 285D, UCLA, WINTER 2017) LECTURE NOTES IN PROGRESS

1 The decision problem for First order logic

Propositional and Predicate Logic - XIII


CS 514, Mathematics for Computer Science Mid-semester Exam, Autumn 2017 Department of Computer Science and Engineering IIT Guwahati

First Order Logic Semantics (3A) Young W. Lim 9/17/17

Propositional Logic: Part II - Syntax & Proofs 0-0

ACLT: Algebra, Categories, Logic in Topology - Grothendieck's generalized topological spaces (toposes)

Logic: The Big Picture

Math 225A Model Theory. Speirs, Martin

Description Logics. Foundations of Propositional Logic. franconi. Enrico Franconi

Learning Goals of CS245 Logic and Computation

Part II. Logic and Set Theory. Year

Přednáška 12. Důkazové kalkuly Kalkul Hilbertova typu. 11/29/2006 Hilbertův kalkul 1

THE LANGUAGE OF FIRST-ORDER LOGIC (FOL) Sec2 Sec1(1-16)

Logic Synthesis and Verification

Logic: Propositional Logic (Part I)

Lecture Notes 1 Basic Concepts of Mathematics MATH 352

Introduction to Metalogic


Overview of Topics. Finite Model Theory. Finite Model Theory. Connections to Database Theory. Qing Wang

Model Theory on Finite Structures

Thinking of Nested Quantification

Outline. Formale Methoden der Informatik First-Order Logic for Forgetters. Why PL1? Why PL1? Cont d. Motivation

A1 Logic (25 points) Using resolution or another proof technique of your stated choice, establish each of the following.

CSE 311: Foundations of Computing I Autumn 2014 Practice Final: Section X. Closed book, closed notes, no cell phones, no calculators.

Foundations of Mathematics MATH 220 FALL 2017 Lecture Notes

MODEL THEORY FOR ALGEBRAIC GEOMETRY

Examples: P: it is not the case that P. P Q: P or Q P Q: P implies Q (if P then Q) Typical formula:

Scott Sentences in Uncountable Structures

Conjunction: p q is true if both p, q are true, and false if at least one of p, q is false. The truth table for conjunction is as follows.

Some consequences of compactness in Lukasiewicz Predicate Logic

Logic: Propositional Logic Truth Tables

CONTENTS. Appendix C: Gothic Alphabet 109

PRESERVATION THEOREMS IN LUKASIEWICZ MODEL THEORY

Predicate Logic - Introduction

Informal Statement Calculus

Notes on Mathematical Logic. David W. Kueker

MASTERS EXAMINATION IN MATHEMATICS

Solutions to Unique Readability Homework Set 30 August 2011

First-Order Logic (FOL)

Applied Logic. Lecture 1 - Propositional logic. Marcin Szczuka. Institute of Informatics, The University of Warsaw

Finite Model Theory Tutorial. Lecture 1

INF3170 Logikk Spring Homework #8 For Friday, March 18

1 Completeness Theorem for First Order Logic

Propositional Logic: Syntax

Syntactic Characterisations in Model Theory

Intelligent Agents. First Order Logic. Ute Schmid. Cognitive Systems, Applied Computer Science, Bamberg University. last change: 19.

Meta-logic derivation rules

Before you get started, make sure you ve read Chapter 1, which sets the tone for the work we will begin doing here.

Introduction to first-order logic:

From Constructibility and Absoluteness to Computability and Domain Independence

Logic. Propositional Logic: Syntax. Wffs

COMP 409: Logic Homework 5

03 Review of First-Order Logic

CHAPTER 2. FIRST ORDER LOGIC

Discrete Mathematics and Its Applications

Transcription:

Special Topics on Applied Mathematical Logic Spring 2012 Lecture 04 Jie-Hong Roland Jiang National Taiwan University March 20, 2012 Outline First-Order Logic Truth and Models (Semantics) Logical Implication Definability Homomorphisms

Truth and Models Truth assignments are to sentential logic what structures (or interpretations) are to first-order logic A structure for a first-order language tells 1. what the universe (the set of objects that refers to) is, and 2. what the parameters (predicate, constant, function symbols) mean Truth and Models Formally, a structure A is a function whose domain is the set of parameters and 1. A assigns to the symbol a nonempty set A called the universe (or domain) ofa for everything in A 2. A assigns to each n-place predicate symbol P an n-ary relation P A A n Pt 1,...,t n t 1,...,t n A is in P A 3. A assigns to each constant symbol c a member c A of A c c A 4. A assigns to each n-place function symbol f an n-ary operation f A : A n A (the mapping must be total)

Truth and Models Example Language of set theory x y y x There exists a set s.t. every set is not its member x y z t(t z (t = x t = y)) For every two sets x and y, there exists a set z such that for every set t, t z iff t = x or t = y (pair-set axiom) Language of number theory Let A be such that A = N and A is the set of pairs m, n with m < n x y y x There exists a natural number that is the smallest We say x y y x is true in A, ora is a model of x y y x x y z t(t z (t = x t = y)) The formula is not true (i.e., false) in A Truth and Models Example Consider a language with and 2-place predicate symbol E Let structure B have B = {a, b, c, d} (vertex set) E B = { a, b, b, a, b, c, c, c } (edge set) a b c d x y Eyx The formula is true in B (there is a vertex not pointed to from any vertex)

Truth and Models A sentence σ is true in A, denoted = A σ To formally define = A ϕ, let ϕ be a wff of our language, A be a structure for the language, and s : V A for V being the set of all variables. Then = A ϕ[s] (meaning A satisfies ϕ with s) iffthe translation of ϕ determined by A is true, where variable x is translated as s(x) wherever it occurs free. Truth and Models Extend s to s case i (terms) s : T A for T the set of all terms s is defined recursively by 1. s(x) =s(x) (x: variable) 2. s(c) =c A (c: constant) 3. s(ft 1,...,t n )=f A (s(t 1 ),...,s(t n )) (f : function) commutative diagram of s(ft) =f A (s(t)) f T T s s A A f A s is unique s depends on both s and A

Truth and Models Extend s to s (cont d) case ii (atomic formulas) explicit (not recursive) definition with 1. = A =t 1 t 2 [s] iffs(t 1 )=s(t 2 ) 2. = A Pt 1 t n [s] iff sequence s(t 1 ),...,s(t n ) P A Truth and Models Extend s to s (cont d) case iii (other wffs) recursive definition with 1. For atomic formulas, see case ii 2. = A ϕ[s] iff = A ϕ[s] 3. = A (ϕ ψ)[s] iff either = A ϕ[s] or = A ψ[s] or both 4. = A xϕ[s] iff for every { d A, = A ϕ[s(x d)], s(y) if y x where s(x d)(y) = d if y = x = A (α β)[s] iff = A α[s] and = A β[s] (similarly for and ) = A xα[s] iff there is some d A such that = A α[s(x d)]

Truth and Models = A ϕ[s] iff the translation of ϕ determined by A is true for free variables translated as s(x) s only matters for free variables If ϕ is a sentence, then s does not matter Truth and Models Example Consider a language with, P (two-place predicate), f (one-place function), and c (constant); let A =(N;, S, 0), i.e., A = N P A = { m, n m n} f A = S, i.e., f A (n) =n +1 c A =0 Let s(v i )=i 1. Then s(ffv 3 )=4 s(c) =0 s(fffc) =3 = A Pcfv 1 [s] ( 0 1) = A v 1 Pcv 1 = A v 1 Pv 2 v 1 [s] = A v 1 v 2 Pv 2 v 1 [s]

Truth and Models Example a b c d = B v 2 Ev 1 v 2 [s] iffs(v 1 )=d = B v 2 Ev 2 v 1 [s] iffs(v 1 )=d = B v 2 Ev 1 v 2 [s] iffs(v 1 )=a, b, c Truth and Models Theorem Assume functions s 1 and s 2 : V A agree at all free variables of ϕ. Then = A ϕ[s 1 ] iff = A ϕ[s 2 ] (prove by induction) If A and B agree at all parameters that occur in ϕ, then = A ϕ[s] iff = B ϕ[s] A and B are elementarily equivalent (denoted A B) ifffor any sentence σ, = A σ iff = B σ

Truth and Models Notation = A ϕ[[a 1,...,a k ]] denotes A satisfies ϕ with s(v i )=a i, where v i is the ith free variable in ϕ E.g., A =(N;, S, 0) = A v 2 Pv 1 v 2 [[0]] = A v 2 Pv 1 v 2 [[1]] Truth and Models Corollary For a sentence σ, either (a) A satisfies σ with every s : V A, or (b) A does not satisfy σ with any s : V A For case (a), we say σ is true in A or A is a model of σ (i.e., = A σ) For case (b), we say σ is false in A

Truth and Models A is a model of a set Σ of sentences iff it is a model of every member of Σ Examples R =(R;0, 1, +, ); Q =(Q;0, 1, +, ) = R x(x x =1+1) = Q x(x x =1+1) Consider a language has only the parameters and a 2-place predicate P x yx = y A =(A; R) is a model iff? x ypxy A =(A; R) is a model iff? x y Pxy A =(A; R) is a model iff? x ypxy A =(A; R) is a model iff? Logical Implication A set Σ of wffs logically implies awffϕ, denoted Σ = ϕ, ifffor every structure A for the language and every function s : V A such that if A satisfies every member of Σ with s, the A also satisfies ϕ with s Entailment = is a semantical relation Recall = denotes tautological implication in sentential logic {γ} = ϕ will be written as γ = ϕ ϕ and ψ are logically equivalent, denoted ϕ = = ψ, iff ϕ = ψ and ψ = ϕ

Logical Implication sentential logic first-order logic = τ = ϕ τ is a tautology ϕ is a valid wff, i.e., for every A and every s : V A, A satisfies ϕ with s Logical Implication Corollary For a set Σ; τ of sentences, Σ = τ iff every model of Σ is also a model of τ. A sentence is valid iff it is true in every structure. Examples v 1 Qv 1 = Qv 2 Qv 1 = v 1 Qv 1 = σ σ v 1 Qv 1 = v 2 Qv 2 x ypxy = y xpxy = x(qx xqx)

Logical Implication Checking tautology (of sentential logic) is a finite process Checking validity (of first-order logic) is an infinite process Must consider every structure Logical Implication The set of valid formulas is not decidable, but semi-decidable (i.e., effectively enumerable) wffs of sentential logic vs. wffs of first-order logic Later we will show that validity ( =) and deducibility ( ) are equivalent in first order logic

Definiability in a Structure { a 1,...,a k = A ϕ[[a 1,...,a k ]]} is a relation that ϕ defines in A A k-ary relation on A is definiable in A iff there is a formula (with free variables v 1,..., v k ) that defines the relation in A E.g., R =(R;0, 1, +, ) = R v 2 v 1 = v 2 v 2 [[a]] a 0 [0, ) is definiable in R = R v 3 v 1 = v 2 + v 3 v 3 [[a, b]] a b { a, b R R a b} is definiable in R A =({a, b, c}; E = { a, b, a, c }) where the language has parameters and b a c {b, c} is defined by v2 Ev 2 v 1 {b} is not definable in A Definiability in a Structure E.g., N =(N;0, S, +, ) under the language for number theory { m, n m < n} is defined in N by v 3 v 1 + Sv 3 = v 2 {2} is defined in N by v 1 = SS0 The set of primes is defined in N by S0 < v 1 v 2 v 3 (v 1 = v 2 v 3 v 2 =1 v 3 =1) Exponentiation { m, n, p p = m n } is definable in N

Definiability in a Structure Let L be a language that does not include an n-place predicate symbol P, L + be the language that extends L and includes P, and τ be a theory in L +. P is explicitly definable if there is an L formula φ with free variables x 1,...,x n such that τ = Px 1...x n φ. P is implicitly definable if for any structure A and any R 1, R 2 A n if both ( A, R 1 ) and ( A, R 2 ) are models of τ, then R 1 = R 2. Theorem (Beth s Definiability Theorem) P is explicitly definable if, and only if, P is implicitly definable. Definiability in a Structure There are uncountably many relations on N, but only countably many possible defining formulas Any decidable relation on N is definable in N ( 3.5)

Definability of a Class of Structures Let ModΣ be the class of all models of a set Σ of sentences. (That is, the class of all structures for the language in which every member of Σ is true.) A set is a class Classes are beyond sets (e.g., the class of all sets) A class K of structures for the language is an elementary class (EC) iff K = Modτ (i.e., Mod{τ}) for some sentence τ where elementary means first order A class K is an elementary class in a wider sense iff K = ModΣ Definability of a Class of Structures E.g., consider the language L with =,, and a 2-place predicate E A graph is a structure A =(V ; E A )forl, where A = V is the (nonempty) set of vertices and E A is an edge relation that is symmetric and irreflexive with axiom: x( y(exy Eyx) Exx) The class of graphs is an elementary class

Homomorphisms A homomorphism h of A into B is a function h : A B such that 1. for predicate symbol P a 1,...,a n P A iff h(a 1 ),...,h(a n ) P B 2. for function symbol f h(f A (a 1,...,a n )) = f B (h(a 1 ),...,h(a n )) h(c A )=c B E.g., A =(N;+, ), B =({e, o};+ B, B) + B e o B e o e e o e e e o o e o e o { e if n is even h(n) = o if n is odd h is a homomorphism of A into B Isomorphism A homomorphism h is called an isomorphism (or isomorphic embedding) ofa into B if h is one-to-one Two structures A and B are isomorphic (denoted A = B) if there is an isomorphism of A onto B Two isomorphic structures satisfy exactly the same sentences

Substructures A is a substructure of B, orb is an extension of A, if A B and the identity map Id : A B is an isomorphism of A into B, equivalently 1. P A is the restriction of P B to A 2. f A is the restriction of f B to A, and c A = c B E.g., A =(P; <) forp: positive integers, B =(N; <) Id(n) = n is an isomorphism A is a substructure of B h(n) = n 1 is an isomorphism Homomorphism Theorem Theorem (Homomorphism Theorem) Let h be a homomorphism of A into B and s : V A, where V is the set of variables. Then (a) for any term t, h(s(t)) = h s(t) (b) for any quantifier-free formula α not containing the equality symbol, = A α[s] iff = B α[h s] The quantifier-free criterion is due to the fact that h may not be onto The exclusion of the equality symbol is due to the fact that h may not be one-to-one

Homomorphism E.g., A =(P; <), B =(N; <) = A v 2 (v 1 v 2 v 1 < v 2 )[[1]] = B v 2 (v 1 v 2 v 1 < v 2 )[[1]] h = Id : A B is not onto = A v 1 = v 2 [[1, 2]] = B v 1 = v 2 [[0, 0]] { 0 if n =1 h(n) = n 2 if n 2 is not one-to-one Elementary Equivalence Two structures A and B for the language are elementarily equivalent (denoted A B) iff for every sentence σ, = A σ iff = B σ Corollary If A = B, then A B The converse is not true E.g., (R; <) (Q; <), but (R; <) = (Q; <)

Automorphism An automorphism of the structure A is an isomorphism (namely, one-to-one homomorphism) of A onto A Corollary Let h be an automorphism of A, and R be an n-ary relation on A definable in A. Then a 1,...,a n Riff h(a 1 ),...,h(a n ) R. Proof. Let ϕ defines R in A. By Homomorphism Theorem, = A ϕ[[a 1,...,a n ]] iff = A ϕ[[h(a 1 ),...,h(a n )]] Therefore, automorphism preserves definable relations and is useful in showing some relation is not definable. E.g., N is not definable in (R; <) By automorphism h(a) =a 3 ( 3 2 N, but 2 N)