Propositional Calculus - Hilbert system H Moonzoo Kim CS Dept. KAIST

Similar documents
Propositional Calculus - Hilbert system H Moonzoo Kim CS Division of EECS Dept. KAIST

Propositional Calculus - Soundness & Completeness of H

Propositional Calculus - Deductive Systems

Propositional Calculus - Natural deduction Moonzoo Kim CS Dept. KAIST

Propositional Calculus - Semantics (3/3) Moonzoo Kim CS Dept. KAIST

Chapter 3: Propositional Calculus: Deductive Systems. September 19, 2008

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

Propositional Logic: Deductive Proof & Natural Deduction Part 1

Learning Goals of CS245 Logic and Computation

02 Propositional Logic

Propositional logic (revision) & semantic entailment. p. 1/34

Predicate Logic - Deductive Systems

Predicate Calculus - Semantic Tableau (2/2) Moonzoo Kim CS Division of EECS Dept. KAIST

2. The Logic of Compound Statements Summary. Aaron Tan August 2017

PROOFS IN MATHEMATICS

Natural Deduction for Propositional Logic

Propositional Logic: Syntax

Systems of modal logic

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

Deductive Systems. Lecture - 3

Formal Logic. Critical Thinking

Outline. Overview. Syntax Semantics. Introduction Hilbert Calculus Natural Deduction. 1 Introduction. 2 Language: Syntax and Semantics

Logic. Propositional Logic: Syntax

Warm-Up Problem. Write a Resolution Proof for. Res 1/32

COMP219: Artificial Intelligence. Lecture 19: Logic for KR

15414/614 Optional Lecture 1: Propositional Logic

Propositional Logic: Gentzen System, G

1. Propositional Calculus

Marie Duží

Discrete Mathematics. Instructor: Sourav Chakraborty. Lecture 4: Propositional Logic and Predicate Lo

COMP219: Artificial Intelligence. Lecture 19: Logic for KR

Advanced Topics in LP and FP

03 Propositional Logic II

Propositional and Predicate Logic - V

Natural Deduction. Formal Methods in Verification of Computer Systems Jeremy Johnson

Sec$on Summary. Mathematical Proofs Forms of Theorems Trivial & Vacuous Proofs Direct Proofs Indirect Proofs

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

Language of Propositional Logic

Predicate Calculus - Semantics 1/4

3. The Logic of Quantified Statements Summary. Aaron Tan August 2017

On the Complexity of the Reflected Logic of Proofs

Propositional Logic: Syntax

Manual of Logical Style (fresh version 2018)

AN INTRODUCTION TO SEPARATION LOGIC. 2. Assertions

Version January Please send comments and corrections to

Overview. Knowledge-Based Agents. Introduction. COMP219: Artificial Intelligence. Lecture 19: Logic for KR

Propositional Logic: Review

Inference in Propositional Logic

The proposition p is called the hypothesis or antecedent. The proposition q is called the conclusion or consequence.

An Introduction to Modal Logic III

The Modal Logic of Pure Provability

CSCI.6962/4962 Software Verification Fundamental Proof Methods in Computer Science (Arkoudas and Musser) Chapter p. 1/33

The Importance of Being Formal. Martin Henz. February 5, Propositional Logic

Propositional Resolution Introduction

a. (6.25 points) where we let b. (6.25 points) c. (6.25 points) d. (6.25 points) B 3 =(x)[ H(x) F (x)], and (11)

CS 380: ARTIFICIAL INTELLIGENCE

General methods in proof theory for modal logic - Lecture 1

Artificial Intelligence Knowledge Representation I

Propositional Logic Arguments (5A) Young W. Lim 10/11/16

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.

Propositional Reasoning

Logic for Computer Science - Week 4 Natural Deduction

Logic and Proofs 1. 1 Overview. 2 Sentential Connectives. John Nachbar Washington University December 26, 2014

Propositional natural deduction

Warm-Up Problem. Is the following true or false? 1/35

1. Propositional Calculus

Classical Propositional Logic

CS 380: ARTIFICIAL INTELLIGENCE PREDICATE LOGICS. Santiago Ontañón

Fundamentals of Logic

Packet #1: Logic & Proofs. Applied Discrete Mathematics

Logic: Propositional Logic Truth Tables

Gödel s Completeness Theorem

CITS2211 Discrete Structures Proofs

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

185.A09 Advanced Mathematical Logic

Logic. Introduction to Artificial Intelligence CS/ECE 348 Lecture 11 September 27, 2001

Dynamic Semantics. Dynamic Semantics. Operational Semantics Axiomatic Semantics Denotational Semantic. Operational Semantics

Chapter 2. Assertions. An Introduction to Separation Logic c 2011 John C. Reynolds February 3, 2011

Propositional Logic. Fall () Propositional Logic Fall / 30

A Weak Post s Theorem and the Deduction Theorem Retold

cis32-ai lecture # 18 mon-3-apr-2006

Temporal Logic - Soundness and Completeness of L

Logic, Sets, and Proofs

Propositional Logic Review

Intelligent Systems. Propositional Logic. Dieter Fensel and Dumitru Roman. Copyright 2008 STI INNSBRUCK

Teaching Natural Deduction as a Subversive Activity

CS 4700: Foundations of Artificial Intelligence

Propositional Logic. Jason Filippou UMCP. ason Filippou UMCP) Propositional Logic / 38

Description Logics. Deduction in Propositional Logic. franconi. Enrico Franconi

Logic. Definition [1] A logic is a formal language that comes with rules for deducing the truth of one proposition from the truth of another.

3 Propositional Logic

Proof Terminology. Technique #1: Direct Proof. Learning objectives. Proof Techniques (Rosen, Sections ) Direct Proof:

Computational Logic Chapter 2. Propositional Logic

Propositional Logic: Models and Proofs

Chapter 11: Automated Proof Systems (1)

MAI0203 Lecture 7: Inference and Predicate Calculus

Logic, Human Logic, and Propositional Logic. Human Logic. Fragments of Information. Conclusions. Foundations of Semantics LING 130 James Pustejovsky

CHAPTER 10. Gentzen Style Proof Systems for Classical Logic

Logical Agents. September 14, 2004

Last Time. Inference Rules

Transcription:

Propositional Calculus - Hilbert system H Moonzoo Kim CS Dept. KAIST moonzoo@cs.kaist.ac.kr CS402 1

Review Goal of logic To check whether given a formula Á is valid To prove a given formula Á ` Á Syntactic method (proof system G, H,etc) Sound & Complete ² Á Semantic method (truth table, etc) Semantic tableau 2

Review (cont.) Remember the following facts Although we have many binary operators ({Ç,Æ,!,Ã,$, #, ", }), " can replace all other binary operators through semantic equivalence. Similarly, {!, :} is an adequate set of binary operators. 2 Á does not necessarily mean ² :Á Deductive proof cannot disprove Á (i.e. claiming that there does not exist a proof for Á) while semantic method can show both validity and satisfiability of Á Very few logics have decision procedure for validity check (i.e., truth table). Thus, we use deductive proof in spite of the above weakness. A proof tree in G grows up while a proof tree in H shrinks down according to characteristics of its inference rules Thus, a proof in G is easier than a proof in H in general 3

Suppose that Sound verification tools there is a target software S there is a formal requirement R We can make a state machine (automata) of S, say AS A state of AS consists of all variables including a program counter. Any state machine can be encoded into a predicate logic formual Á as We will see this encoding in the first order logic classes We call V is sound whenever S has a bug, V always detects the bug Program verification is simply to prove Á AS ² R For this purpose, we use a formal verification tool V so that Á AS `V R We call V is complete whenever V detects a bug, that bug is a real bug. Á AS 2R ) Á AS 0V R (iff Á AS `V R ) Á AS ² R ) Á AS 0V R! Á AS 2R (iff Á AS ² R ) Á AS `V R) In reality, most formal verification tools are just sound, not complete (I.e., formal verification tools may raise false alarms). However, for debugging purpose, soundness is great. 4

The Hilbert system H Def 3.9 H is a deductive system with three axiom schemes and one rule of inference. For any formulas A,B,C, the following formulas are axioms (in fact axiom schemata): Axiom1: ` (A! (B! A)) Axiom2: ` (A! (B! C))!((A! B)! (A! C)) Axiom3: ` (:B! :A)! (A! B)) The rule of inference is called modus ponens (MP). For any formulas A,B `A `A!B `B Note that axioms used in a proof in H are usually very long because the MP rule reduces a length of formula (see Thm 3.10) at least one premise (` A! B) is longer than conclusion (B) 5

G v.s. H G is a deductive system for a set of formulas while H is a deductive system for a single formula G has one form of axiom and many rules (for 8 - rules and 7 -rules) while H has several axioms (in fact axiom schemes) but only one rule 6

Derived rules Def. 3.12 Let U be a set of formulas and A a formula. The notation U ` A means that the formulas in U are assumptions in the proof of A. If A i 2 U, a proof of U ` A may include an element of the form U ` A i Collorary. U [ {A} ` A Rule 3.13 Deduction rule U[fAg`B U`A!B Note that deduction rule increase the size of a formula, thus making a proof easier compared to MP rule 7

U[fAg`B U`A!B premise conclusion Soundness of deduction rule Thm 3.14 The deduction rule is a sound derived rule By induction on the length n of the proof U [ {A} ` B For n=1, B is proved in one step, so B must be either an element of U [ {A} or an axiom of H If B is A, then ` A!B by Thm 3.10 (` A! A), so certainly U ` A! B. Otherwise (i.e., B2U or B is an axion), the following is a proof of U ` A! B U ` B U ` A! B U ` B!(A!B) axiom 1 MP 8

U[fAg`B premise U`A!B conclusion Soundness of deduction rule For n>1, the last step in the proof of U[{A}`B is an inference of B using MP. there is a formula C such that formula i in the proof is U [ {A} ` C and formula j is U [ {A} ` C! B, for i, j < n. By the inductive hypothesis U ` A! C and U ` A! (C! B). A proof of U ` A! B is given by inductive hypothesis U ` A!(C!B) U ` (A!(C!B))!((A!C)!(A!B)) U ` (A!C)! (A!B) U ` A! B axiom 2 MP U ` A! C inductive hypothesis MP 9

Theorems and derived rules in H Note that any theorem of the form U ` A! B justifies a derived rule of the form simply by using MP on A and A! B U`A U`B Rule 3.15 Contrapositive rule by Axiom 3 ` (:B!:A)! (A!B)) U`:B!:A U`A!B Rule 3.17 Transitivity rule by Thm 3.16 ` (A!B)![(B!C)!(A!C)] U`A!B U`B!C U`A!C Rule 3.19 Exchange of antecedent rule by Thm 3.18 ` [(A! (B!C)]! [(B!(A!C)] U`A!(B!C) U`B!(A!C) 10

Theorems and derived rules in H Rule 3.23 Double negation rule by Thm 3.22 U ` ::A! A Let true be an abbreviation for p! p and false be an abbreviation for :(p! p) Rule 3.27 Reductio ad absurdum (RAA) rule Thm 3.28 ` (A! :A)! :A Thm 3.31 Weakening ` A! A Ç B ` B! A Ç B ` (A! B)! ((C Ç A)! (C Ç B)) U`::A U`A U`:A!f alse U`A 11