The Context of Inference
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Philosophy 405: Knowledge, Truth and Mathematics Hamilton College Spring 2008 Russell Marcus M, W: 1-2:15Pm [email protected]
Philosophy 405: Knowledge, Truth and Mathematics Hamilton College Spring 2008 Russell Marcus M, W: 1-2:15pm [email protected] Class 15: Hilbert and Gödel I. Hilbert’s programme We have seen four different Hilberts: the term formalist (mathematical terms refer to inscriptions), the game formalist (ideal terms are meaningless), the deductivist (mathematics consists of deductions within consistent systems) the finitist (mathematics must proceed on finitary, but not foolishly so, basis). Gödel’s Theorems apply specifically to the deductivist Hilbert. But, Gödel would not have pursued them without the term formalist’s emphasis on terms, which lead to the deductivist’s pursuit of meta-mathematics. We have not talked much about the finitist Hilbert, which is the most accurate label for Hilbert’s programme. Hilbert makes a clear distinction between finite statements, and infinitary statements, which include reference to ideal elements. Ideal elements allow generality in mathematical formulas, and require acknowledgment of infinitary statements. See Hilbert 195-6. When Hilbert mentions ‘a+b=b+a’, he is referring to a universally quantified formula: (x)(y)(x+y=y+x) x and y range over all numbers, and so are not finitary. See Shapiro 159 on bounded and unbounded quantifiers. Hilbert’s blocky notation refers to bounded quantifiers. Note that a universal statement, taken as finitary, is incapable of negation, since it becomes an infinite statement. (x)Px is a perfectly finitary statement -(x)Px is equivalent to (x)-Px, which is infinitary - uh-oh! The admission of ideal elements begs questions of the meanings of terms in ideal statements. To what do the a and the b in ‘a+b=b+a’ refer? See Hilbert 194. -
Predicate Logic. Formal and Informal Proofs
CS 441 Discrete Mathematics for CS Lecture 5 Predicate logic Milos Hauskrecht [email protected] 5329 Sennott Square CS 441 Discrete mathematics for CS M. Hauskrecht Negation of quantifiers English statement: • Nothing is perfect. • Translation: ¬ x Perfect(x) Another way to express the same meaning: • Everything ... M. Hauskrecht 1 Negation of quantifiers English statement: • Nothing is perfect. • Translation: ¬ x Perfect(x) Another way to express the same meaning: • Everything is imperfect. • Translation: x ¬ Perfect(x) Conclusion: ¬ x P (x) is equivalent to x ¬ P(x) M. Hauskrecht Negation of quantifiers English statement: • It is not the case that all dogs are fleabags. • Translation: ¬ x Dog(x) Fleabag(x) Another way to express the same meaning: • There is a dog that … M. Hauskrecht 2 Negation of quantifiers English statement: • It is not the case that all dogs are fleabags. • Translation: ¬ x Dog(x) Fleabag(x) Another way to express the same meaning: • There is a dog that is not a fleabag. • Translation: x Dog(x) ¬ Fleabag(x) • Logically equivalent to: – x ¬ ( Dog(x) Fleabag(x) ) Conclusion: ¬ x P (x) is equivalent to x ¬ P(x) M. Hauskrecht Negation of quantified statements (aka DeMorgan Laws for quantifiers) Negation Equivalent ¬x P(x) x ¬P(x) ¬x P(x) x ¬P(x) M. Hauskrecht 3 Formal and informal proofs CS 441 Discrete mathematics for CS M. Hauskrecht Theorems and proofs • The truth value of some statement about the world is obvious and easy to assign • The truth of other statements may not be obvious, … …. But it may still follow (be derived) from known facts about the world To show the truth value of such a statement following from other statements we need to provide a correct supporting argument - a proof Important questions: – When is the argument correct? – How to construct a correct argument, what method to use? CS 441 Discrete mathematics for CS M. -
Arxiv:1906.04871V1 [Math.CO] 12 Jun 2019
Nearly Finitary Matroids By Patrick C. Tam DISSERTATION Submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in MATHEMATICS in the OFFICE OF GRADUATE STUDIES of the UNIVERSITY OF CALIFORNIA DAVIS Approved: Eric Babson Jes´usDe Loera arXiv:1906.04871v1 [math.CO] 12 Jun 2019 Matthias K¨oppe Committee in Charge 2018 -i- c Patrick C. Tam, 2018. All rights reserved. To... -ii- Contents Abstract iv Acknowledgments v Chapter 1. Introduction 1 Chapter 2. Summary of Main Results 17 Chapter 3. Finitarization Spectrum 20 3.1. Definitions and Motivation 20 3.2. Ladders 22 3.3. More on Spectrum 24 3.4. Nearly Finitary Matroids 27 3.5. Unionable Matroids 33 Chapter 4. Near Finitarization 35 4.1. Near Finitarization 35 4.2. Independence System Example 36 Chapter 5. Ψ-Matroids and Related Constructions 39 5.1. Ψ-Matroids 39 5.2. P (Ψ)-Matroids 42 5.3. Matroids and Axiom Systems 44 Chapter 6. Thin Sum Matroids 47 6.1. Nearly-Thin Families 47 6.2. Topological Matroids 48 Bibliography 51 -iii- Patrick C. Tam March 2018 Mathematics Nearly Finitary Matroids Abstract In this thesis, we study nearly finitary matroids by introducing new definitions and prove various properties of nearly finitary matroids. In 2010, an axiom system for infinite matroids was proposed by Bruhn et al. We use this axiom system for this thesis. In Chapter 2, we summarize our main results after reviewing historical background and motivation. In Chapter 3, we define a notion of spectrum for matroids. Moreover, we show that the spectrum of a nearly finitary matroid can be larger than any fixed finite size. -
CHAPTER 8 Hilbert Proof Systems, Formal Proofs, Deduction Theorem
CHAPTER 8 Hilbert Proof Systems, Formal Proofs, Deduction Theorem The Hilbert proof systems are systems based on a language with implication and contain a Modus Ponens rule as a rule of inference. They are usually called Hilbert style formalizations. We will call them here Hilbert style proof systems, or Hilbert systems, for short. Modus Ponens is probably the oldest of all known rules of inference as it was already known to the Stoics (3rd century B.C.). It is also considered as the most "natural" to our intuitive thinking and the proof systems containing it as the inference rule play a special role in logic. The Hilbert proof systems put major emphasis on logical axioms, keeping the rules of inference to minimum, often in propositional case, admitting only Modus Ponens, as the sole inference rule. 1 Hilbert System H1 Hilbert proof system H1 is a simple proof system based on a language with implication as the only connective, with two axioms (axiom schemas) which characterize the implication, and with Modus Ponens as a sole rule of inference. We de¯ne H1 as follows. H1 = ( Lf)g; F fA1;A2g MP ) (1) where A1;A2 are axioms of the system, MP is its rule of inference, called Modus Ponens, de¯ned as follows: A1 (A ) (B ) A)); A2 ((A ) (B ) C)) ) ((A ) B) ) (A ) C))); MP A ;(A ) B) (MP ) ; B 1 and A; B; C are any formulas of the propositional language Lf)g. Finding formal proofs in this system requires some ingenuity. Let's construct, as an example, the formal proof of such a simple formula as A ) A. -
List of Rules of Inference 1 List of Rules of Inference
List of rules of inference 1 List of rules of inference This is a list of rules of inference, logical laws that relate to mathematical formulae. Introduction Rules of inference are syntactical transform rules which one can use to infer a conclusion from a premise to create an argument. A set of rules can be used to infer any valid conclusion if it is complete, while never inferring an invalid conclusion, if it is sound. A sound and complete set of rules need not include every rule in the following list, as many of the rules are redundant, and can be proven with the other rules. Discharge rules permit inference from a subderivation based on a temporary assumption. Below, the notation indicates such a subderivation from the temporary assumption to . Rules for classical sentential calculus Sentential calculus is also known as propositional calculus. Rules for negations Reductio ad absurdum (or Negation Introduction) Reductio ad absurdum (related to the law of excluded middle) Noncontradiction (or Negation Elimination) Double negation elimination Double negation introduction List of rules of inference 2 Rules for conditionals Deduction theorem (or Conditional Introduction) Modus ponens (or Conditional Elimination) Modus tollens Rules for conjunctions Adjunction (or Conjunction Introduction) Simplification (or Conjunction Elimination) Rules for disjunctions Addition (or Disjunction Introduction) Separation of Cases (or Disjunction Elimination) Disjunctive syllogism List of rules of inference 3 Rules for biconditionals Biconditional introduction Biconditional Elimination Rules of classical predicate calculus In the following rules, is exactly like except for having the term everywhere has the free variable . Universal Introduction (or Universal Generalization) Restriction 1: does not occur in . -
Formalism II Gödel’S Incompleteness Theorems Hilbert's Programme and Its Collapse Curry
Outline Hilbert’s programme Formalism II Gödel’s incompleteness theorems Hilbert's Programme and its collapse Curry 13 April 2005 Joost Cassee Gustavo Lacerda Martijn Pennings 1 2 Previously on PhilMath… Foundations of Mathematics Axiomatic methods Logicism: Principia Mathematica Logicism Foundational crisis Formalism Russell’s paradox Term Formalism Cantor’s ‘inconsistent multitudes’ Game Formalism Law of excluded middle: P or not-P Intuitionism Deductivism = Game Formalism + preservation of truth Consistency paramount Quiet period for Hilbert: 1905 ~ 1920 No intuition needed Rejection of logicism 3 4 1 Birth of Finitism Finitary arithmetic Hermann Weyl: “The new foundational crisis in Basic arithmetic: 2+3=5, 7+7≠10, … mathematics” (1921) Intuitionistic restrictions – crippled mathematics Bounded quantifiers Bounded: 100 < p < 200 and p is prime Hilbert’s defense: finitism Unbounded: p > 100 and p and p+2 are prime ‘Basing the if of if-then-ism’ Core: finitary arithmetic All sentences effectively decidable Construction of all mathematics from core Finite algorithm Epistemologically satisfying 5 6 Finitary arithmetic – ontology Ideal mathematics – the rest Meaningful, independent of logic – Kantian Game-Formalistic rules Correspondance to finitary arithmetic Concrete symbols themselves: |, ||, |||, … … but not too concrete – not physical Restriction: consistency with finitary arithmetic Essential to human thought – not reducible Formal systems described in finitary arithmetic Finitary proof of -
Hilbert's Program Then And
Hilbert’s Program Then and Now Richard Zach Abstract Hilbert’s program was an ambitious and wide-ranging project in the philosophy and foundations of mathematics. In order to “dispose of the foundational questions in mathematics once and for all,” Hilbert proposed a two-pronged approach in 1921: first, classical mathematics should be formalized in axiomatic systems; second, using only restricted, “finitary” means, one should give proofs of the consistency of these axiomatic sys- tems. Although G¨odel’s incompleteness theorems show that the program as originally conceived cannot be carried out, it had many partial suc- cesses, and generated important advances in logical theory and meta- theory, both at the time and since. The article discusses the historical background and development of Hilbert’s program, its philosophical un- derpinnings and consequences, and its subsequent development and influ- ences since the 1930s. Keywords: Hilbert’s program, philosophy of mathematics, formal- ism, finitism, proof theory, meta-mathematics, foundations of mathemat- ics, consistency proofs, axiomatic method, instrumentalism. 1 Introduction Hilbert’s program is, in the first instance, a proposal and a research program in the philosophy and foundations of mathematics. It was formulated in the early 1920s by German mathematician David Hilbert (1862–1943), and was pursued by him and his collaborators at the University of G¨ottingen and elsewhere in the 1920s and 1930s. Briefly, Hilbert’s proposal called for a new foundation of mathematics based on two pillars: the axiomatic method, and finitary proof theory. Hilbert thought that by formalizing mathematics in axiomatic systems, and subsequently proving by finitary methods that these systems are consistent (i.e., do not prove contradictions), he could provide a philosophically satisfactory grounding of classical, infinitary mathematics (analysis and set theory). -
A Vindication of Program Verification 1. Introduction
June 2, 2015 13:21 History and Philosophy of Logic SB_progver_selfref_driver˙final A Vindication of Program Verification Selmer Bringsjord Department of Cognitive Science Department of Computer Science Lally School of Management & Technology Rensselaer AI & Reasoning Laboratory Rensselaer Polytechnic Institute (RPI) Troy NY 12180 USA [email protected] Received 00 Month 200x; final version received 00 Month 200x Fetzer famously claims that program verification isn't even a theoretical possibility, and offers a certain argument for this far-reaching claim. Unfortunately for Fetzer, and like-minded thinkers, this position-argument pair, while based on a seminal insight that program verification, despite its Platonic proof-theoretic airs, is plagued by the inevitable unreliability of messy, real-world causation, is demonstrably self-refuting. As I soon show, Fetzer (and indeed anyone else who provides an argument- or proof-based attack on program verification) is like the person who claims: \My sole claim is that every claim expressed by an English sentence and starting with the phrase `My sole claim' is false." Or, more accurately, such thinkers are like the person who claims that modus tollens is invalid, and supports this claim by giving an argument that itself employs this rule of inference. 1. Introduction Fetzer (1988) famously claims that program verification isn't even a theoretical possibility,1 and seeks to convince his readers of this claim by providing what has now become a widely known argument for it. Unfortunately for Fetzer, and like-minded thinkers, this position-argument pair, while based on a seminal insight that program verification, despite its Platonic proof-theoretic airs, is plagued by the inevitable unreliability of messy, real-world causation, is demonstrably self-refuting. -
Module 3: Proof Techniques
Module 3: Proof Techniques Theme 1: Rule of Inference Let us consider the following example. Example 1: Read the following “obvious” statements: All Greeks are philosophers. Socrates is a Greek. Therefore, Socrates is a philosopher. This conclusion seems to be perfectly correct, and quite obvious to us. However, we cannot justify it rigorously since we do not have any rule of inference. When the chain of implications is more complicated, as in the example below, a formal method of inference is very useful. Example 2: Consider the following hypothesis: 1. It is not sunny this afternoon and it is colder than yesterday. 2. We will go swimming only if it is sunny. 3. If we do not go swimming, then we will take a canoe trip. 4. If we take a canoe trip, then we will be home by sunset. From this hypothesis, we should conclude: We will be home by sunset. We shall come back to it in Example 5. The above conclusions are examples of a syllogisms defined as a “deductive scheme of a formal argument consisting of a major and a minor premise and a conclusion”. Here what encyclope- dia.com is to say about syllogisms: Syllogism, a mode of argument that forms the core of the body of Western logical thought. Aristotle defined syllogistic logic, and his formulations were thought to be the final word in logic; they underwent only minor revisions in the subsequent 2,200 years. We shall now discuss rules of inference for propositional logic. They are listed in Table 1. These rules provide justifications for steps that lead logically to a conclusion from a set of hypotheses. -
Recursion and Induction
Recursion and Induction Notes on Mathematical Logic and Model Theory David Pierce September 17, 2008 Columns in the Ionic order, Priene, Ionia (Söke, Aydın, Turkey) Contents Preface 4 Conventions 5 Chapter 1. Introduction 6 1.1. Building blocks 6 1.2. Model theory 8 1.3. Use and mention 9 1.4. The natural numbers 10 1.5. More building blocks 15 1.6. Well-ordered sets and cardinalities 17 1.7. Structures 18 1.8. Algebras 20 1.9. Propositional logic 22 Exercises 24 Chapter 2. Propositional model theory 26 2.1. Propositional formulas 26 2.2. Recursion 27 2.3. Notation 29 2.4. Truth 31 2.5. Logical entailment 33 2.6. Compactness 35 2.7. Syntactic entailment 36 2.8. Completeness 39 2.9. Other propositional logics 41 Exercises 43 Chapter 3. First-order logic 46 3.1. Terms 46 3.2. Atomic formulas 48 3.3. Open formulas 49 3.4. Formulas in general 50 3.5. Logical entailment 52 Exercises 54 Chapter 4. Quantifier-elimination and complete theories 56 4.1. Total orders 56 4.2. The natural numbers 59 Exercises 60 2 CONTENTS 3 Chapter 5. Relations between structures 62 5.1. Basic relations 62 5.2. Derived relations 63 5.3. Implications 63 5.4. Cardinalities 65 Exercises 68 Chapter 6. Compactness 70 6.1. Theorem 70 6.2. Applications 73 Exercises 75 Chapter 7. Completeness 76 7.1. Introduction 76 7.2. Propositional logic 76 7.3. Tautological completeness 77 7.4. Deductive completeness 78 7.5. Completeness 78 Exercises 82 Chapter 8. -
The Weird and Wonderful World of Constructive Mathematics
The weird and wonderful world of constructive mathematics Anti Mathcamp 2017 1. Down the rabbit hole Answer Yes, there is. If there is intelligent life elsewhere in the universe, then the program is print "Yes". If not, the program is p r i n t "No " . A puzzle Question Does there exist a computer program that is guaranteed to terminate in a finite amount of time, and will print \Yes" if there is intelligent life elsewhere in the universe and \No" if there is not? A puzzle Question Does there exist a computer program that is guaranteed to terminate in a finite amount of time, and will print \Yes" if there is intelligent life elsewhere in the universe and \No" if there is not? Answer Yes, there is. If there is intelligent life elsewhere in the universe, then the program is print "Yes". If not, the program is p r i n t "No " . 2 NO! That's WRONG! Two responses 1 Haha, that's clever. Two responses 1 Haha, that's clever. 2 NO! That's WRONG! More of the same A joke The math department at USD, where I work, is on the ground floor of Serra Hall, which is laid out as \a maze of twisty little passages, all alike." One day a lost visitor poked his head into an office and said \Excuse me, is there a way out of this maze?" The math professor in the office looked up and replied \Yes." Does it have to be that way? \When I use a word," Humpty Dumpty said, in rather a scornful tone, \it means just what I choose it to mean| neither more nor less." \The question is," said Alice, \whether you can make words mean so many different things." \The question is," said Humpty Dumpty, \which is to be master|that's all." In mathematics, we make the rules! In particular, we decide what words mean. -
CHAPTER 7 GENERAL PROOF SYSTEMS 1 Introduction
CHAPTER 7 GENERAL PROOF SYSTEMS 1 Introduction Proof systems are built to prove statements. They can be thought as an infer- ence machine with special statements, called provable statements, or sometimes theorems being its ¯nal products. The starting points are called axioms of the system. We distinguish two kinds of axioms: logicalLA and speci¯c SX. When building a proof system for a given language and its semantics i.e. for a logic de¯ned semantically we choose as a set of logical axioms LA some subset of tautologies, i.e. statements always true. This is why we call them logical axioms. A proof system with only logical axioms LA is also called a logic proof system. If we build a proof system for which there is no known semantics, like it has happened in the case of classical, intuitionistic, and modal logics, we think about the logical axioms as statements universally true. We choose as axioms (¯nite set) the statements we for sure want to be universally true, and whatever semantics follows they must be tautologies with respect to it. Logical axioms are hence not only tautologies under an established semantics, but they also guide us how to establish a semantics, when it is yet unknown. For the set of speci¯c axioms SA we choose these formulas of the language that describe our knowledge of a universe we want to prove facts about. They are not universally true, they are true only in the universe we are interested to describe and investigate. This is why we call them speci¯c axioms.