James Chapman University of Tartu Principle of Explosion Acknowledgements
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Two Sources of Explosion
Two sources of explosion Eric Kao Computer Science Department Stanford University Stanford, CA 94305 United States of America Abstract. In pursuit of enhancing the deductive power of Direct Logic while avoiding explosiveness, Hewitt has proposed including the law of excluded middle and proof by self-refutation. In this paper, I show that the inclusion of either one of these inference patterns causes paracon- sistent logics such as Hewitt's Direct Logic and Besnard and Hunter's quasi-classical logic to become explosive. 1 Introduction A central goal of a paraconsistent logic is to avoid explosiveness { the inference of any arbitrary sentence β from an inconsistent premise set fp; :pg (ex falso quodlibet). Hewitt [2] Direct Logic and Besnard and Hunter's quasi-classical logic (QC) [1, 5, 4] both seek to preserve the deductive power of classical logic \as much as pos- sible" while still avoiding explosiveness. Their work fits into the ongoing research program of identifying some \reasonable" and \maximal" subsets of classically valid rules and axioms that do not lead to explosiveness. To this end, it is natural to consider which classically sound deductive rules and axioms one can introduce into a paraconsistent logic without causing explo- siveness. Hewitt [3] proposed including the law of excluded middle and the proof by self-refutation rule (a very special case of proof by contradiction) but did not show whether the resulting logic would be explosive. In this paper, I show that for quasi-classical logic and its variant, the addition of either the law of excluded middle or the proof by self-refutation rule in fact leads to explosiveness. -
Logic, Sets, and Proofs David A
Logic, Sets, and Proofs David A. Cox and Catherine C. McGeoch Amherst College 1 Logic Logical Statements. A logical statement is a mathematical statement that is either true or false. Here we denote logical statements with capital letters A; B. Logical statements be combined to form new logical statements as follows: Name Notation Conjunction A and B Disjunction A or B Negation not A :A Implication A implies B if A, then B A ) B Equivalence A if and only if B A , B Here are some examples of conjunction, disjunction and negation: x > 1 and x < 3: This is true when x is in the open interval (1; 3). x > 1 or x < 3: This is true for all real numbers x. :(x > 1): This is the same as x ≤ 1. Here are two logical statements that are true: x > 4 ) x > 2. x2 = 1 , (x = 1 or x = −1). Note that \x = 1 or x = −1" is usually written x = ±1. Converses, Contrapositives, and Tautologies. We begin with converses and contrapositives: • The converse of \A implies B" is \B implies A". • The contrapositive of \A implies B" is \:B implies :A" Thus the statement \x > 4 ) x > 2" has: • Converse: x > 2 ) x > 4. • Contrapositive: x ≤ 2 ) x ≤ 4. 1 Some logical statements are guaranteed to always be true. These are tautologies. Here are two tautologies that involve converses and contrapositives: • (A if and only if B) , ((A implies B) and (B implies A)). In other words, A and B are equivalent exactly when both A ) B and its converse are true. -
On the Analysis of Indirect Proofs: Contradiction and Contraposition
On the analysis of indirect proofs: Contradiction and contraposition Nicolas Jourdan & Oleksiy Yevdokimov University of Southern Queensland [email protected] [email protected] roof by contradiction is a very powerful mathematical technique. Indeed, Premarkable results such as the fundamental theorem of arithmetic can be proved by contradiction (e.g., Grossman, 2009, p. 248). This method of proof is also one of the oldest types of proof early Greek mathematicians developed. More than two millennia ago two of the most famous results in mathematics: The irrationality of 2 (Heath, 1921, p. 155), and the infinitude of prime numbers (Euclid, Elements IX, 20) were obtained through reasoning by contradiction. This method of proof was so well established in Greek mathematics that many of Euclid’s theorems and most of Archimedes’ important results were proved by contradiction. In the 17th century, proofs by contradiction became the focus of attention of philosophers and mathematicians, and the status and dignity of this method of proof came into question (Mancosu, 1991, p. 15). The debate centred around the traditional Aristotelian position that only causality could be the base of true scientific knowledge. In particular, according to this traditional position, a mathematical proof must proceed from the cause to the effect. Starting from false assumptions a proof by contradiction could not reveal the cause. As Mancosu (1996, p. 26) writes: “There was thus a consensus on the part of these scholars that proofs by contradiction were inferior to direct Australian Senior Mathematics Journal vol. 30 no. 1 proofs on account of their lack of causality.” More recently, in the 20th century, the intuitionists went further and came to regard proof by contradiction as an invalid method of reasoning. -
Logic and Proof Release 3.18.4
Logic and Proof Release 3.18.4 Jeremy Avigad, Robert Y. Lewis, and Floris van Doorn Sep 10, 2021 CONTENTS 1 Introduction 1 1.1 Mathematical Proof ............................................ 1 1.2 Symbolic Logic .............................................. 2 1.3 Interactive Theorem Proving ....................................... 4 1.4 The Semantic Point of View ....................................... 5 1.5 Goals Summarized ............................................ 6 1.6 About this Textbook ........................................... 6 2 Propositional Logic 7 2.1 A Puzzle ................................................. 7 2.2 A Solution ................................................ 7 2.3 Rules of Inference ............................................ 8 2.4 The Language of Propositional Logic ................................... 15 2.5 Exercises ................................................. 16 3 Natural Deduction for Propositional Logic 17 3.1 Derivations in Natural Deduction ..................................... 17 3.2 Examples ................................................. 19 3.3 Forward and Backward Reasoning .................................... 20 3.4 Reasoning by Cases ............................................ 22 3.5 Some Logical Identities .......................................... 23 3.6 Exercises ................................................. 24 4 Propositional Logic in Lean 25 4.1 Expressions for Propositions and Proofs ................................. 25 4.2 More commands ............................................ -
Fourier's Proof of the Irrationality of E
Ursinus College Digital Commons @ Ursinus College Transforming Instruction in Undergraduate Calculus Mathematics via Primary Historical Sources (TRIUMPHS) Summer 2020 Fourier's Proof of the Irrationality of e Kenneth M. Monks Follow this and additional works at: https://digitalcommons.ursinus.edu/triumphs_calculus Click here to let us know how access to this document benefits ou.y Fourier's Proof of the Irrationality of e Kenneth M Monks ∗ August 6, 2020 We begin with a short passage from Aristotle's1 Prior Analytics2. This translation was completed by Oxford scholars in 1931 and compiled by Richard McKeon into The Basic Works of Aristotle [McKeon, 1941]. 1111111111111111111111111111111111111111 xI.23. For all who effect an argument per impossibile infer syllogistically what is false, and prove the original conclusion hypothetically when something impossible results from the as- sumption of its contradictory; e.g. that the diagonal of a square is incommensurate with the side, because odd numbers are equal to evens if it is supposed to be commensurate. 1111111111111111111111111111111111111111 The goal of this project is to work through a proof of the irrationality of the number e due to Joseph Fourier. This number would not have even been defined in any publication for another two millennia3 (plus a few years) after the writing of Prior Analytics! So, the reader may wonder why we are rewinding our clocks so far back. Well, it turns out that the key ideas required to understand Fourier's proof of the irrationality of e can be traced right back to that passage from Aristotle. In Section 1, we extract the key pattern of Aristotelian logic needed to understand Fourier's proof, and give it a bit more of a modern formulation. -
Beginning Logic MATH 10130 Spring 2019 University of Notre Dame Contents
Beginning Logic MATH 10130 Spring 2019 University of Notre Dame Contents 0.1 What is logic? What will we do in this course? . .1 I Propositional Logic 5 1 Beginning propositional logic 6 1.1 Symbols . .6 1.2 Well-formed formulas . .7 1.3 Basic translation . .8 1.4 Implications . 11 1.5 Nuances with negations . 12 2 Proofs 13 2.1 Introduction to proofs . 13 2.2 The first rules of inference . 14 2.3 Rule for implications . 20 2.4 Rules for conjunctions . 24 2.5 Rules for disjunctions . 28 2.6 Proof by contradiction . 32 2.7 Bi-conditional statements . 35 2.8 More examples of proofs . 36 2.9 Some useful proofs . 39 3 Truth 48 3.1 Definition of Truth . 48 3.2 Truth tables . 49 3.3 Analysis of arguments using truth tables . 53 4 Soundness and Completeness 56 4.1 Two notions of validity . 56 4.2 Examples: proofs vs. truth tables . 57 4.3 More examples . 63 4.4 Verifying Soundness . 70 4.5 Explanation of Completeness . 72 i II Predicate Logic 74 5 Beginning predicate logic 75 5.1 Shortcomings of propositional logic . 75 5.2 Symbols of predicate logic . 76 5.3 Definition of well-formed formula . 77 5.4 Translation . 82 5.5 Learning the idioms for predicate logic . 84 5.6 Free variables and sentences . 86 6 Proofs 91 6.1 Basic proofs . 91 6.2 Rules for universal quantifiers . 93 6.3 Rules for existential quantifiers . 98 6.4 Rules for equality . 102 7 Structures and Truth 106 7.1 Languages and structures . -
Common Sense for Concurrency and Strong Paraconsistency Using Unstratified Inference and Reflection
Published in ArXiv http://arxiv.org/abs/0812.4852 http://commonsense.carlhewitt.info Common sense for concurrency and strong paraconsistency using unstratified inference and reflection Carl Hewitt http://carlhewitt.info This paper is dedicated to John McCarthy. Abstract Unstratified Reflection is the Norm....................................... 11 Abstraction and Reification .............................................. 11 This paper develops a strongly paraconsistent formalism (called Direct Logic™) that incorporates the mathematics of Diagonal Argument .......................................................... 12 Computer Science and allows unstratified inference and Logical Fixed Point Theorem ........................................... 12 reflection using mathematical induction for almost all of Disadvantages of stratified metatheories ........................... 12 classical logic to be used. Direct Logic allows mutual Reification Reflection ....................................................... 13 reflection among the mutually chock full of inconsistencies Incompleteness Theorem for Theories of Direct Logic ..... 14 code, documentation, and use cases of large software systems Inconsistency Theorem for Theories of Direct Logic ........ 15 thereby overcoming the limitations of the traditional Tarskian Consequences of Logically Necessary Inconsistency ........ 16 framework of stratified metatheories. Concurrency is the Norm ...................................................... 16 Gödel first formalized and proved that it is not possible -
Proofs and Mathematical Reasoning
Proofs and Mathematical Reasoning University of Birmingham Author: Supervisors: Agata Stefanowicz Joe Kyle Michael Grove September 2014 c University of Birmingham 2014 Contents 1 Introduction 6 2 Mathematical language and symbols 6 2.1 Mathematics is a language . .6 2.2 Greek alphabet . .6 2.3 Symbols . .6 2.4 Words in mathematics . .7 3 What is a proof? 9 3.1 Writer versus reader . .9 3.2 Methods of proofs . .9 3.3 Implications and if and only if statements . 10 4 Direct proof 11 4.1 Description of method . 11 4.2 Hard parts? . 11 4.3 Examples . 11 4.4 Fallacious \proofs" . 15 4.5 Counterexamples . 16 5 Proof by cases 17 5.1 Method . 17 5.2 Hard parts? . 17 5.3 Examples of proof by cases . 17 6 Mathematical Induction 19 6.1 Method . 19 6.2 Versions of induction. 19 6.3 Hard parts? . 20 6.4 Examples of mathematical induction . 20 7 Contradiction 26 7.1 Method . 26 7.2 Hard parts? . 26 7.3 Examples of proof by contradiction . 26 8 Contrapositive 29 8.1 Method . 29 8.2 Hard parts? . 29 8.3 Examples . 29 9 Tips 31 9.1 What common mistakes do students make when trying to present the proofs? . 31 9.2 What are the reasons for mistakes? . 32 9.3 Advice to students for writing good proofs . 32 9.4 Friendly reminder . 32 c University of Birmingham 2014 10 Sets 34 10.1 Basics . 34 10.2 Subsets and power sets . 34 10.3 Cardinality and equality . -
Analytic Continuation of Ζ(S) Violates the Law of Non-Contradiction (LNC)
Analytic Continuation of ζ(s) Violates the Law of Non-Contradiction (LNC) Ayal Sharon ∗y July 30, 2019 Abstract The Dirichlet series of ζ(s) was long ago proven to be divergent throughout half-plane Re(s) ≤ 1. If also Riemann’s proposition is true, that there exists an "expression" of ζ(s) that is convergent at all s (except at s = 1), then ζ(s) is both divergent and convergent throughout half-plane Re(s) ≤ 1 (except at s = 1). This result violates all three of Aristotle’s "Laws of Thought": the Law of Identity (LOI), the Law of the Excluded Middle (LEM), and the Law of Non- Contradition (LNC). In classical and intuitionistic logics, the violation of LNC also triggers the "Principle of Explosion" / Ex Contradictione Quodlibet (ECQ). In addition, the Hankel contour used in Riemann’s analytic continuation of ζ(s) violates Cauchy’s integral theorem, providing another proof of the invalidity of Riemann’s ζ(s). Riemann’s ζ(s) is one of the L-functions, which are all in- valid due to analytic continuation. This result renders unsound all theorems (e.g. Modularity, Fermat’s last) and conjectures (e.g. BSD, Tate, Hodge, Yang-Mills) that assume that an L-function (e.g. Riemann’s ζ(s)) is valid. We also show that the Riemann Hypothesis (RH) is not "non-trivially true" in classical logic, intuitionistic logic, or three-valued logics (3VLs) that assign a third truth-value to paradoxes (Bochvar’s 3VL, Priest’s LP ). ∗Patent Examiner, U.S. Patent and Trademark Office (USPTO). -
Glukg Logic and Its Application for Non-Monotonic Reasoning
GLukG logic and its application for Non-Monotonic Reasoning Mauricio Osorio Galindo, Universidad de las Am´ericas - Puebla, Email: osoriomauri@ gmail. com Abstract. We present GLukG, a paraconsistent logic recently intro- duced. We discuss our motivation as well as interesting properties of this logic. We introduce a non-monotonic semantics based on GLukG. 1 Introduction It is well known that monotonic logics can be used to define nonmonotonic semantics [8,7,5] and more recently in [4,17,15,16]. It is also well known that nonmonotonic reasoning (NMR) is useful to model intelligent agents. It has recently been shown that GLukG logic can be used to express interesting non- monotonic semantics [16]. More generally, two major classes of logics that can be successfully used to model nonmonotonic reasoning are (constructive) interme- diate logics and paraconsistent logics [17,15,16]. The most well known semantics for NMR is the stable semantics [6]. This semantics provides a fairly general framework for representing and reasoning with incomplete information. There are programs such as P1: a ← ¬b. a ← b. b ← a: that do not have stable models. This is not exactly a problem of the stable semantics but sometimes we have applications where we need a behavior closer to classical logic such as in argumentation [11]. The stable semantics has been extended to include default negation in the head of the programs (see for instance [19]) and in this case one can construct inconsistent programs such as P2: ¬a. a. b ← a. In this case the stable semantics gives no stable models. The sceptical version of the stable semantics infers every formula in this example. -
2. Methods of Proof 2.1. Types of Proofs. Suppose We Wish to Prove
2. METHODS OF PROOF 69 2. Methods of Proof 2.1. Types of Proofs. Suppose we wish to prove an implication p ! q. Here are some strategies we have available to try. • Trivial Proof: If we know q is true then p ! q is true regardless of the truth value of p. • Vacuous Proof: If p is a conjunction of other hypotheses and we know one or more of these hypotheses is false, then p is false and so p ! q is vacuously true regardless of the truth value of q. • Direct Proof: Assume p, and then use the rules of inference, axioms, defi- nitions, and logical equivalences to prove q. • Indirect Proof or Proof by Contradiction: Assume p and :q and derive a contradiction r ^ :r. • Proof by Contrapositive: (Special case of Proof by Contradiction.) Give a direct proof of :q !:p. Assume :q and then use the rules of inference, axioms, definitions, and logical equivalences to prove :p.(Can be thought of as a proof by contradiction in which you assume p and :q and arrive at the contradiction p ^ :p.) • Proof by Cases: If the hypothesis p can be separated into cases p1 _ p2 _ ···_ pk, prove each of the propositions, p1 ! q, p2 ! q,..., pk ! q, separately. (You may use different methods of proof for different cases.) Discussion We are now getting to the heart of this course: methods you can use to write proofs. Let's investigate the strategies given above in some detail. 2.2. Trivial Proof/Vacuous Proof. Example 2.2.1. -
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.