Against the Unrestricted Applicability of Disjunction Elimination
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Ling 130 Notes: a Guide to Natural Deduction Proofs
Ling 130 Notes: A guide to Natural Deduction proofs Sophia A. Malamud February 7, 2018 1 Strategy summary Given a set of premises, ∆, and the goal you are trying to prove, Γ, there are some simple rules of thumb that will be helpful in finding ND proofs for problems. These are not complete, but will get you through our problem sets. Here goes: Given Delta, prove Γ: 1. Apply the premises, pi in ∆, to prove Γ. Do any other obvious steps. 2. If you need to use a premise (or an assumption, or another resource formula) which is a disjunction (_-premise), then apply Proof By Cases (Disjunction Elimination, _E) rule and prove Γ for each disjunct. 3. Otherwise, work backwards from the type of goal you are proving: (a) If the goal Γ is a conditional (A ! B), then assume A and prove B; use arrow-introduction (Conditional Introduction, ! I) rule. (b) If the goal Γ is a a negative (:A), then assume ::A (or just assume A) and prove con- tradiction; use Reductio Ad Absurdum (RAA, proof by contradiction, Negation Intro- duction, :I) rule. (c) If the goal Γ is a conjunction (A ^ B), then prove A and prove B; use Conjunction Introduction (^I) rule. (d) If the goal Γ is a disjunction (A _ B), then prove one of A or B; use Disjunction Intro- duction (_I) rule. 4. If all else fails, use RAA (proof by contradiction). 2 Using rules for conditionals • Conditional Elimination (modus ponens) (! E) φ ! , φ ` This rule requires a conditional and its antecedent. -
Starting the Dismantling of Classical Mathematics
Australasian Journal of Logic Starting the Dismantling of Classical Mathematics Ross T. Brady La Trobe University Melbourne, Australia [email protected] Dedicated to Richard Routley/Sylvan, on the occasion of the 20th anniversary of his untimely death. 1 Introduction Richard Sylvan (n´eRoutley) has been the greatest influence on my career in logic. We met at the University of New England in 1966, when I was a Master's student and he was one of my lecturers in the M.A. course in Formal Logic. He was an inspirational leader, who thought his own thoughts and was not afraid to speak his mind. I hold him in the highest regard. He was very critical of the standard Anglo-American way of doing logic, the so-called classical logic, which can be seen in everything he wrote. One of his many critical comments was: “G¨odel's(First) Theorem would not be provable using a decent logic". This contribution, written to honour him and his works, will examine this point among some others. Hilbert referred to non-constructive set theory based on classical logic as \Cantor's paradise". In this historical setting, the constructive logic and mathematics concerned was that of intuitionism. (The Preface of Mendelson [2010] refers to this.) We wish to start the process of dismantling this classi- cal paradise, and more generally classical mathematics. Our starting point will be the various diagonal-style arguments, where we examine whether the Law of Excluded Middle (LEM) is implicitly used in carrying them out. This will include the proof of G¨odel'sFirst Theorem, and also the proof of the undecidability of Turing's Halting Problem. -
Qvp) P :: ~~Pp :: (Pvp) ~(P → Q
TEN BASIC RULES OF INFERENCE Negation Introduction (~I – indirect proof IP) Disjunction Introduction (vI – addition ADD) Assume p p Get q & ~q ˫ p v q ˫ ~p Disjunction Elimination (vE – version of CD) Negation Elimination (~E – version of DN) p v q ~~p → p p → r Conditional Introduction (→I – conditional proof CP) q → r Assume p ˫ r Get q Biconditional Introduction (↔I – version of ME) ˫ p → q p → q Conditional Elimination (→E – modus ponens MP) q → p p → q ˫ p ↔ q p Biconditional Elimination (↔E – version of ME) ˫ q p ↔ q Conjunction Introduction (&I – conjunction CONJ) ˫ p → q p or q ˫ q → p ˫ p & q Conjunction Elimination (&E – simplification SIMP) p & q ˫ p IMPORTANT DERIVED RULES OF INFERENCE Modus Tollens (MT) Constructive Dilemma (CD) p → q p v q ~q p → r ˫ ~P q → s Hypothetical Syllogism (HS) ˫ r v s p → q Repeat (RE) q → r p ˫ p → r ˫ p Disjunctive Syllogism (DS) Contradiction (CON) p v q p ~p ~p ˫ q ˫ Any wff Absorption (ABS) Theorem Introduction (TI) p → q Introduce any tautology, e.g., ~(P & ~P) ˫ p → (p & q) EQUIVALENCES De Morgan’s Law (DM) (p → q) :: (~q→~p) ~(p & q) :: (~p v ~q) Material implication (MI) ~(p v q) :: (~p & ~q) (p → q) :: (~p v q) Commutation (COM) Material Equivalence (ME) (p v q) :: (q v p) (p ↔ q) :: [(p & q ) v (~p & ~q)] (p & q) :: (q & p) (p ↔ q) :: [(p → q ) & (q → p)] Association (ASSOC) Exportation (EXP) [p v (q v r)] :: [(p v q) v r] [(p & q) → r] :: [p → (q → r)] [p & (q & r)] :: [(p & q) & r] Tautology (TAUT) Distribution (DIST) p :: (p & p) [p & (q v r)] :: [(p & q) v (p & r)] p :: (p v p) [p v (q & r)] :: [(p v q) & (p v r)] Conditional-Biconditional Refutation Tree Rules Double Negation (DN) ~(p → q) :: (p & ~q) p :: ~~p ~(p ↔ q) :: [(p & ~q) v (~p & q)] Transposition (TRANS) CATEGORICAL SYLLOGISM RULES (e.g., Ǝx(Fx) / ˫ Fy). -
Semantics and Context-Dependence: Towards a Strawsonian Account∗
Semantics and Context-Dependence: Towards a Strawsonian Account∗ Richard G Heck, Jr Brown University Some time in the mid-1990s, I began to encounter variations on the following argument, which was popular with certain of my colleagues and with students who had fallen under their influence. (i) Semantics is about truth-conditions. (ii) Only utterances have truth-conditions. (iii) Hence, a semantic theory must assign truth-conditions to utterances. (iv) Only a theory that incorporated a complete theory of human rationality could assign truth-conditions to utterances. (v) So there is no such thing as a semantic theory (in anything like the usual sense). The argument need not be formulated in terms of truth-conditions. The first premise could equally be stated as: Semantics is about the expression of propositions. The rest of the argument then adapts smoothly. So (i) is meant to be obvious and uncontroversial. With regard to the second premise, it is important to appreciate the force of the word “only”: (ii) asserts that (perhaps with a very few exceptions, such as statements of pure mathematics) sentences never have truth-conditions; only utterances do. So what underwrites (ii) is not just the existence of context-dependence but, rather, its ubiquity. As has become clear over the last few decades, it is not just the obvious expressions—like “I”, “here”, “this”, and the like—whose meaning seems to vary with the circumstances of utterance. All of the following sentences seem as if they could express different propositions on different occasions, due to context-dependence connected with the italicized expressions: • No-one passed the test. -
Logical Verification Course Notes
Logical Verification Course Notes Femke van Raamsdonk [email protected] Vrije Universiteit Amsterdam autumn 2008 Contents 1 1st-order propositional logic 3 1.1 Formulas . 3 1.2 Natural deduction for intuitionistic logic . 4 1.3 Detours in minimal logic . 10 1.4 From intuitionistic to classical logic . 12 1.5 1st-order propositional logic in Coq . 14 2 Simply typed λ-calculus 25 2.1 Types . 25 2.2 Terms . 26 2.3 Substitution . 28 2.4 Beta-reduction . 30 2.5 Curry-Howard-De Bruijn isomorphism . 32 2.6 Coq . 38 3 Inductive types 41 3.1 Expressivity . 41 3.2 Universes of Coq . 44 3.3 Inductive types . 45 3.4 Coq . 48 3.5 Inversion . 50 4 1st-order predicate logic 53 4.1 Terms and formulas . 53 4.2 Natural deduction . 56 4.2.1 Intuitionistic logic . 56 4.2.2 Minimal logic . 60 4.3 Coq . 62 5 Program extraction 67 5.1 Program specification . 67 5.2 Proof of existence . 68 5.3 Program extraction . 68 5.4 Insertion sort . 68 i 1 5.5 Coq . 69 6 λ-calculus with dependent types 71 6.1 Dependent types: introduction . 71 6.2 λP ................................... 75 6.3 Predicate logic in λP ......................... 79 7 Second-order propositional logic 83 7.1 Formulas . 83 7.2 Intuitionistic logic . 85 7.3 Minimal logic . 88 7.4 Classical logic . 90 8 Polymorphic λ-calculus 93 8.1 Polymorphic types: introduction . 93 8.2 λ2 ................................... 94 8.3 Properties of λ2............................ 98 8.4 Expressiveness of λ2........................ -
Borderline Vs. Unknown: Comparing Three-Valued Representations of Imperfect Information Davide Ciucci, Didier Dubois, Jonathan Lawry
Borderline vs. unknown: comparing three-valued representations of imperfect information Davide Ciucci, Didier Dubois, Jonathan Lawry To cite this version: Davide Ciucci, Didier Dubois, Jonathan Lawry. Borderline vs. unknown: comparing three-valued representations of imperfect information. International Journal of Approximate Reasoning, Elsevier, 2014, vol. 55 (n° 9), pp. 1866-1889. 10.1016/j.ijar.2014.07.004. hal-01154064 HAL Id: hal-01154064 https://hal.archives-ouvertes.fr/hal-01154064 Submitted on 21 May 2015 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Open Archive TOULOUSE Archive Ouverte ( OATAO ) OATAO is a n open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse .fr/ Eprints ID : 13234 To link to this article : DOI:10.1016/j.ijar.2014.07.004 URL : http://dx.doi.org/10.1016/j.ijar.2014.07.004 To cite this version : Ciucci, Davide and Dubois, Didier and Lawry, Jonathan Borderline vs. unknown : comparing three-valued representations of imperfect information. (2014) International Journal of Approximate Reasoning, vol. 55 (n° 9). -
Sharp Boundaries and Supervaluationism
Sharp Boundaries and Supervaluationism by JONATHAN JAMES SALISBURY A thesis submitted to The University of Birmingham for the degree of MASTER OF PHILOSOPHY Department of Philosophy, Theology and Religion College of Arts and Law The University of Birmingham December 2010 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. Abstract It is claimed to be a crucial advantage of supervaluationism over other theories of vagueness that it avoids any commitment to sharp boundaries. This thesis will challenge that claim and argue that almost all forms of supervaluationism are committed to infinitely sharp boundaries and that some of these boundaries are interesting enough to be problematic. I shall argue that only iterated supervaluationism can avoid any commitment to sharp boundaries, but on the other hand that is the model that Terrance Horgan has recently argued is a form of transvaluationism and thus logically incoherent. I shall first argue that infinitely higher-order vagueness gives rise to an infinite number of boundaries. I will then argue that an infinite number of these boundaries are, in the case of the vague term ‘tall’, located over a finite range of heights. -
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 ............................................ -
Propositional Logic
Propositional logic Readings: Sections 1.1 and 1.2 of Huth and Ryan. In this module, we will consider propositional logic, which will look familiar to you from Math 135 and CS 251. The difference here is that we first define a formal proof system and practice its use before talking about a semantic interpretation (which will also be familiar) and showing that these two notions coincide. 1 Declarative sentences (1.1) A proposition or declarative sentence is one that can, in principle, be argued as being true or false. Examples: “My car is green” or “Susan was born in Canada”. Many sentences are not declarative, such as “Help!”, “What time is it?”, or “Get me something to eat.” The declarative sentences above are atomic; they cannot be decomposed further. A sentence like “My car is green AND you do not have a car” is a compound sentence or compositional sentence. 2 To clarify the manipulations we perform in logical proofs, we will represent declarative sentences symbolically by atoms such as p, q, r. (We avoid t, f , T , F for reasons which will become evident.) Compositional sentences will be represented by formulas, which combine atoms with connectives. Formulas are intended to symbolically represent statements in the type of mathematical or logical reasoning we have done in the past. Our standard set of connectives will be , , , and . (In Math : ^ _ ! 135, you also used , which we will not use.) Soon, we will $ describe the set of formulas as a formal language; for the time being, we use an informal description. -
Isabelle for Philosophers∗
Isabelle for Philosophers∗ Ben Blumson September 20, 2019 It is unworthy of excellent men to lose hours like slaves in the labour of calculation which could safely be relegated to anyone else if machines were used. Liebniz [11] p. 181. This is an introduction to the Isabelle proof assistant aimed at philosophers and students of philosophy.1 1 Propositional Logic Imagine you are caught in an air raid in the Second World War. You might reason as follows: Either I will be killed in this raid or I will not be killed. Suppose that I will. Then even if I take precautions, I will be killed, so any precautions I take will be ineffective. But suppose I am not going to be killed. Then I won't be killed even if I neglect all precautions; so on this assumption, no precautions ∗This draft is based on notes for students in my paradoxes and honours metaphysics classes { I'm grateful to the students for their help, especially Mark Goh, Zhang Jiang, Kee Wei Loo and Joshua Thong. I've also benefitted from discussion or correspondence on these issues with Zach Barnett, Sam Baron, David Braddon-Mitchell, Olivier Danvy, Paul Oppenheimer, Bruno Woltzenlogel Paleo, Michael Pelczar, David Ripley, Divyanshu Sharma, Manikaran Singh, Neil Sinhababu and Weng Hong Tang. 1I found a very useful introduction to be Nipkow [8]. Another still helpful, though unfortunately dated, introduction is Grechuk [6]. A person wishing to know how Isabelle works might first consult Paulson [9]. For the software itself and comprehensive docu- mentation, see https://isabelle.in.tum.de/. -
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 . -
Vagueness and Propositional Content
VAGUENESS AND PROPOSITIONAL CONTENT by BENJAMIN ROHRS B.A., Biola University, 2008 M.A., Northern Illinois University, 2010 A dissertation submitted to the Faculty of the Graduate School of the University of Colorado in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Philosophy 2016 This thesis entitled: Vagueness and Propositional Content written by Benjamin Wayne Rohrs has been approved for the Department of Philosophy Graeme Forbes Graham Oddie Martha Palmer Raul Saucedo Michael Tooley Date The final copy of this thesis has been examined by the signatories, and we find that both the content and the form meet acceptable presentation standards of scholarly work in the above mentioned discipline. ii ABSTRACT Rohrs, Benjamin Wayne (Ph.D., Department of Philosophy) Vagueness and Propositional Content Thesis directed by Professor Graeme Forbes. This dissertation investigates the propositional content of vague sentences. It is a study in analytic metaphysics and analytic philosophy of language. A standard view in those sub-fields is that the content of a sentence is the proposition it expresses. For example, the English sentence ‘Snow is white’ and the German sentence ‘Schnee ist weiss’ have the same content because each expresses the proposition that snow is white. It is also standard to assume that propositions are bivalent, which is to say that any proposition P is either true or false in every possible case. However, these assumptions are called into question when we consider the phenomenon of vagueness. Sentences such as, ‘John is an adult’, ‘Johanna is tall’, and ‘This avocado is ripe’, admit of borderline cases in which they are neither clearly true nor clearly false.