Natural Deduction
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Classifying Material Implications Over Minimal Logic
Classifying Material Implications over Minimal Logic Hannes Diener and Maarten McKubre-Jordens March 28, 2018 Abstract The so-called paradoxes of material implication have motivated the development of many non- classical logics over the years [2–5, 11]. In this note, we investigate some of these paradoxes and classify them, over minimal logic. We provide proofs of equivalence and semantic models separating the paradoxes where appropriate. A number of equivalent groups arise, all of which collapse with unrestricted use of double negation elimination. Interestingly, the principle ex falso quodlibet, and several weaker principles, turn out to be distinguishable, giving perhaps supporting motivation for adopting minimal logic as the ambient logic for reasoning in the possible presence of inconsistency. Keywords: reverse mathematics; minimal logic; ex falso quodlibet; implication; paraconsistent logic; Peirce’s principle. 1 Introduction The project of constructive reverse mathematics [6] has given rise to a wide literature where various the- orems of mathematics and principles of logic have been classified over intuitionistic logic. What is less well-known is that the subtle difference that arises when the principle of explosion, ex falso quodlibet, is dropped from intuitionistic logic (thus giving (Johansson’s) minimal logic) enables the distinction of many more principles. The focus of the present paper are a range of principles known collectively (but not exhaustively) as the paradoxes of material implication; paradoxes because they illustrate that the usual interpretation of formal statements of the form “. → . .” as informal statements of the form “if. then. ” produces counter-intuitive results. Some of these principles were hinted at in [9]. Here we present a carefully worked-out chart, classifying a number of such principles over minimal logic. -
Proof Theory Can Be Viewed As the General Study of Formal Deductive Systems
Proof Theory Jeremy Avigad December 19, 2017 Abstract Proof theory began in the 1920’s as a part of Hilbert’s program, which aimed to secure the foundations of mathematics by modeling infinitary mathematics with formal axiomatic systems and proving those systems consistent using restricted, finitary means. The program thus viewed mathematics as a system of reasoning with precise linguistic norms, governed by rules that can be described and studied in concrete terms. Today such a viewpoint has applications in mathematics, computer science, and the philosophy of mathematics. Keywords: proof theory, Hilbert’s program, foundations of mathematics 1 Introduction At the turn of the nineteenth century, mathematics exhibited a style of argumentation that was more explicitly computational than is common today. Over the course of the century, the introduction of abstract algebraic methods helped unify developments in analysis, number theory, geometry, and the theory of equations, and work by mathematicians like Richard Dedekind, Georg Cantor, and David Hilbert towards the end of the century introduced set-theoretic language and infinitary methods that served to downplay or suppress computational content. This shift in emphasis away from calculation gave rise to concerns as to whether such methods were meaningful and appropriate in mathematics. The discovery of paradoxes stemming from overly naive use of set-theoretic language and methods led to even more pressing concerns as to whether the modern methods were even consistent. This led to heated debates in the early twentieth century and what is sometimes called the “crisis of foundations.” In lectures presented in 1922, Hilbert launched his Beweistheorie, or Proof Theory, which aimed to justify the use of modern methods and settle the problem of foundations once and for all. -
On Basic Probability Logic Inequalities †
mathematics Article On Basic Probability Logic Inequalities † Marija Boriˇci´cJoksimovi´c Faculty of Organizational Sciences, University of Belgrade, Jove Ili´ca154, 11000 Belgrade, Serbia; [email protected] † The conclusions given in this paper were partially presented at the European Summer Meetings of the Association for Symbolic Logic, Logic Colloquium 2012, held in Manchester on 12–18 July 2012. Abstract: We give some simple examples of applying some of the well-known elementary probability theory inequalities and properties in the field of logical argumentation. A probabilistic version of the hypothetical syllogism inference rule is as follows: if propositions A, B, C, A ! B, and B ! C have probabilities a, b, c, r, and s, respectively, then for probability p of A ! C, we have f (a, b, c, r, s) ≤ p ≤ g(a, b, c, r, s), for some functions f and g of given parameters. In this paper, after a short overview of known rules related to conjunction and disjunction, we proposed some probabilized forms of the hypothetical syllogism inference rule, with the best possible bounds for the probability of conclusion, covering simultaneously the probabilistic versions of both modus ponens and modus tollens rules, as already considered by Suppes, Hailperin, and Wagner. Keywords: inequality; probability logic; inference rule MSC: 03B48; 03B05; 60E15; 26D20; 60A05 1. Introduction The main part of probabilization of logical inference rules is defining the correspond- Citation: Boriˇci´cJoksimovi´c,M. On ing best possible bounds for probabilities of propositions. Some of them, connected with Basic Probability Logic Inequalities. conjunction and disjunction, can be obtained immediately from the well-known Boole’s Mathematics 2021, 9, 1409. -
7.1 Rules of Implication I
Natural Deduction is a method for deriving the conclusion of valid arguments expressed in the symbolism of propositional logic. The method consists of using sets of Rules of Inference (valid argument forms) to derive either a conclusion or a series of intermediate conclusions that link the premises of an argument with the stated conclusion. The First Four Rules of Inference: ◦ Modus Ponens (MP): p q p q ◦ Modus Tollens (MT): p q ~q ~p ◦ Pure Hypothetical Syllogism (HS): p q q r p r ◦ Disjunctive Syllogism (DS): p v q ~p q Common strategies for constructing a proof involving the first four rules: ◦ Always begin by attempting to find the conclusion in the premises. If the conclusion is not present in its entirely in the premises, look at the main operator of the conclusion. This will provide a clue as to how the conclusion should be derived. ◦ If the conclusion contains a letter that appears in the consequent of a conditional statement in the premises, consider obtaining that letter via modus ponens. ◦ If the conclusion contains a negated letter and that letter appears in the antecedent of a conditional statement in the premises, consider obtaining the negated letter via modus tollens. ◦ If the conclusion is a conditional statement, consider obtaining it via pure hypothetical syllogism. ◦ If the conclusion contains a letter that appears in a disjunctive statement in the premises, consider obtaining that letter via disjunctive syllogism. Four Additional Rules of Inference: ◦ Constructive Dilemma (CD): (p q) • (r s) p v r q v s ◦ Simplification (Simp): p • q p ◦ Conjunction (Conj): p q p • q ◦ Addition (Add): p p v q Common Misapplications Common strategies involving the additional rules of inference: ◦ If the conclusion contains a letter that appears in a conjunctive statement in the premises, consider obtaining that letter via simplification. -
Systematic Construction of Natural Deduction Systems for Many-Valued Logics
23rd International Symposium on Multiple Valued Logic. Sacramento, CA, May 1993 Proceedings. (IEEE Press, Los Alamitos, 1993) pp. 208{213 Systematic Construction of Natural Deduction Systems for Many-valued Logics Matthias Baaz∗ Christian G. Ferm¨ullery Richard Zachy Technische Universit¨atWien, Austria Abstract sion.) Each position i corresponds to one of the truth values, vm is the distinguished truth value. The in- A construction principle for natural deduction sys- tended meaning is as follows: Derive that at least tems for arbitrary finitely-many-valued first order log- one formula of Γm takes the value vm under the as- ics is exhibited. These systems are systematically ob- sumption that no formula in Γi takes the value vi tained from sequent calculi, which in turn can be au- (1 i m 1). ≤ ≤ − tomatically extracted from the truth tables of the log- Our starting point for the construction of natural ics under consideration. Soundness and cut-free com- deduction systems are sequent calculi. (A sequent is pleteness of these sequent calculi translate into sound- a tuple Γ1 ::: Γm, defined to be satisfied by an ness, completeness and normal form theorems for the interpretationj iffj for some i 1; : : : ; m at least one 2 f g natural deduction systems. formula in Γi takes the truth value vi.) For each pair of an operator 2 or quantifier Q and a truth value vi 1 Introduction we construct a rule introducing a formula of the form 2(A ;:::;A ) or (Qx)A(x), respectively, at position i The study of natural deduction systems for many- 1 n of a sequent. -
Propositional Logic (PDF)
Mathematics for Computer Science Proving Validity 6.042J/18.062J Instead of truth tables, The Logic of can try to prove valid formulas symbolically using Propositions axioms and deduction rules Albert R Meyer February 14, 2014 propositional logic.1 Albert R Meyer February 14, 2014 propositional logic.2 Proving Validity Algebra for Equivalence The text describes a for example, bunch of algebraic rules to the distributive law prove that propositional P AND (Q OR R) ≡ formulas are equivalent (P AND Q) OR (P AND R) Albert R Meyer February 14, 2014 propositional logic.3 Albert R Meyer February 14, 2014 propositional logic.4 1 Algebra for Equivalence Algebra for Equivalence for example, The set of rules for ≡ in DeMorgan’s law the text are complete: ≡ NOT(P AND Q) ≡ if two formulas are , these rules can prove it. NOT(P) OR NOT(Q) Albert R Meyer February 14, 2014 propositional logic.5 Albert R Meyer February 14, 2014 propositional logic.6 A Proof System A Proof System Another approach is to Lukasiewicz’ proof system is a start with some valid particularly elegant example of this idea. formulas (axioms) and deduce more valid formulas using proof rules Albert R Meyer February 14, 2014 propositional logic.7 Albert R Meyer February 14, 2014 propositional logic.8 2 A Proof System Lukasiewicz’ Proof System Lukasiewicz’ proof system is a Axioms: particularly elegant example of 1) (¬P → P) → P this idea. It covers formulas 2) P → (¬P → Q) whose only logical operators are 3) (P → Q) → ((Q → R) → (P → R)) IMPLIES (→) and NOT. The only rule: modus ponens Albert R Meyer February 14, 2014 propositional logic.9 Albert R Meyer February 14, 2014 propositional logic.10 Lukasiewicz’ Proof System Lukasiewicz’ Proof System Prove formulas by starting with Prove formulas by starting with axioms and repeatedly applying axioms and repeatedly applying the inference rule. -
Chapter 9: Answers and Comments Step 1 Exercises 1. Simplification. 2. Absorption. 3. See Textbook. 4. Modus Tollens. 5. Modus P
Chapter 9: Answers and Comments Step 1 Exercises 1. Simplification. 2. Absorption. 3. See textbook. 4. Modus Tollens. 5. Modus Ponens. 6. Simplification. 7. X -- A very common student mistake; can't use Simplification unless the major con- nective of the premise is a conjunction. 8. Disjunctive Syllogism. 9. X -- Fallacy of Denying the Antecedent. 10. X 11. Constructive Dilemma. 12. See textbook. 13. Hypothetical Syllogism. 14. Hypothetical Syllogism. 15. Conjunction. 16. See textbook. 17. Addition. 18. Modus Ponens. 19. X -- Fallacy of Affirming the Consequent. 20. Disjunctive Syllogism. 21. X -- not HS, the (D v G) does not match (D v C). This is deliberate to make sure you don't just focus on generalities, and make sure the entire form fits. 22. Constructive Dilemma. 23. See textbook. 24. Simplification. 25. Modus Ponens. 26. Modus Tollens. 27. See textbook. 28. Disjunctive Syllogism. 29. Modus Ponens. 30. Disjunctive Syllogism. Step 2 Exercises #1 1 Z A 2. (Z v B) C / Z C 3. Z (1)Simp. 4. Z v B (3) Add. 5. C (2)(4)MP 6. Z C (3)(5) Conj. For line 4 it is easy to get locked into line 2 and strategy 1. But they do not work. #2 1. K (B v I) 2. K 3. ~B 4. I (~T N) 5. N T / ~N 6. B v I (1)(2) MP 7. I (6)(3) DS 8. ~T N (4)(7) MP 9. ~T (8) Simp. 10. ~N (5)(9) MT #3 See textbook. #4 1. H I 2. I J 3. -
Complexities of Proof-Theoretical Reductions
Complexities of Proof-Theoretical Reductions Michael Toppel Submitted in accordance with the requirements for the degree of Doctor of Philosophy The University of Leeds Department of Pure Mathematics September 2016 iii The candidate confirms that the work submitted is his own and that appropriate credit has been given where reference has been made to the work of others. This copy has been supplied on the understanding that it is copyright material and that no quotation from the thesis may be published without proper acknowledgement. c 2016 The University of Leeds and Michael Toppel iv v Abstract The present thesis is a contribution to a project that is carried out by Michael Rathjen 0 and Andreas Weiermann to give a general method to study the proof-complexity of Σ1- sentences. This general method uses the generalised ordinal-analysis that was given by Buchholz, Ruede¨ and Strahm in [5] and [44] as well as the generalised characterisation of provable-recursive functions of PA + TI(≺ α) that was given by Weiermann in [60]. The present thesis links these two methods by giving an explicit elementary bound for the i proof-complexity increment that occurs after the transition from the theory IDc ! + TI(≺ α), which was used by Ruede¨ and Strahm, to the theory PA + TI(≺ α), which was analysed by Weiermann. vi vii Contents Abstract . v Contents . vii Introduction 1 1 Justifying the use of Multi-Conclusion Sequents 5 1.1 Introduction . 5 1.2 A Gentzen-semantics . 8 1.3 Multi-Conclusion Sequents . 15 1.4 Comparison with other Positions and Responses to Objections . -
Argument Forms and Fallacies
6.6 Common Argument Forms and Fallacies 1. Common Valid Argument Forms: In the previous section (6.4), we learned how to determine whether or not an argument is valid using truth tables. There are certain forms of valid and invalid argument that are extremely common. If we memorize some of these common argument forms, it will save us time because we will be able to immediately recognize whether or not certain arguments are valid or invalid without having to draw out a truth table. Let’s begin: 1. Disjunctive Syllogism: The following argument is valid: “The coin is either in my right hand or my left hand. It’s not in my right hand. So, it must be in my left hand.” Let “R”=”The coin is in my right hand” and let “L”=”The coin is in my left hand”. The argument in symbolic form is this: R ˅ L ~R __________________________________________________ L Any argument with the form just stated is valid. This form of argument is called a disjunctive syllogism. Basically, the argument gives you two options and says that, since one option is FALSE, the other option must be TRUE. 2. Pure Hypothetical Syllogism: The following argument is valid: “If you hit the ball in on this turn, you’ll get a hole in one; and if you get a hole in one you’ll win the game. So, if you hit the ball in on this turn, you’ll win the game.” Let “B”=”You hit the ball in on this turn”, “H”=”You get a hole in one”, and “W”=”you win the game”. -
An Integration of Resolution and Natural Deduction Theorem Proving
From: AAAI-86 Proceedings. Copyright ©1986, AAAI (www.aaai.org). All rights reserved. An Integration of Resolution and Natural Deduction Theorem Proving Dale Miller and Amy Felty Computer and Information Science University of Pennsylvania Philadelphia, PA 19104 Abstract: We present a high-level approach to the integra- ble of translating between them. In order to achieve this goal, tion of such different theorem proving technologies as resolution we have designed a programming language which permits proof and natural deduction. This system represents natural deduc- structures as values and types. This approach builds on and ex- tion proofs as X-terms and resolution refutations as the types of tends the LCF approach to natural deduction theorem provers such X-terms. These type structures, called ezpansion trees, are by replacing the LCF notion of a uakfation with explicit term essentially formulas in which substitution terms are attached to representation of proofs. The terms which represent proofs are quantifiers. As such, this approach to proofs and their types ex- given types which generalize the formulas-as-type notion found tends the formulas-as-type notion found in proof theory. The in proof theory [Howard, 19691. Resolution refutations are seen LCF notion of tactics and tacticals can also be extended to in- aa specifying the type of a natural deduction proofs. This high corporate proofs as typed X-terms. Such extended tacticals can level view of proofs as typed terms can be easily combined with be used to program different interactive and automatic natural more standard aspects of LCF to yield the integration for which Explicit representation of proofs deduction theorem provers. -
Natural Deduction and the Curry-Howard-Isomorphism
Natural Deduction and the Curry-Howard-Isomorphism Andreas Abel August 2016 Abstract We review constructive propositional logic and natural deduction and connect it to the simply-typed lambda-calculus with the Curry- Howard Isomorphism. Constructive Logic A fundamental property of constructive logic is the disjunction property: If the disjunction A _ B is provable, then either A is provable or B is provable. This property is not compatible with the principle of the excluded middle (tertium non datur), which states that A _:A holds for any proposition A. While each fool can state the classical tautology \aliens exist or don't", this certainly does not give us a means to decide whether aliens exist or not. A constructive proof of the fool's statement would require either showcasing an alien or a stringent argument for the impossibility of their existence.1 1 Natural deduction for propositional logic The proof calculus of natural deduction goes back to Gentzen[1935]. 1 For a more mathematical example of undecidability, refer to the continuum hypothesis CH which states that no cardinal exists between the set of the natural numbers and the set of reals. It is independent of ZFC, Zermelo-Fr¨ankel set theory with the axiom of choice, meaning that in ZFC, neither CH nor :CH is provable. 1 1.1 Propositions Formulæ of propositional logic are given by the following grammar: P; Q atomic proposition A; B; C ::= P j A ) B implication j A ^ B j > conjunction, truth j A _ B j ? disjunction, absurdity Even though we write formulas in linearized (string) form, we think of them as (abstract syntax) trees. -
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.