Metalogic Notes Saverio Perugini University of Dayton, [email protected]
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“The Church-Turing “Thesis” As a Special Corollary of Gödel's
“The Church-Turing “Thesis” as a Special Corollary of Gödel’s Completeness Theorem,” in Computability: Turing, Gödel, Church, and Beyond, B. J. Copeland, C. Posy, and O. Shagrir (eds.), MIT Press (Cambridge), 2013, pp. 77-104. Saul A. Kripke This is the published version of the book chapter indicated above, which can be obtained from the publisher at https://mitpress.mit.edu/books/computability. It is reproduced here by permission of the publisher who holds the copyright. © The MIT Press The Church-Turing “ Thesis ” as a Special Corollary of G ö del ’ s 4 Completeness Theorem 1 Saul A. Kripke Traditionally, many writers, following Kleene (1952) , thought of the Church-Turing thesis as unprovable by its nature but having various strong arguments in its favor, including Turing ’ s analysis of human computation. More recently, the beauty, power, and obvious fundamental importance of this analysis — what Turing (1936) calls “ argument I ” — has led some writers to give an almost exclusive emphasis on this argument as the unique justification for the Church-Turing thesis. In this chapter I advocate an alternative justification, essentially presupposed by Turing himself in what he calls “ argument II. ” The idea is that computation is a special form of math- ematical deduction. Assuming the steps of the deduction can be stated in a first- order language, the Church-Turing thesis follows as a special case of G ö del ’ s completeness theorem (first-order algorithm theorem). I propose this idea as an alternative foundation for the Church-Turing thesis, both for human and machine computation. Clearly the relevant assumptions are justified for computations pres- ently known. -
Revisiting Gödel and the Mechanistic Thesis Alessandro Aldini, Vincenzo Fano, Pierluigi Graziani
Theory of Knowing Machines: Revisiting Gödel and the Mechanistic Thesis Alessandro Aldini, Vincenzo Fano, Pierluigi Graziani To cite this version: Alessandro Aldini, Vincenzo Fano, Pierluigi Graziani. Theory of Knowing Machines: Revisiting Gödel and the Mechanistic Thesis. 3rd International Conference on History and Philosophy of Computing (HaPoC), Oct 2015, Pisa, Italy. pp.57-70, 10.1007/978-3-319-47286-7_4. hal-01615307 HAL Id: hal-01615307 https://hal.inria.fr/hal-01615307 Submitted on 12 Oct 2017 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. Distributed under a Creative Commons Attribution| 4.0 International License Theory of Knowing Machines: Revisiting G¨odeland the Mechanistic Thesis Alessandro Aldini1, Vincenzo Fano1, and Pierluigi Graziani2 1 University of Urbino \Carlo Bo", Urbino, Italy falessandro.aldini, [email protected] 2 University of Chieti-Pescara \G. D'Annunzio", Chieti, Italy [email protected] Abstract. Church-Turing Thesis, mechanistic project, and G¨odelian Arguments offer different perspectives of informal intuitions behind the relationship existing between the notion of intuitively provable and the definition of decidability by some Turing machine. One of the most for- mal lines of research in this setting is represented by the theory of know- ing machines, based on an extension of Peano Arithmetic, encompassing an epistemic notion of knowledge formalized through a modal operator denoting intuitive provability. -
Church's Thesis and the Conceptual Analysis of Computability
Church’s Thesis and the Conceptual Analysis of Computability Michael Rescorla Abstract: Church’s thesis asserts that a number-theoretic function is intuitively computable if and only if it is recursive. A related thesis asserts that Turing’s work yields a conceptual analysis of the intuitive notion of numerical computability. I endorse Church’s thesis, but I argue against the related thesis. I argue that purported conceptual analyses based upon Turing’s work involve a subtle but persistent circularity. Turing machines manipulate syntactic entities. To specify which number-theoretic function a Turing machine computes, we must correlate these syntactic entities with numbers. I argue that, in providing this correlation, we must demand that the correlation itself be computable. Otherwise, the Turing machine will compute uncomputable functions. But if we presuppose the intuitive notion of a computable relation between syntactic entities and numbers, then our analysis of computability is circular.1 §1. Turing machines and number-theoretic functions A Turing machine manipulates syntactic entities: strings consisting of strokes and blanks. I restrict attention to Turing machines that possess two key properties. First, the machine eventually halts when supplied with an input of finitely many adjacent strokes. Second, when the 1 I am greatly indebted to helpful feedback from two anonymous referees from this journal, as well as from: C. Anthony Anderson, Adam Elga, Kevin Falvey, Warren Goldfarb, Richard Heck, Peter Koellner, Oystein Linnebo, Charles Parsons, Gualtiero Piccinini, and Stewart Shapiro. I received extremely helpful comments when I presented earlier versions of this paper at the UCLA Philosophy of Mathematics Workshop, especially from Joseph Almog, D. -
5 Propositional Logic: Consistency and Completeness
5 Propositional Logic: Consistency and completeness Reading: Metalogic Part II, 24, 15, 28-31 Contents 5.1 Soundness . 61 5.2 Consistency . 62 5.3 Completeness . 63 5.3.1 An Axiomatization of Propositional Logic . 63 5.3.2 Kalmar's Proof: Informal Exposition . 66 5.3.3 Kalmar's Proof . 68 5.4 Homework Exercises . 70 5.4.1 Questions . 70 5.4.2 Answers . 70 5.1 Soundness In this section, we establish the soundness of the system, i.e., Theorem 3 (Soundness). Every theorem is a tautology, i.e., If ` A then j= A. Proof The proof is by induction the length of the proof of A. For the Basis step, we show that each of the axioms is a tautology. For the induction step, we show that if A and A ⊃ B are tautologies, then B is a tautology. Case 1 (PS1): AB B ⊃ A (A ⊃ (B ⊃ A)) TT TT TF TT FT FT FF TT Case 2 (PS2) 62 5 Propositional Logic: Consistency and completeness XYZ ABC B ⊃ C A ⊃ (B ⊃ C) A ⊃ B A ⊃ C Y ⊃ ZX ⊃ (Y ⊃ Z) TTT TTTTTT TTF FFTFFT TFT TTFTTT TFF TTFFTT FTT TTTTTT FTF FTTTTT FFT TTTTTT FFF TTTTTT Case 3 (PS3) AB » B » A » B ⊃∼ A A ⊃ B (» B ⊃∼ A) ⊃ (A ⊃ B) TT FFTTT TF TFFFT FT FTTTT FF TTTTT Case 4 (MP). If A is a tautology, i.e., true for every assignment of truth values to the atomic letters, and if A ⊃ B is a tautology, then there is no assignment which makes A T and B F. -
An Un-Rigorous Introduction to the Incompleteness Theorems∗
An un-rigorous introduction to the incompleteness theorems∗ phil 43904 Jeff Speaks October 8, 2007 1 Soundness and completeness When discussing Russell's logical system and its relation to Peano's axioms of arithmetic, we distinguished between the axioms of Russell's system, and the theorems of that system. Roughly, the axioms of a theory are that theory's basic assumptions, and the theorems are the formulae provable from the axioms using the rules provided by the theory. Suppose we are talking about the theory A of arithmetic. Then, if we express the idea that a certain sentence p is a theorem of A | i.e., provable from A's axioms | as follows: `A p Now we can introduce the notion of the valid sentences of a theory. For our purposes, think of a valid sentence as a sentence in the language of the theory that can't be false. For example, consider a simple logical language which contains some predicates (written as upper-case letters), `not', `&', and some names, each of which is assigned some object or other in each interpretation. Now consider a sentence like F n In most cases, a sentence like this is going to be true on some interpretations, and false in others | it depends on which object is assigned to `n', and whether it is in the set of things assigned to `F '. However, if we consider a sentence like ∗The source for much of what follows is Michael Detlefsen's (much less un-rigorous) “G¨odel'stheorems", available at http://www.rep.routledge.com/article/Y005. -
Rules of Replacement II, §7.4
Philosophy 109, Modern Logic, Queens College Russell Marcus, Instructor email: [email protected] website: http://philosophy.thatmarcusfamily.org Office phone: (718) 997-5287 Rules of Replacement II, §7.4 I. The Last Five Rules of Replacement See the appendix at the end of the lesson for truth tables proving equivalence for each. Transposition (Trans) P e Q :: -Q e -P You may switch the antecedent and consequent of a conditional statement, as long as you negate (or un-negate) both. Often used with (HS). Also, traditionally, called the ‘contrapositive’. Sample Derivation: 1. A e B 2. D e -B / A e -D 3. --B e -D 2, Trans 4. A e -D 1, 3, DN, HS QED Transposition can be tricky when only one term is negated: A e -B becomes, by Trans: --B e -A which becomes, by DN B e -A Equivalently, but doing the double negation first: A e -B becomes, by DN: --A e -B becomes, by Trans: B e -A Either way, you can include the DN on the line with Trans. Material Implication (Impl) P e Q :: -P w Q Implication allows you to change a statement from a disjunction to a conditional, or vice versa. It’s often easier to work with disjunctions. You can use (DM) to get conjunctions. You may be able to use distribution, which doesn’t apply to conditionals. On the other hand, sometimes, you just want to work with conditionals. You can use (HS) and (MP). Proofs are overdetermined by our system - there are many ways to do them. -
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. -
Epistemological Consequences of the Incompleteness Theorems
Epistemological Consequences of the Incompleteness Theorems Giuseppe Raguní UCAM - Universidad Católica de Murcia, Avenida Jerónimos 135, Guadalupe 30107, Murcia, Spain - [email protected] After highlighting the cases in which the semantics of a language cannot be mechanically reproduced (in which case it is called inherent), the main episte- mological consequences of the first incompleteness Theorem for the two funda- mental arithmetical theories are shown: the non-mechanizability for the truths of the first-order arithmetic and the peculiarities for the model of the second- order arithmetic. Finally, the common epistemological interpretation of the second incompleteness Theorem is corrected, proposing the new Metatheorem of undemonstrability of internal consistency. KEYWORDS: semantics, languages, epistemology, paradoxes, arithmetic, in- completeness, first-order, second-order, consistency. 1 Semantics in the Languages Consider an arbitrary language that, as normally, makes use of a countable1 number of characters. Combining these characters in certain ways, are formed some fundamental strings that we call terms of the language: those collected in a dictionary. When the terms are semantically interpreted, i. e. a certain meaning is assigned to them, we have their distinction in adjectives, nouns, verbs, etc. Then, a proper grammar establishes the rules arXiv:1602.03390v1 [math.GM] 13 Jan 2016 of formation of sentences. While the terms are finite, the combinations of grammatically allowed terms form an infinite-countable amount of possible sentences. In a non-trivial language, the meaning associated to each term, and thus to each ex- pression that contains it, is not always unique. The same sentence can enunciate different things, so representing different propositions. -
Completeness of the Propositions-As-Types Interpretation of Intuitionistic Logic Into Illative Combinatory Logic
University of Wollongong Research Online Faculty of Engineering and Information Faculty of Engineering and Information Sciences - Papers: Part A Sciences 1-1-1998 Completeness of the propositions-as-types interpretation of intuitionistic logic into illative combinatory logic Wil Dekkers Catholic University, Netherlands Martin Bunder University of Wollongong, [email protected] Henk Barendregt Catholic University, Netherlands Follow this and additional works at: https://ro.uow.edu.au/eispapers Part of the Engineering Commons, and the Science and Technology Studies Commons Recommended Citation Dekkers, Wil; Bunder, Martin; and Barendregt, Henk, "Completeness of the propositions-as-types interpretation of intuitionistic logic into illative combinatory logic" (1998). Faculty of Engineering and Information Sciences - Papers: Part A. 1883. https://ro.uow.edu.au/eispapers/1883 Research Online is the open access institutional repository for the University of Wollongong. For further information contact the UOW Library: [email protected] Completeness of the propositions-as-types interpretation of intuitionistic logic into illative combinatory logic Abstract Illative combinatory logic consists of the theory of combinators or lambda calculus extended by extra constants (and corresponding axioms and rules) intended to capture inference. In a preceding paper, [2], we considered 4 systems of illative combinatory logic that are sound for first order intuitionistic prepositional and predicate logic. The interpretation from ordinary logic into the illative systems can be done in two ways: following the propositions-as-types paradigm, in which derivations become combinators, or in a more direct way, in which derivations are not translated. Both translations are closely related in a canonical way. In the cited paper we proved completeness of the two direct translations. -
A Conceptual Framework for Investigating Organizational Control and Resistance in Crowd-Based Platforms
Proceedings of the 50th Hawaii International Conference on System Sciences | 2017 A Conceptual Framework for Investigating Organizational Control and Resistance in Crowd-Based Platforms David A. Askay California Polytechnic State University [email protected] Abstract Crowd-based platforms coordinate action through This paper presents a research agenda for crowd decomposing tasks and encouraging individuals to behavior research by drawing from the participate by providing intrinsic (e.g., fun, organizational control literature. It addresses the enjoyment) and/or extrinsic (e.g., status, money, need for research into the organizational and social social interaction, etc.) motivators [3]. Three recent structures that guide user behavior and contributions Information Systems (IS) reviews of crowdsourcing in crowd-based platforms. Crowd behavior is research [6, 4, 7] emphasize the importance of situated within a conceptual framework of designing effective incentive systems. However, organizational control. This framework helps research on motivation is somewhat disparate, with scholars more fully articulate the full range of various categorizations and often inconsistent control mechanisms operating in crowd-based findings as to which incentives are the most effective platforms, contextualizes these mechanisms into the [4]. Moreover, this approach can be limited by its context of crowd-based platforms, challenges existing often deterministic and rational assumptions of user rational assumptions about incentive systems, and behavior and motivation, which overlooks normative clarifies theoretical constructs of organizational and social aspects of human behavior [8]. To more control to foster stronger integration between fully understand the dynamics of crowd behavior and information systems research and organizational and governance of crowd-based projects, IS researchers management science. -
Bundled Fragments of First-Order Modal Logic: (Un)Decidability
Bundled Fragments of First-Order Modal Logic: (Un)Decidability Anantha Padmanabha Institute of Mathematical Sciences, HBNI, Chennai, India [email protected] https://orcid.org/0000-0002-4265-5772 R Ramanujam Institute of Mathematical Sciences, HBNI, Chennai, India [email protected] Yanjing Wang Department of Philosophy, Peking University, Beijing, China [email protected] Abstract Quantified modal logic is notorious for being undecidable, with very few known decidable frag- ments such as the monodic ones. For instance, even the two-variable fragment over unary predic- ates is undecidable. In this paper, we study a particular fragment, namely the bundled fragment, where a first-order quantifier is always followed by a modality when occurring in the formula, inspired by the proposal of [15] in the context of non-standard epistemic logics of know-what, know-how, know-why, and so on. As always with quantified modal logics, it makes a significant difference whether the domain stays the same across possible worlds. In particular, we show that the predicate logic with the bundle ∀ alone is undecidable over constant domain interpretations, even with only monadic predicates, whereas having the ∃ bundle instead gives us a decidable logic. On the other hand, over increasing domain interpretations, we get decidability with both ∀ and ∃ bundles with unrestricted predicates, where we obtain tableau based procedures that run in PSPACE. We further show that the ∃ bundle cannot distinguish between constant domain and variable domain interpretations. 2012 ACM Subject Classification Theory of computation → Modal and temporal logics Keywords and phrases First-order modal logic, decidability, bundled fragments Digital Object Identifier 10.4230/LIPIcs.FSTTCS.2018.43 Acknowledgements We thank the reviewers for the insightful and helpful comments. -
John P. Burgess Department of Philosophy Princeton University Princeton, NJ 08544-1006, USA [email protected]
John P. Burgess Department of Philosophy Princeton University Princeton, NJ 08544-1006, USA [email protected] LOGIC & PHILOSOPHICAL METHODOLOGY Introduction For present purposes “logic” will be understood to mean the subject whose development is described in Kneale & Kneale [1961] and of which a concise history is given in Scholz [1961]. As the terminological discussion at the beginning of the latter reference makes clear, this subject has at different times been known by different names, “analytics” and “organon” and “dialectic”, while inversely the name “logic” has at different times been applied much more broadly and loosely than it will be here. At certain times and in certain places — perhaps especially in Germany from the days of Kant through the days of Hegel — the label has come to be used so very broadly and loosely as to threaten to take in nearly the whole of metaphysics and epistemology. Logic in our sense has often been distinguished from “logic” in other, sometimes unmanageably broad and loose, senses by adding the adjectives “formal” or “deductive”. The scope of the art and science of logic, once one gets beyond elementary logic of the kind covered in introductory textbooks, is indicated by two other standard references, the Handbooks of mathematical and philosophical logic, Barwise [1977] and Gabbay & Guenthner [1983-89], though the latter includes also parts that are identified as applications of logic rather than logic proper. The term “philosophical logic” as currently used, for instance, in the Journal of Philosophical Logic, is a near-synonym for “nonclassical logic”. There is an older use of the term as a near-synonym for “philosophy of language”.