Introducing Substitution in Proof Theory

Total Page:16

File Type:pdf, Size:1020Kb

Introducing Substitution in Proof Theory Introducing Substitution in Proof Theory Alessio Guglielmi University of Bath 20 July 2014 This talk is available at http://cs.bath.ac.uk/ag/t/ISPT.pdf It is an abridged version of this other talk: http://cs.bath.ac.uk/ag/t/PCMTGI.pdf Deep inference web site: http://alessio.guglielmi.name/res/cos/ Outline Problem: compressing proofs. Solution: proof composition mechanisms beyond Gentzen. Open deduction: composition by connectives and inference, smaller analytic proofs than in Gentzen. Atomic flows: geometry is enough to normalise. Composition by substitution: more geometry, more efficiency, more naturality. ON THE PROOF COMPLEXITY OF DEEP INFERENCE 21 SKSg can analogously be extended, but there is no need to create a special rule; we only need to broaden the criterion by which we recognize a proof. Definition 5.3. An extended SKSg proof of α is an SKSg derivation with conclusion α ¯ ¯ ¯ ¯ ¯ ¯ and premiss [A1 β1] [β1 A1] [Ah βh ] [βh Ah ],whereA1, A1,...,Ah , Ah ∨ ∧ ∨ ∧ ···∧ ∨ ∧ ∨ are mutually distinct and A1 / β1,α and ... and Ah / β1,...,βh ,α.WedenotebyxSKSg the proof system whose proofs∈ are extended SKSg proofs.∈ Theorem 5.4. For every xFrege proof of length l and size n there exists an xSKSg proof of 2 the same formula and whose length and size are, respectively, O(l ) and O(n ). Proof. Consider an xFrege proof as in Definition 5.1. By Remark 5.2 and Theorem 4.6, there exists the following xSKSg proof, whose length and size are yielded by 4.6: ¯ ¯ ¯ ¯ [A1 β1] [β1 A1] [Ah βh ] [βh Ah ] ∨ ∧ ∨ ∧ ···∧ ∨ ∧ ∨ $ SKSg . $ αk ! Although not strictly necessary to establish the equivalence of the four extended for- malisms (see diagram in the Introduction), the following theorem is very easy to prove. Theorem 5.5. For every xSKSg proof of size n there exists an xFrege proof of the same 4 5 formula and whose length and size are, respectively, O(n ) and O(n ). Proof. Consider an xSKSg proof as in Definition 5.3. The statement is an immediate consequence of Theorem 4.11, after observing that there is an O(h)-length and O(hn)- size xFrege proof A β ,...,A β ,..., A β A β . Problem: compressing1 ↔ 1 h ↔ proofsh ( 1 ↔ 1) ∧ ∧ ( h ↔ h ) ON THE PROOF COMPLEXITY··· OF DEEP INFERENCE 7 ! CorollaryHow can 5.6.we makeSystems proofsxFrege smaller?and xSKSgKnownareStructural mechanisms:p-equivalent.rules Logical rule We1. Re-use now move the to same thesubstitution sub-proof: cut rule. rule. Proof theory. A A¯ A A Definition2. Re-use 5.7. theA samesubstitution sub-proof:i Frege∧ dagness(proof,) orsystem cocontractionw is a Frege: systemc augmented. with ↑ f ↑ t ↑ A A A ∧ the3.substitution Substitution rule: sub cointeraction.WedenotebyIn Frege, equivalentsFrege coweakeningthe to (4). proof system cocontraction where a proof is a Aσ or cut derivation with no premisses, conclusion α ,andshape 4. Tseitin extensionSKSg : p A (where p kis a fresh atom). Optimal? t f A A A B C $αi αi ∨ ∧ [ ∨ ] 5. Higher orders (including 1i 2nd order propositional).w h c s ↓≡A A¯ ↓ A ≡ ↓ A A B C α ,...,α , α σ ,∨α ,...,α , α σ ,α ,...,α , ( ∧ ) ∨ KSg 1 i1 1 j1 1 i1+1 ih 1 jh h ih +1 k − interaction weakening− contraction switch where all the conclusions of substitution instances α ,...,α are singled out, α We will see that 1– 4 (and !or a"# bit$ also 5) have a lot! to"#i1 do$ withih j1 identity ∈ αproof,..., compositionα ,...,α: thisα is our,..., mainα tool.,andtherestoftheproofisasinFrege. 1 i1 1 jh 1 ih 1 { − } ∈{ − } We rely on the following result. FIGURE 2. Systems SKSg and KSg. Our main objective is providing for small spaces of canonical proofs Theorem(= eliminating 5.8. (Cook-Reckhow bureaucracy = getting and Krají goodˇcek-Pudlák, proof semantics).[CR79, KP89]) Systems xFrege and sFrege are p-equivalent. Atomic structural rules Logical rules We can extend SKSg witha a¯ the same substitutiona rule asa for Frege.Theruleisusedlike ai ∧ aw ac other proper rules of system↑ f SKSg,soitsinstancesareinterleavedwith↑ t ↑ a a =-rule instances. ∧ Definition 5.9. AncointeractionsSKSg proof is coweakening a proof of SKSg cocontractionwhere, in addition to the inference steps generated by rulesor ofcutSKSg,weadmitinferencestepsobtainedasinstancesofthe SKS A substitution rulesub . t f a a A [B C ] (A B) (C D) Aaiσ aw ac ∨ s ∧ ∨ m ∧ ∨ ∧ ↓ a a¯ ↓ a ↓ a (A B) C [A C ] [B D] ∨ ∧ ∨ ∨ ∧ ∨ KS interaction weakening contraction switch medial or identity FIGURE 3. Systems SKS and KS. We can now define some deep-inference proof systems. System SKS is the most impor- tant for the proof theory of classical logic, because of its atomic structural rules. System SKSg relates SKS to proof systems in other formalisms, like Frege. Definition 2.13. CoS proof systems KSg = i ,w ,c ,s , SKSg = KSg i ,w , { ↓ ↓ ↓ } ∪ { ↑ ↑ c , KS = ai ,aw ,ac ,s,m and SKS = KS ai ,aw ,ac are defined in Figures 2 and↑} 3, for a{ language↓ ↓ containing↓ } f, t, disjunction,∪ { and↑ conjunction.↑ ↑} Proof systems where none of the rules i , ai , w ,andaw appear are said to be analytic. ↑ ↑ ↑ ↑ Example 2.14. This is a valid derivation in all CoS proof systems defined previously (and it plays a role in the proof of Lemma 3.11): γ [(([α¯ α] c) (α d)) δ] = ∨ ∨ ∧ ∧ ∧ ∨ γ [(((α d) c) [α α¯]) δ] s ∨ ∧ ∧ ∧ ∨ ∨ . γ [[(((α d) c) α) α¯] δ] = ∨ ∧ ∧ ∧ ∨ ∨ α¯ γ α c α d δ [ ∨ ] ∨ [(( ∧ ) ∧ ( ∧ )) ∨ ] Note that SKSg, KSg, SKS,andKS are closed under renaming and substitution (see Remark 2.11). This is so because of the distinction between atoms and formula variables. Obtaining the closure of these and other systems under renaming and substitution is one of the main technical reasons for distinguishing between atoms and variables. The following theorem is proved in [Brü04],andfollowsimmediatelyfromSec- tion 3.1, where we prove that CoS systems p-simulate Gentzen systems. Solution: proof composition mechanisms beyond Gentzen Less is more. Let's make better use of what we have already. Given two proofs φ : A B and : C D: ) ) 1. For a logical connective ? we have: φ ? :(A ? C) (B ? D) : ) Proofs are composed by the connectives of the formula language. 2. For an inference rule B=C we have: φ/ψ : A D : ) Proofs are composed by inference rules. 3. For an atom a we have: φ a : A a C; ¯a D¯ B a D; ¯a C¯ : f g f g ) f g Proofs are composed by substitution. Two (relatively) new formalisms Open deduction: composition by (1) connectives and (2) inference rules. I It exists [5] and it can be taken as a definition for deep inference. I It generalises the sequent calculus by removing its restrictions. I Sequents ‘depth-1 inference without full inference composition'. ≈ I Hypersequents ‘depth-2 inference without full inference ≈ composition'. I It compresses proofs by cut, dagness and depth itself (new, exponential speed-up). I I'll show the main ideas and some results. ‘Formalism B': open deduction + (3) substitution. I It almost exists (work with Bruscoli, Gundersen and Parigot). I It further compresses proofs by substitution (conjectured further superpolynomial speed-up, it is equivalent to Frege + substitution). I I'll show some ideas and what I think we can get. 4 PAOLA BRUSCOLI, ALESSIO GUGLIELMI, TOM GUNDERSEN, AND MICHEL PARIGOT 4 PAOLA BRUSCOLI, ALESSIO GUGLIELMI, TOM GUNDERSEN, AND MICHEL PARIGOT ξ γ instances of α and β, respectively, generates an (inference) step ρ { }, for each context ξ ξδ C instances of A and B, respectively, generates an (inference) step ρ{ {} }, for each context ξ .Aderivation, Φ, from α (premiss) to β (conclusion) is a chain ofξ−−−−−−−− inferenceD steps with {} { } ξ .Aderivation, Φ, from A (premiss) to B (conclusion) is aα chain of inference steps with {} α at the top and β at the bottom, and is usually indicated by Φ ! A, where is the name " A at the top and B at the bottom, and is usually indicated by! Φ , where" is the name β B of the proof system or a set of inference rules (we might omit and ); a proof, often of the proof system or a set of inference rules (we might omitΦ and ); a proof, often denoted by , is a derivation with premiss t; besides , we denoteΦ derivations" with . denoted byΠ , is a derivation with premiss t; besidesΦ , we denote derivations withΨ . Sometimes weΠ group n 0 inference steps of the same ruleΦ ρ together into one step, andΨ Sometimes we group!n 0 inference steps of the same rule ρ together into one step, and we label the step with n ρ. we label the step with n ρ. The size α of a formula· α, and the size of a derivation , is the number of unit The size A of a formula· A, and the sizeΦ of a derivationΦ , is the number of unit and atom occurrences| | appearing in it. | | Φ Φ and atom occurrences| | appearing in it. | | By α a /β ,...,a /β , we denote the operation of simultaneously substituting for- By A1 a /1 B ,...,h a /hB , we denote the operation of simultaneously substituting for- mulae β{ ,...,1 β1 intoh all}h the occurrences of the atoms a ,..., a in the formula α, mulae1B{,...,hB into all} the occurrences of the atoms1 a ,...,h a in the formula A, respectively;1 note thath the occurrences of a¯ ,..., a¯ are not automatically1 h substituted. respectively; note that the occurrences of1 a¯ ,...,h a¯ are not automatically substituted. Often, we only substitute certain occurrences of1 atoms,h and these are indicated with su- Often, we only substitute certain occurrences of atoms, and these are indicated with su- perscripts that establish a relation with atomic flows.
Recommended publications
  • Deep Inference
    Deep Inference Alessio Guglielmi University of Bath [email protected] 1 Introduction Deep inference could succinctly be described as an extreme form of linear logic [12]. It is a methodology for designing proof formalisms that generalise Gentzen formalisms, i.e. the sequent calculus and natural deduction [11]. In a sense, deep inference is obtained by applying some of the main concepts behind linear logic to the formalisms, i.e., to the rules by which proof systems are designed. By do- ing so, we obtain a better proof theory than the traditional one due to Gentzen. In fact, in deep inference we can provide proof systems for more logics, in a more regular and modular way, with smaller proofs, less syntax, less bureau- cracy and we have a chance to make substantial progress towards a solution to the century-old problem of the identity of proofs. The first manuscript on deep inference appeared in 1999 and the first refereed papers in 2001 [6, 19]. So far, two formalisms have been designed and developed in deep inference: the calcu- lus of structures [15] and open deduction [17]. A third one, nested sequents [5], introduces deep inference features into a more traditional Gentzen formalism. Essentially, deep inference tries to understand proof composition and proof normalisation (in a very liberal sense including cut elimination [11]) in the most logic-agnostic way. Thanks to it we obtain a deeper understanding of the nature of normalisation. It seems that normalisation is a primitive, simple phenomenon that manifests itself in more or less complicated ways that depend more on the choice of representation for proofs rather than their true mathematical na- ture.
    [Show full text]
  • Facilitating Meta-Theory Reasoning (Invited Paper)
    Facilitating Meta-Theory Reasoning (Invited Paper) Giselle Reis Carnegie Mellon University in Qatar [email protected] Structural proof theory is praised for being a symbolic approach to reasoning and proofs, in which one can define schemas for reasoning steps and manipulate proofs as a mathematical structure. For this to be possible, proof systems must be designed as a set of rules such that proofs using those rules are correct by construction. Therefore, one must consider all ways these rules can interact and prove that they satisfy certain properties which makes them “well-behaved”. This is called the meta-theory of a proof system. Meta-theory proofs typically involve many cases on structures with lots of symbols. The majority of cases are usually quite similar, and when a proof fails, it might be because of a sub-case on a very specific configuration of rules. Developing these proofs by hand is tedious and error-prone, and their combinatorial nature suggests they could be automated. There are various approaches on how to automate, either partially or completely, meta-theory proofs. In this paper, I will present some techniques that I have been involved in for facilitating meta-theory reasoning. 1 Introduction Structural proof theory is a branch of logic that studies proofs as mathematical objects, understanding the kinds of operations and transformations that can be done with them. To do that, one must represent proofs using a regular and unambiguous structure, which is constructed from a fixed set of rules. This set of rules is called a proof calculus, and there are many different ones.
    [Show full text]
  • Propositional Logic: Deductive Proof & Natural Deduction Part 1
    Propositional Logic: Deductive Proof & Natural Deduction Part 1 CS402, Spring 2016 Shin Yoo Shin Yoo Propositional Logic: Deductive Proof & Natural Deduction Part 1 Deductive Proof In propositional logic, a valid formula is a tautology. So far, we could show the validity of a formula φ in the following ways: Through the truth table for φ Obtain φ as a substitution instance of a formula known to be valid. That is, q ! (p ! q) is valid, therefore r ^ s ! (p _ q ! r ^ s) is also valid. Obtain φ through interchange of equivalent formulas. That is, if φ ≡ and φ is a subformula of a valid formula χ, χ0 obtained by replacing all occurrences of φ in χ with is also valid. Shin Yoo Propositional Logic: Deductive Proof & Natural Deduction Part 1 Deductive Proof Goals of logic: (given U), is φ valid? Theorem 1 (2.38, Ben-Ari) U j= φ iff j= A1 ^ ::: ^ An ! φ when U = fA1;:::; Ang. However, there are problems in semantic approach. Set of axioms may be infinite: for example, Peano and ZFC (Zermelo-Fraenkel set theory) theories cannot be finitely axiomatised. Hilbert system, H, uses axiom schema, which in turn generates an infinite number of axioms. We cannot write truth tables for these. The truth table itself is not always there! Very few logical systems have decision procedures for validity. For example, predicate logic does not have any such decision procedure. Shin Yoo Propositional Logic: Deductive Proof & Natural Deduction Part 1 Semantic vs. Syntax j= φ vs. ` φ Truth Tools Semantics Syntax Validity Proof All Interpretations Finite Proof Trees Undecidable Manual Heuristics (except propositional logic) Shin Yoo Propositional Logic: Deductive Proof & Natural Deduction Part 1 Deductive Proof A deductive proof system relies on a set of proof rules (also inference rules), which are in themselves syntactic transformations following specific patterns.
    [Show full text]
  • Agent-Based Blackboard Architecture for a Higher-Order Theorem Prover
    Masterarbeit am Institut für Informatik der Freien Universität Berlin, Arbeitsgruppe Künstliche Intelligenz Agent-based Blackboard Architecture for a Higher-Order Theorem Prover Max Wisniewski [email protected] Betreuer: PD. Dr. Christoph Benzmüller Berlin, den 17. Oktober 2014 Abstract The automated theorem prover Leo was one of the first systems able to prove theorems in higher-order logic. Since the first version of Leo many other systems emerged and outperformed Leo and its successor Leo-II. The Leo-III project’s aim is to develop a new prover reclaiming the lead in the area of higher-order theorem proving. Current competitive theorem provers sequentially manipulate sets of formulas in a global loop to obtain a proof. Nowadays in almost every area in computer science, concurrent and parallel approaches are increas- ingly used. Although some research towards parallel theorem proving has been done and even some systems were implemented, most modern the- orem provers do not use any form of parallelism. In this thesis we present an architecture for Leo-III that use paral- lelism in its very core. To this end an agent-based blackboard architecture is employed. Agents denote independent programs which can act on their own. In comparison to classical theorem prover architectures, the global loop is broken down to a set of tasks that can be computed in paral- lel. The results produced by all agents will be stored in a blackboard, a globally shared datastructure, thus visible to all other agents. For a proof of concept example agents are given demonstrating an agent-based approach can be used to implemented a higher-order theorem prover.
    [Show full text]
  • Unifying Theories of Logics with Undefinedness
    Unifying Theories of Logics with Undefinedness Victor Petru Bandur PhD University of York Computer Science September, 2014 Abstract A relational approach to the question of how different logics relate formally is described. We consider three three-valued logics, as well as classical and semi-classical logic. A fundamental representation of three-valued predicates is developed in the Unifying Theories of Programming (UTP) framework of Hoare and He. On this foundation, the five logics are encoded semantically as UTP theories. Several fundamental relationships are revealed using theory linking mechanisms, which corroborate results found in the literature, and which have direct applicability to the sound mixing of logics in order to prove facts. The initial development of the fundamental three-valued predicate model, on which the theories are based, is then applied to the novel systems-of-systems specification language CML, in order to reveal proof obligations which bridge a gap that exists between the semantics of CML and the existing semantics of one of its sub-languages, VDM. Finally, a detailed account is given of an envisioned model theory for our proposed structuring, which aims to lift the sentences of the five logics encoded to the second order, allowing them to range over elements of existing UTP theories of computation, such as designs and CSP processes. We explain how this would form a complete treatment of logic interplay that is expressed entirely inside UTP. ii Contents Abstract ii Contents iii List of Figures vi Acknowledgments vii Author's Declaration viii 1 Background 1 1.1 Introduction . .1 1.2 Logic in Software Rationale .
    [Show full text]
  • Proof Terms for Classical Derivations Greg Restall* Philosophy Department the University of Melbourne [email protected] June 13, 2017 Version 0.922
    proof terms for classical derivations Greg Restall* Philosophy Department The University of Melbourne [email protected] june 13, 2017 Version 0.922 Abstract: I give an account of proof terms for derivations in a sequent calculus for classical propositional logic. The term for a derivation δ of a sequent Σ ∆ encodes how the premises Σ and conclusions ∆ are related in δ. This encoding is many–to–one in the sense that different derivations can have the same proof term, since different derivations may be different ways of representing the same underlying connection between premises and conclusions. However, not all proof terms for a sequent Σ ∆ are the same. There may be different ways to connect those premises and conclusions. Proof terms can be simplified in a process corresponding to the elimination of cut inferences in se- quentderivations. However, unlikecuteliminationinthesequentcalculus, eachproofterm hasa unique normal form (fromwhichallcutshavebeeneliminated)anditisstraightforwardtoshowthattermreduc- tion is strongly normalising—every reduction process terminates in that unique normal form. Further- more, proof terms are invariants for sequent derivations in a strong sense—two derivations δ1 and δ2 have the same proofterm if and only if some permutation of derivation steps sends δ1 to δ2 (given a rela- tively natural class of permutations of derivations in the sequent calculus). Since not every derivation of a sequent can be permuted into every other derivation of that sequent, proof terms provide a non-trivial account of the identity of proofs, independent of the syntactic representation of those proofs. outline This paper has six sections: Section 1 motivates the problem of proof identity, and reviews the reasons that the question of proof identity for classical propositional logic is difficult.
    [Show full text]
  • Logic Three Tutorials at Tbilisi
    Logic Three tutorials at Tbilisi Wilfrid Hodges 1.1 Queen Mary, University of London [email protected] FIRST TUTORIAL October 2003 Entailments Revised 17 October 2003. For copyright reasons some of the photos are not included. 1 2 1.2 1.3 Two sentences: If p and q are sentences, the expression (a) Noam Chomsky is very clever. p |= q (b) Noam Chomsky is clever. is called a sequent. If (a) is true then (b) must be true too. If it is true, i.e. if p does entail q, We express this by saying that (a) entails (b), in symbols then we say it is a valid sequent, NC is very clever. |= NC is clever. or for short an entailment. 3 4 1.5 Typical problem Imagine a situation with two Noam Chomskys, 1.4 Provisional definition Logic is the study of entailments. Butit’sabadideatogotoadefinition so early. one very clever and one very unintelligent. 5 6 1.7 1.6 Remedy Conversation: A situation (for a set of sentences) consists of the information needed to fix who the named people are, what the date is, • “Noam Chomsky is very clever.” and anything else relevant to the truth of the sentences. • “Yes, but on the other hand Noam Chomsky Then we can revise our notion of entailment: is not clever at all.” ‘(a) entails (b)’ means We can understand this conversation. In every situation, if (a) is true then (b) is true. (David Lewis, ‘Scorekeeping in a language game’.) This remedy is not waterproof, but it will allow us to continue building up logic.
    [Show full text]
  • A Mechanised Proof of Gödel's Incompleteness Theorems Using
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Apollo A Mechanised Proof of G¨odel'sIncompleteness Theorems using Nominal Isabelle Lawrence C. Paulson Abstract An Isabelle/HOL formalisation of G¨odel'stwo incompleteness theorems is presented. The work follows Swierczkowski's´ detailed proof of the theorems using hered- itarily finite (HF) set theory [32]. Avoiding the usual arithmetical encodings of syntax eliminates the necessity to formalise elementary number theory within an embedded logical calculus. The Isabelle formalisation uses two separate treatments of variable binding: the nominal package [34] is shown to scale to a development of this complex- ity, while de Bruijn indices [3] turn out to be ideal for coding syntax. Critical details of the Isabelle proof are described, in particular gaps and errors found in the literature. 1 Introduction This paper describes mechanised proofs of G¨odel'sincompleteness theorems [8], includ- ing the first mechanised proof of the second incompleteness theorem. Very informally, these results can be stated as follows: Theorem 1 (First Incompleteness Theorem) If L is a consistent theory capable of formalising a sufficient amount of elementary mathematics, then there is a sentence δ such that neither δ nor :δ is a theorem of L, and moreover, δ is true.1 Theorem 2 (Second Incompleteness Theorem) If L is as above and Con(L) is a sentence stating that L is consistent, then Con(L) is not a theorem of L. Both of these will be presented formally below. Let us start to examine what these theorems actually assert.
    [Show full text]
  • Satisfiability Calculus: an Abstract Formulation of Semantic Proof Systems
    Fundamenta Informaticae XX (2019) 1–50 1 DOI 10.3233/FI-2016-0000 IOS Press Satisfiability Calculus: An Abstract Formulation of Semantic Proof Systems Carlos G. Lopez Pombo∗ Pablo F. Castroy CONICET-Universidad de Buenos Aires. CONICET- Department of Computer Science Instituto de Investigacion´ en Ciencias de la Universidad Nacional de R´ıo Cuarto Computacion´ (ICC) R´ıo Cuarto, Argentina [email protected] [email protected] Nazareno M. Aguirrez Thomas S.E. Maibaumx CONICET- Department of Computer Science Department of Computing & Software Universidad Nacional de R´ıo Cuarto McMaster University, Canada R´ıo Cuarto, Argentina [email protected] [email protected] Abstract. The theory of institutions, introduced by Goguen and Burstall in 1984, can be thought of as an abstract formulation of model theory. This theory has been shown to be particularly useful in computer science, as a mathematical foundation for formal approaches to software con- struction. Institution theory was extended by a number of researchers, Jose´ Meseguer among them, who, in 1989, presented General Logics, wherein the model theoretical view of institutions Address for correspondence: Department of Computer Science, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Argentina ∗Carlos G. Lopez Pombo wants to thank the founding from Agencia Nacional de Promocion´ Cient´ıfica y Tecnologica´ (ANPCyT) through grant PICT 2013 No. 2129, from Universidad de Buenos Aires through grant UBACyT 2014-2017 No. 20020130200092BA and from Consejo Nacional de Investigaciones Cient´ıficas y Tecnologicas´ (CONICET) through grant PIP 2014-2016 No. 11220130100148CO. yPablo Castro wants to thank the founding from Agencia Nacional de Promocion´ Cient´ıfica y Tecnologica´ (ANPCyT) through grant PICT 2013 No.
    [Show full text]
  • Constructive Completeness Proofs and Delimited Control Danko Ilik
    Constructive Completeness Proofs and Delimited Control Danko Ilik To cite this version: Danko Ilik. Constructive Completeness Proofs and Delimited Control. Software Engineering [cs.SE]. Ecole Polytechnique X, 2010. English. tel-00529021 HAL Id: tel-00529021 https://pastel.archives-ouvertes.fr/tel-00529021 Submitted on 24 Oct 2010 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. Thèse présentée pour obtenir le grade de Docteur de l’Ecole Polytechnique Spécialité : Informatique par Danko ILIK´ Titre de la thèse : Preuves constructives de complétude et contrôle délimité Soutenue le 22 octobre 2010 devant le jury composé de : M. Hugo HERBELIN Directeur de thèse M. Ulrich BERGER Rapporteur M. Thierry COQUAND Rapporteur M. Olivier DANVY Rapporteur M. Gilles DOWEK Examinateur M. Paul-André MELLIÈS Examinateur M. Alexandre MIQUEL Examinateur M. Wim VELDMAN Examinateur Constructive Completeness Proofs and Delimited Control Danko ILIK´ ABSTRACT. Motivated by facilitating reasoning with logical meta-theory in- side the Coq proof assistant, we investigate the constructive versions of some completeness theorems. We start by analysing the proofs of Krivine and Berardi-Valentini, that classical logic is constructively complete with respect to (relaxed) Boolean models, and the algorithm behind the proof.
    [Show full text]
  • HISTORY of LOGICAL CONSEQUENCE 1. Introduction
    HISTORY OF LOGICAL CONSEQUENCE CONRAD ASMUS AND GREG RESTALL 1. Introduction Consequence is a, if not the, core subject matter of logic. Aristotle's study of the syllogism instigated the task of categorising arguments into the logically good and the logically bad; the task remains an essential element of the study of logic. In a logically good argument, the conclusion follows validly from the premises; thus, the study of consequence and the study of validity are the same. In what follows, we will engage with a variety of approaches to consequence. The following neutral framework will enhance the discussion of this wide range of approaches. Consequences are conclusions of valid arguments. Arguments have two parts: a conclusion and a collection of premises. The conclusion and the premises are all entities of the same sort. We will call the conclusion and premises of an argument the argument's components and will refer to anything that can be an argument component as a proposition. The class of propositions is defined func- tionally (they are the entities which play the functional role of argument compo- nents); thus, the label should be interpreted as metaphysically neutral. Given the platonistic baggage often associated with the label \proposition", this may seem a strange choice but the label is already used for the argument components of many of the approaches below (discussions of Aristotlean and Medieval logic are two ex- amples). A consequence relation is a relation between collections of premises and conclusions; a collection of premises is related to a conclusion if and only if the latter is a consequence of the former.
    [Show full text]
  • Propositional Calculus • Proof Calculus for Predicate Calculus
    Predicate Calculus Formal Methods in Verification of Computer Systems Jeremy Johnson Outline 1. Motivation 1. Variables, quantifiers and predicates 2. Syntax 1. Terms and formulas 2. Quantifiers, scope and substitution 3. Rules of natural deduction for quantifiers 4. Semantics 1. Models and semantic entailment 5. Undecidability and limitations Example 1 • Every student is younger than some instructor • ∀x ( S(x) → ∃y(I(y) ∧ Y(x,y) ) • S(x) : x is a student • I(x) : is an instructor • Y(x,y) : x is younger than y Example 2 • Not all birds can fly • ¬ ∀x ( B(x) → F(x) ) • ∃x ( (B(x) ∧ ¬ F(x) ) • B(x) : x is a bird • F(x) : x can fly • Semantically equivalent formulas Example 3 • Every child is younger than its mother • ∀x ∀y ( C(x) ∧ M(y,x) → Y(x,y) ) • C(x) : x is child • M(x,y) : x is y’s mother • Y(x,y) : x is younger than y • ∀x ( C(x) → Y(x,m(x)) • m(x) : function for mother of x Example 4 • Andy and Paul have the same maternal grandmother • ∀x ∀y ∀u ∀v ( M(x,y) ∧ M(y,a) ∧ M(u,v) ∧ M(v,p) → x = u ) • m(m(a)) = m(m(p)) • a, b : variables for Andy and Paul • = : binary predicate Example 5 • Everyone has a mother • ∀x ∃y ( M(y,x) ) • ∃x ∀y ( M(y,x) ) [ not equivalent ] • Everyone has exactly one mother • ∀x ∃y ( M(y,x) ∧ ∀z (M(z,x) → z = y ) Example 6 • Some people have more than one brother • ∃x ∃y1 ∃y2 ( B(y1,x) ∧ B(y2,x) ∧ ¬(y1 = y2) ) Comparison to Propositional Calculus • Proof calculus for predicate calculus • φ1,…,φn ψ [ extend natural deduction ] Provide semantics for predicate calculus • ⊢ • φ1,…,φn ψ [ models needed to evaluate
    [Show full text]