Sequent Calculi for Skeptical Reasoning in Predicate Default Logic and Other Nonmonotonic Logics ∗

Total Page:16

File Type:pdf, Size:1020Kb

Sequent Calculi for Skeptical Reasoning in Predicate Default Logic and Other Nonmonotonic Logics ∗ Sequent Calculi for Skeptical Reasoning in Predicate Default Logic and Other Nonmonotonic Logics ∗ Robert Saxon Milnikel ([email protected]) Department of Mathematics, Kenyon College Abstract. Sequent calculi for skeptical consequence in predicate default logic, predicate stable model logic programming, and infinite autoepistemic theories are presented and proved sound and complete. While skeptical consequence is decidable in the finite propositional case of all three formalisms, the move to predicate or 1 infinite theories increases the complexity of skeptical reasoning to being Π1-complete. This implies the need for sequent rules with countably many premises, and such rules are employed. Keywords: Default logic, Stable models, Autoepistemic logic, Sequent calculus AMS Subject Classifications: 03B42, 68N17, 68T27 1. Introduction Skeptical consequence is a notion common to all forms of nonmono- tonic reasoning. Every nonmonotonic formalism permits different world views to be justified using the same set of facts and principles; the skeptical consequences of a framework are the notions common to all world views associated with that framework. Our purpose in this paper is to present a Gentzen-style sequent calculus (incorporating some in- finitary rules) which will allow us to deduce the skeptical consequences of a given framework. Such sequent calculi (with purely finite rules) were defined for several types of nonmonotonic systems by Bonatti and Olivetti in [6], but they restricted their attention to finite propositional systems for which skeptical consequence is decidable. We will adapt and extend their systems to accommodate infinite predicate systems. We will focus on three types of nonmonotonic reasoning: stable model logic programming (due to Gelfond and Lifschitz, [8]), default logic (due to Reiter, [22]), and autoepistemic logic (due to Moore, [19]). In all three cases, when one steps from the finite and propositional to the predicate and potentially infinite, finding the set of skeptical 1 consequences of a framework goes from being decidable to being Π1- complete, at the same level of the computability hierarchy as true arithmetic. This result was proved for stable model logic program- ∗ This paper grew directly out of the author’s dissertation, written under the direction of Anil Nerode. c 2004 Kluwer Academic Publishers. Printed in the Netherlands. fulldefaultsequent.tex; 18/06/2004; 16:12; p.1 2 R.S. Milnikel ming by Marek, Nerode, and Remmel in [13], but it translates to the other systems quite easily. (The reader should be aware that there will be a few computability theoretic ideas and motivations discussed in this introductory section, but that they may be considered “deep background” and will not be a part of the exposition of the main ideas.) 1 0 Π1 sets correspond to finite-path computable (or Π1) subtrees of ω<ω in a very natural way. See [7] for an excellent exposition. This makes skeptical consequence a natural fit for sequent calculi with in- finitary rules, since a sequent proof is, at its core, a finite-path tree. Bonatti and Olivetti also addressed credulous consequence (“Can this notion be a part of some world view?”) in their paper, but in the cases they were interested in, this question was also decidable. In our more 1 general context, credulous reasoning is Σ1-complete, not a natural type of question to address with trees-as-proofs. (One could write a sequent 1 calculus for credulous reasoning in Π2 logic, but this would take us too far afield.) Why do we plan to address the nonmonotonic formalisms listed earlier and not others? Default logic, autoepistemic logic, and circum- scription are historically the most established frameworks, with stable model logic programming now as widely studied as those three. We will begin with stable model logic programming because it has the simplest classical monotonic base over which the nonmonotonicity is layered. This will permit us to focus on the distinctly nonmonotonic parts of the skeptical sequent calculus in our first encounter with such systems. The reason for excluding circumscription (due to McCarthy, [15]) is easily stated: Skeptical consequence for predicate circumscription was 1 1 shown by Schlipf in [23] to be Π2-complete, not Π1-complete like the 1 other systems mentioned. As I said earlier, a Π2 sequent calculus would take us far beyond the intended scope of this paper. We will also not be discussing Marek, Nerode, and Remmel’s nonmonotone rule systems (see [12]) or McDermott and Doyle’s nonmonotonic modal logics (see [16]). The reasons are twofold in each case. Nonmonotone rule systems have not entered the mainstream of the nonmonotonic reasoning liter- ature, and are also essentially isomorphic to propositional stable model logic programming. The systems of McDermott and Doyle are also not as central to the field as some other formalisms, and would benefit from a more specific study in the context of Artemov’s logic of proofs (see [3]). Why does the move from the propositional to the predicate entail such an enormous increase in complexity? Because in general, it also implies a move from a finite set of rules to an infinite one. In predicate logic programming, an open variable is viewed as an abbreviation for all values which that variable might take on. The standard approach fulldefaultsequent.tex; 18/06/2004; 16:12; p.2 Predicate Nonmonotone Sequent Calculi 3 is to make each of those possible instantiations explicit, turning a fi- nite predicate logic program over an infinite domain into an infinite program. In default logic, there has been debate since Reiter first defined the framework in 1980 about how to treat unbounded variables in the rules. Reiter ([22]) advocated treating open variables (at least in the negative premises of a default rule) in the same way that they are treated in logic programs: as abbreviations for the same rule with each ground term of the language substituted. Again, this can turn a finite default theory into an infinite grounded one. This is the definition we will use in this paper. However, there is some quite justified criticism of this ap- : MP (x) proach. Under these definitions, the default theory ( , ¬P (a)) P (x) does not imply (∀x)[P (x) ↔ x 6= a]. Lifschitz, in [10], defines exten- sions (the possible world views associated with default logic) relative to fixed domains. For finite theories and finite domains, everything is decidable, but over infinite domains this is no longer the case. In [18], it is shown that skeptical reasoning over countable domains using 1 Lifschitz’ definition of extension is Π2-complete, the same level as for circumscription. Because nonmonotonic logics deal not only with proof but with lack of proof, we will need not only standard monotone sequent calculi, but also rule systems for showing a lack of proof. (We will call these antisequent calculi, using the terminology of Bonatti from [5].) While propositional provability and lack of provability are decidable, predicate provability is only recursively enumerable, and hence predicate non- 1 provability is co-r.e. Just as Σ1 sets do not lend themselves naturally 1 to tree-based proofs, neither do co-r.e. sets. However, while Σ1 sets 1 required a jump to Π2 logic, co-r.e. sets are easily accommodated in 1 the Π1 framework within which we will already be working. Bringing such enormously powerful logical machinery to bear on such a relatively simple problem may seem like overkill, but it works out quite naturally. The reader is thus warned that infinitary proofs will appear throughout the paper, even when talking about something as simple as lack of a standard predicate logic proof. When discussing autoepistemic logic, we limit ourselves to the propo- sitional case, but with a potentially infinite theory. This puts us at the 1 same Π1 level of complexity as for stable model logic programming and default logic. Predicate autoepistemic logic is discussed in the literature (see, for example, [9]), and the interested reader should not find it difficult to combine the rules specific to predicate logic (from the discussion of default logic) with the results about propositional autoepistemic logic. fulldefaultsequent.tex; 18/06/2004; 16:12; p.3 4 R.S. Milnikel We will begin in Section 2 with some preliminary definitions and results about the types of nonmonotonic systems we will consider in this paper. Section 3 presents rudimentary sequent and antisequent calculi for Horn programs, continues with a sequent calculus for skep- tical reasoning in stable model logic programming, and concludes with a proof of the soundness and completeness of this calculus. Section 4 concentrates on finding an antisequent calculus for classical predicate logic, and concludes with a very brief treatment of a sequent calculus for skeptical reasoning in default logic. The nonmonotonic aspects of stable model logic programming and default logic are so similar that the sequent calculi are nearly identical and no proof is necessary for the soundness and completeness theorems in this case. Section 5 presents a sequent calculus for skeptical reasoning in infinite propositional au- toepistemic theories, and proves soundness and completeness theorems for this calculus. Section 6 looks toward further directions for research. 2. Preliminaries We will be working with systems based on a variety of languages, both predicate and propositional. We will assume that the reader has some familiarity with classical propositional and predicate logic, including the notion of a Herbrand base for a given predicate language, the standard sequent calculus LK for propositional logic, and the modal operator L. 2.1. Stable Model Logic Programming Logic programming is a broad and widely studied subfield of computer science. We will concentrate here on only one aspect – finding models of a program given a particular interpretation of negation. For a more general introduction, see [2], [11], or [21].
Recommended publications
  • Nested Sequents, a Natural Generalisation of Hypersequents, Allow Us to Develop a Systematic Proof Theory for Modal Logics
    Nested Sequents Habilitationsschrift Kai Br¨unnler Institut f¨ur Informatik und angewandte Mathematik Universit¨at Bern May 28, 2018 arXiv:1004.1845v1 [cs.LO] 11 Apr 2010 Abstract We see how nested sequents, a natural generalisation of hypersequents, allow us to develop a systematic proof theory for modal logics. As opposed to other prominent formalisms, such as the display calculus and labelled sequents, nested sequents stay inside the modal language and allow for proof systems which enjoy the subformula property in the literal sense. In the first part we study a systematic set of nested sequent systems for all normal modal logics formed by some combination of the axioms for seriality, reflexivity, symmetry, transitivity and euclideanness. We establish soundness and completeness and some of their good properties, such as invertibility of all rules, admissibility of the structural rules, termination of proof-search, as well as syntactic cut-elimination. In the second part we study the logic of common knowledge, a modal logic with a fixpoint modality. We look at two infinitary proof systems for this logic: an existing one based on ordinary sequents, for which no syntactic cut-elimination procedure is known, and a new one based on nested sequents. We see how nested sequents, in contrast to ordinary sequents, allow for syntactic cut-elimination and thus allow us to obtain an ordinal upper bound on the length of proofs. iii Contents 1 Introduction 1 2 Systems for Basic Normal Modal Logics 5 2.1 ModalAxiomsasLogicalRules . 6 2.1.1 TheSequentSystems .................... 6 2.1.2 Soundness........................... 12 2.1.3 Completeness........................
    [Show full text]
  • Sequent-Type Calculi for Systems of Nonmonotonic Paraconsistent Logics
    Sequent-Type Calculi for Systems of Nonmonotonic Paraconsistent Logics Tobias Geibinger Hans Tompits Databases and Artificial Intelligence Group, Knowledge-Based Systems Group, Institute of Logic and Computation, Institute of Logic and Computation, Technische Universit¨at Wien, Technische Universit¨at Wien, Favoritenstraße 9-11, A-1040 Vienna, Austria Favoritenstraße 9-11, A-1040 Vienna, Austria [email protected] [email protected] Paraconsistent logics constitute an important class of formalisms dealing with non-trivial reasoning from inconsistent premisses. In this paper, we introduce uniform axiomatisations for a family of nonmonotonic paraconsistent logics based on minimal inconsistency in terms of sequent-type proof systems. The latter are prominent and widely-used forms of calculi well-suited for analysing proof search. In particular, we provide sequent-type calculi for Priest’s three-valued minimally inconsistent logic of paradox, and for four-valued paraconsistent inference relations due to Arieli and Avron. Our calculi follow the sequent method first introduced in the context of nonmonotonic reasoning by Bonatti and Olivetti, whose distinguishing feature is the use of a so-called rejection calculus for axiomatising invalid formulas. In fact, we present a general method to obtain sequent systems for any many-valued logic based on minimal inconsistency, yielding the calculi for the logics of Priest and of Arieli and Avron as special instances. 1 Introduction Paraconsistent logics reject the principle of explosion, also known as ex falso sequitur quodlibet, which holds in classical logic and allows the derivation of any assertion from a contradiction. The motivation behind paraconsistent logics is simple, as contradictory theories may still contain useful information, hence we would like to be able to draw non-trivial conclusions from said theories.
    [Show full text]
  • 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.
    [Show full text]
  • Linear Logic Programming Dale Miller INRIA/Futurs & Laboratoire D’Informatique (LIX) Ecole´ Polytechnique, Rue De Saclay 91128 PALAISEAU Cedex FRANCE
    1 An Overview of Linear Logic Programming Dale Miller INRIA/Futurs & Laboratoire d’Informatique (LIX) Ecole´ polytechnique, Rue de Saclay 91128 PALAISEAU Cedex FRANCE Abstract Logic programming can be given a foundation in sequent calculus by viewing computation as the process of building a cut-free sequent proof bottom-up. The first accounts of logic programming as proof search were given in classical and intuitionistic logic. Given that linear logic allows richer sequents and richer dynamics in the rewriting of sequents during proof search, it was inevitable that linear logic would be used to design new and more expressive logic programming languages. We overview how linear logic has been used to design such new languages and describe briefly some applications and implementation issues for them. 1.1 Introduction It is now commonplace to recognize the important role of logic in the foundations of computer science. When a major new advance is made in our understanding of logic, we can thus expect to see that advance ripple into many areas of computer science. Such rippling has been observed during the years since the introduction of linear logic by Girard in 1987 [Gir87]. Since linear logic embraces computational themes directly in its design, it often allows direct and declarative approaches to compu- tational and resource sensitive specifications. Linear logic also provides new insights into the many computational systems based on classical and intuitionistic logics since it refines and extends these logics. There are two broad approaches by which logic, via the theory of proofs, is used to describe computation [Mil93]. One approach is the proof reduction paradigm, which can be seen as a foundation for func- 1 2 Dale Miller tional programming.
    [Show full text]
  • Permutability of Proofs in Intuitionistic Sequent Calculi
    Permutabilityofproofsinintuitionistic sequent calculi Roy Dyckho Scho ol of Mathematical Computational Sciences St Andrews University St Andrews Scotland y Lus Pinto Departamento de Matematica Universidade do Minho Braga Portugal Abstract Weprove a folklore theorem that two derivations in a cutfree se quent calculus for intuitioni sti c prop ositional logic based on Kleenes G are interp ermutable using a set of basic p ermutation reduction rules derived from Kleenes work in i they determine the same natu ral deduction The basic rules form a conuentandweakly normalisin g rewriting system We refer to Schwichtenb ergs pro of elsewhere that a mo dication of this system is strongly normalising Key words intuitionistic logic pro of theory natural deduction sequent calcu lus Intro duction There is a folklore theorem that twointuitionistic sequent calculus derivations are really the same i they are interp ermutable using p ermutations as de scrib ed by Kleene in Our purp ose here is to make precise and provesuch a p ermutability theorem Prawitz showed howintuitionistic sequent calculus derivations determine LJ to NJ here we consider only natural deductions via a mapping from the cutfree derivations and normal natural deductions resp ectively and in eect that this mapping is surjectiveby constructing a rightinverse of from NJ to LJ Zucker showed that in the negative fragment of the calculus c LJ ie LJ including cut two derivations have the same image under i they are interconvertible using a sequence of p ermutativeconversions eg p
    [Show full text]
  • Gentzen Sequent Calculus GL
    Chapter 11 (Part 2) Gentzen Sequent Calculus GL The proof system GL for the classical propo- sitional logic is a version of the original Gentzen (1934) systems LK. A constructive proof of the completeness the- orem for the system GL is very similar to the proof of the completeness theorem for the system RS. Expressions of the system like in the original Gentzen system LK are Gentzen sequents. Hence we use also a name Gentzen sequent calculus. 1 Language of GL: L = Lf[;\;);:;g. We add a new symbol to the alphabet: ¡!. It is called a Gentzen arrow. The sequents are built out of ¯nite sequences (empty included) of formulas, i.e. elements of F¤, and the additional sign ¡!. We denote, as in the RS system, the ¯nite sequences of formulas by Greek capital let- ters ¡; ¢; §, with indices if necessary. Sequent de¯nition: a sequent is the expres- sion ¡ ¡! ¢; where ¡; ¢ 2 F¤. Meaning of sequents Intuitively, we interpret a sequent A1; :::; An ¡! B1; :::; Bm; where n; m ¸ 1 as a formula (A1 \ ::: \ An) ) (B1 [ ::: [ Bm): The sequent: A1; :::; An ¡! (where n ¸ 1) means that A1 \ ::: \ An yields a contra- diction. The sequent ¡! B1; :::; Bm (where m ¸ 1) means j= (B1 [ ::: [ Bm). The empty sequent: ¡! means a contra- diction. 2 Given non empty sequences: ¡, ¢, we de- note by σ¡ any conjunction of all formulas of ¡, and by ±¢ any disjunction of all formulas of ¢. The intuitive semantics (meaning, interpre- tation) of a sequent ¡ ¡! ¢ (where ¡; ¢ are nonempty) is ¡ ¡! ¢ ´ (σ¡ ) ±¢): 3 Formal semantics for sequents (expressions of GL) Let v : V AR ¡! fT;F g be a truth assign- ment, v¤ its (classical semantics) extension to the set of formulas F.
    [Show full text]
  • Towards the Automated Generation of Focused Proof Systems
    Towards the Automated Generation of Focused Proof Systems Vivek Nigam Giselle Reis Leonardo Lima Federal University of Para´ıba, Brazil Inria & LIX, France Federal University of Para´ıba, Brazil [email protected] [email protected] [email protected] This paper tackles the problem of formulating and proving the completeness of focused-like proof systems in an automated fashion. Focusing is a discipline on proofs which structures them into phases in order to reduce proof search non-determinism. We demonstrate that it is possible to construct a complete focused proof system from a given un-focused proof system if it satisfies some conditions. Our key idea is to generalize the completeness proof based on permutation lemmas given by Miller and Saurin for the focused linear logic proof system. This is done by building a graph from the rule permutation relation of a proof system, called permutation graph. We then show that from the per- mutation graph of a given proof system, it is possible to construct a complete focused proof system, and additionally infer for which formulas contraction is admissible. An implementation for building the permutation graph of a system is provided. We apply our technique to generate the focused proof systems MALLF, LJF and LKF for linear, intuitionistic and classical logics, respectively. 1 Introduction In spite of its widespread use, the proposition and completeness proofs of focused proof systems are still an ad-hoc and hard task, done for each individual system separately. For example, the original completeness proof for the focused linear logic proof system (LLF) [1] is very specific to linear logic.
    [Show full text]
  • The Sequent Calculus
    Chapter udf The Sequent Calculus This chapter presents Gentzen's standard sequent calculus LK for clas- sical first-order logic. It could use more examples and exercises. To include or exclude material relevant to the sequent calculus as a proof system, use the \prfLK" tag. seq.1 Rules and Derivations fol:seq:rul: For the following, let Γ; ∆, Π; Λ represent finite sequences of sentences. sec Definition seq.1 (Sequent). A sequent is an expression of the form Γ ) ∆ where Γ and ∆ are finite (possibly empty) sequences of sentences of the lan- guage L. Γ is called the antecedent, while ∆ is the succedent. The intuitive idea behind a sequent is: if all of the sentences in the an- explanation tecedent hold, then at least one of the sentences in the succedent holds. That is, if Γ = h'1;:::;'mi and ∆ = h 1; : : : ; ni, then Γ ) ∆ holds iff ('1 ^ · · · ^ 'm) ! ( 1 _···_ n) holds. There are two special cases: where Γ is empty and when ∆ is empty. When Γ is empty, i.e., m = 0, ) ∆ holds iff 1 _···_ n holds. When ∆ is empty, i.e., n = 0, Γ ) holds iff :('1 ^ · · · ^ 'm) does. We say a sequent is valid iff the corresponding sentence is valid. If Γ is a sequence of sentences, we write Γ; ' for the result of appending ' to the right end of Γ (and '; Γ for the result of appending ' to the left end of Γ ). If ∆ is a sequence of sentences also, then Γ; ∆ is the concatenation of the two sequences. 1 Definition seq.2 (Initial Sequent).
    [Show full text]
  • Relating Natural Deduction and Sequent Calculus for Intuitionistic Non-Commutative Linear Logic
    MFPS XV Preliminary Version Relating Natural Deduction and Sequent Calculus for Intuitionistic Non-Commutative Linear Logic Jeff Polakow 1 and Frank Pfenning 2 Department of Computer Science Carnegie Mellon University Pittsburgh, Pennsylvania, USA Abstract We present a sequent calculus for intuitionistic non-commutative linear logic (IN- CLL), show that it satisfies cut elimination, and investigate its relationship to a natural deduction system for the logic. We show how normal natural deductions correspond to cut-free derivations, and arbitrary natural deductions to sequent derivations with cut. This gives us a syntactic proof of normalization for a rich system of non-commutative natural deduction and its associated λ-calculus. IN- CLL conservatively extends linear logic with means to express sequencing, which has applications in functional programming, logical frameworks, logic programming, and natural language parsing. 1 Introduction Linear logic [11] has been described as a logic of state because it views linear hypotheses as resources which may be consumed in the course of a deduction. It thereby significantly extends the expressive power of both classical and intuitionistic logics, yet it does not offer means to express sequencing. This is possible in non-commutative linear logic [1,5,2] which goes back to the seminal work by Lambek [16]. In [20] we introduced a system of natural deduction for intuitionistic non- commutative linear logic (INCLL) which conservatively extends intuitionistic linear logic. The associated proof term calculus is a λ-calculus with functions that must use their arguments in a specified order which is useful to capture 1 [email protected], partially supported by the National Science Foundation under grant CCR-9804014.
    [Show full text]
  • A Tutorial on Proof Systems and Typed Lambda-Calculi
    University of Pennsylvania ScholarlyCommons Technical Reports (CIS) Department of Computer & Information Science October 1991 Constructive Logics Part I: A Tutorial on Proof Systems and Typed Lambda-Calculi Jean H. Gallier University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/cis_reports Recommended Citation Jean H. Gallier, "Constructive Logics Part I: A Tutorial on Proof Systems and Typed Lambda-Calculi", . October 1991. University of Pennsylvania Department of Computer and Information Science Technical Report No. MS-CIS-91-74. This paper is posted at ScholarlyCommons. https://repository.upenn.edu/cis_reports/410 For more information, please contact [email protected]. Constructive Logics Part I: A Tutorial on Proof Systems and Typed Lambda- Calculi Abstract The purpose of this paper is to give an exposition of material dealing with constructive logic, typed λ- calculi, and linear logic. The emergence in the past ten years of a coherent field of esearr ch often named "logic and computation" has had two major (and related) effects: firstly, it has rocked vigorously the world of mathematical logic; secondly, it has created a new computer science discipline, which spans from what is traditionally called theory of computation, to programming language design. Remarkably, this new body of work relies heavily on some "old" concepts found in mathematical logic, like natural deduction, sequent calculus, and λ-calculus (but often viewed in a different light), and also on some newer concepts. Thus, it may be quite a challenge to become initiated to this new body of work (but the situation is improving, there are now some excellent texts on this subject matter).
    [Show full text]
  • Constructive Provability Logic
    Constructive Provability Logic Robert J. Simmons and Bernardo Toninho We present constructive provability logic, an intuitionstic modal logic that validates the L¨obrule of G¨odel and L¨ob'sprovability logic by permitting logical reflection over provability. Two distinct variants of this logic, CPL and CPL*, are presented in natural deduction and sequent calculus forms which are then shown to be equivalent. In addition, we discuss the use of constructive provability logic to justify stratified negation in logic programming within an intuitionstic and structural proof theory. All theorems presented in this paper are formalized in the Agda proof assistant. An earlier version of this work was presented at IMLA 2011 [Simmons and Toninho 2011]. Draft as of May 29, 2012 Consider the following propositions (where \⊃" represents implication): 8x: 8y: edge(x; y) ⊃ edge(y; x) 8x: 8y: edge(x; y) ⊃ path(x; y) 8x: 8y: 8z: edge(x; y) ⊃ path(y; z) ⊃ path(x; z) One way to think of these propositions is as rules in a bottom-up logic program. This gives them an operational meaning: given some known set of facts, a bottom- up logic program uses rules to derive more facts. If we start with the single fact edge(a; b), we can derive edge(b; a) by using the first rule (taking x = a and y = b), and then, using this new fact, we can derive path(b; a) by using the second rule (taking x = b and y = a). Finally, from the original edge(a; b) fact and the new path(b; a) fact, we can derive path(a; a) using the third rule (taking x = a, y = b, and z = a).
    [Show full text]
  • Introduction to Sequent Calculus
    Introduction to Sequent Calculus Tudor Jebelean RISC{Linz Johannes Kepler University October 25, 2019 Abstract This is a tutorial introduction to sequent calculus, starting from a certain natural style of proving, and based on an example. We present this as a an exercise in constructing the abstract model \sequent calculus" of the of the real world method of proving logical statements in \natural style". 1 Introduction The purpose of mathematical logic is to study the real{world1 activity of proving mathematical statements and to construct and analyse abstract models of it. In this presentation we analyse a concrete example of proof developed in the \natural style" which is used by mathematicians, we identify the essential aspects of the proof method, and we introduce sequent calculus as the mathe- matical model which can be constructed as an abstraction of it. 2 Proving in Natural Style 2.1 Proof Example Let us consider the propositional formula: (G0) ((A ) C) _ (B ) C)) ) ((A ^ B) ) C): The proof this formula, by the intuitive method which is \built in" our brain, as the result of our mathematical training, may look as follows: [1] For proving (G0), we assume: (A1) (A ) C) _ (B ) C) and we prove: (G1) (A ^ B) ) C: 1Mathematics operates on abstract models, however the activity of mathematicians takes place in the real world, which therefore also includes the proofs they develop. 1 [2] For proving (G1), we assume: (A2) A ^ B and we prove: (G2) C: [3] From (A2) we obtain: (A2.1) A and (A2.2) B: [4] We prove (G2) by case distinction, using the disjunction (A1).
    [Show full text]