Paraconsistent Logic: a Proof-Theoretical Approach*
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Logic Programming in a Fragment of Intuitionistic Linear Logic ∗
Logic Programming in a Fragment of Intuitionistic Linear Logic ¤ Joshua S. Hodas Dale Miller Computer Science Department Computer Science Department Harvey Mudd College University of Pennsylvania Claremont, CA 91711-5990 USA Philadelphia, PA 19104-6389 USA [email protected] [email protected] Abstract When logic programming is based on the proof theory of intuitionistic logic, it is natural to allow implications in goals and in the bodies of clauses. Attempting to prove a goal of the form D ⊃ G from the context (set of formulas) Γ leads to an attempt to prove the goal G in the extended context Γ [ fDg. Thus during the bottom-up search for a cut-free proof contexts, represented as the left-hand side of intuitionistic sequents, grow as stacks. While such an intuitionistic notion of context provides for elegant specifications of many computations, contexts can be made more expressive and flexible if they are based on linear logic. After presenting two equivalent formulations of a fragment of linear logic, we show that the fragment has a goal-directed interpretation, thereby partially justifying calling it a logic programming language. Logic programs based on the intuitionistic theory of hereditary Harrop formulas can be modularly embedded into this linear logic setting. Programming examples taken from theorem proving, natural language parsing, and data base programming are presented: each example requires a linear, rather than intuitionistic, notion of context to be modeled adequately. An interpreter for this logic programming language must address the problem of splitting contexts; that is, when attempting to prove a multiplicative conjunction (tensor), say G1 G2, from the context ∆, the latter must be split into disjoint contexts ∆1 and ∆2 for which G1 follows from ∆1 and G2 follows from ∆2. -
Relevant and Substructural Logics
Relevant and Substructural Logics GREG RESTALL∗ PHILOSOPHY DEPARTMENT, MACQUARIE UNIVERSITY [email protected] June 23, 2001 http://www.phil.mq.edu.au/staff/grestall/ Abstract: This is a history of relevant and substructural logics, written for the Hand- book of the History and Philosophy of Logic, edited by Dov Gabbay and John Woods.1 1 Introduction Logics tend to be viewed of in one of two ways — with an eye to proofs, or with an eye to models.2 Relevant and substructural logics are no different: you can focus on notions of proof, inference rules and structural features of deduction in these logics, or you can focus on interpretations of the language in other structures. This essay is structured around the bifurcation between proofs and mod- els: The first section discusses Proof Theory of relevant and substructural log- ics, and the second covers the Model Theory of these logics. This order is a natural one for a history of relevant and substructural logics, because much of the initial work — especially in the Anderson–Belnap tradition of relevant logics — started by developing proof theory. The model theory of relevant logic came some time later. As we will see, Dunn's algebraic models [76, 77] Urquhart's operational semantics [267, 268] and Routley and Meyer's rela- tional semantics [239, 240, 241] arrived decades after the initial burst of ac- tivity from Alan Anderson and Nuel Belnap. The same goes for work on the Lambek calculus: although inspired by a very particular application in lin- guistic typing, it was developed first proof-theoretically, and only later did model theory come to the fore. -
Linear Logic : Its Syntax and Semantics
LINEAR LOGIC : ITS SYNTAX AND SEMANTICS Jean-Yves Girard Laboratoire de Math´ematiques Discr`etes UPR 9016 { CNRS 163, Avenue de Luminy, Case 930 F-13288 Marseille Cedex 09 [email protected] 1 THE SYNTAX OF LINEAR LOGIC 1.1 The connectives of linear logic Linear logic is not an alternative logic ; it should rather be seen as an exten- sion of usual logic. Since there is no hope to modify the extant classical or intuitionistic connectives 1, linear logic introduces new connectives. 1.1.1 Exponentials : actions vs situations Classical and intuitionistic logics deal with stable truths : if A and A B, then B, but A still holds. ) This is perfect in mathematics, but wrong in real life, since real implication is causal. A causal implication cannot be iterated since the conditions are modified after its use ; this process of modification of the premises (conditions) is known in physics as reaction. For instance, if A is to spend $1 on a pack of cigarettes and B is to get them, you lose $1 in this process, and you cannot do it a second time. The reaction here was that $1 went out of your pocket. The first objection to that view is that there are in mathematics, in real life, cases where reaction does not exist or can be neglected : think of a lemma which is forever true, or of a Mr. Soros, who has almost an infinite amount of dollars. 1: Witness the fate of non-monotonic \logics" who tried to tamper with logical rules with- out changing the basic operations : : : 1 2 Jean-Yves Girard Such cases are situations in the sense of stable truths. -
Categorical Models for Intuitionistic and Linear Type Theory
Categorical Models for Intuitionistic and Linear Type Theory Maria Emilia Maietti, Valeria de Paiva, and Eike Ritter? School of Computer Science, University of Birmingham Edgbaston, Birmingham B15 2TT, United Kingdom mem,vdp,exr @cs.bham.ac.uk { } Abstract. This paper describes the categorical semantics of a system of mixed intuitionistic and linear type theory (ILT). ILT was proposed by G. Plotkin and also independently by P. Wadler. The logic associ- ated with ILT is obtained as a combination of intuitionistic logic with intuitionistic linear logic, and can be embedded in Barber and Plotkin’s Dual Intuitionistic Linear Logic (DILL). However, unlike DILL, the logic for ILT lacks an explicit modality ! that translates intuitionistic proofs into linear ones. So while the semantics of DILL can be given in terms of monoidal adjunctions between symmetric monoidal closed categories and cartesian closed categories, the semantics of ILT is better presented via fibrations. These interpret double contexts, which cannot be reduced to linear ones. In order to interpret the intuitionistic and linear iden- tity axioms acting on the same type we need fibrations satisfying the comprehension axiom. 1 Introduction This paper arises from the need to fill a gap in the conceptual development of the xSLAM project. The xSLAM project is concerned with the design and implementation of abstract machines based on linear logic. For xSLAM we ini- tially developed a linear λ-calculus by adding explicit substitutions to Barber and Plotkin’s DILL [GdPR00]. We then considered the categorical models one obtains for both intuitionistic and linear logic with explicit substitutions on the style of Abadi et al. -
A Unifying Field in Logics: Neutrosophic Logic. Neutrosophy, Neutrosophic Set, Neutrosophic Probability and Statistics
FLORENTIN SMARANDACHE A UNIFYING FIELD IN LOGICS: NEUTROSOPHIC LOGIC. NEUTROSOPHY, NEUTROSOPHIC SET, NEUTROSOPHIC PROBABILITY AND STATISTICS (fourth edition) NL(A1 A2) = ( T1 ({1}T2) T2 ({1}T1) T1T2 ({1}T1) ({1}T2), I1 ({1}I2) I2 ({1}I1) I1 I2 ({1}I1) ({1} I2), F1 ({1}F2) F2 ({1} F1) F1 F2 ({1}F1) ({1}F2) ). NL(A1 A2) = ( {1}T1T1T2, {1}I1I1I2, {1}F1F1F2 ). NL(A1 A2) = ( ({1}T1T1T2) ({1}T2T1T2), ({1} I1 I1 I2) ({1}I2 I1 I2), ({1}F1F1 F2) ({1}F2F1 F2) ). ISBN 978-1-59973-080-6 American Research Press Rehoboth 1998, 2000, 2003, 2005 FLORENTIN SMARANDACHE A UNIFYING FIELD IN LOGICS: NEUTROSOPHIC LOGIC. NEUTROSOPHY, NEUTROSOPHIC SET, NEUTROSOPHIC PROBABILITY AND STATISTICS (fourth edition) NL(A1 A2) = ( T1 ({1}T2) T2 ({1}T1) T1T2 ({1}T1) ({1}T2), I1 ({1}I2) I2 ({1}I1) I1 I2 ({1}I1) ({1} I2), F1 ({1}F2) F2 ({1} F1) F1 F2 ({1}F1) ({1}F2) ). NL(A1 A2) = ( {1}T1T1T2, {1}I1I1I2, {1}F1F1F2 ). NL(A1 A2) = ( ({1}T1T1T2) ({1}T2T1T2), ({1} I1 I1 I2) ({1}I2 I1 I2), ({1}F1F1 F2) ({1}F2F1 F2) ). ISBN 978-1-59973-080-6 American Research Press Rehoboth 1998, 2000, 2003, 2005 1 Contents: Preface by C. Le: 3 0. Introduction: 9 1. Neutrosophy - a new branch of philosophy: 15 2. Neutrosophic Logic - a unifying field in logics: 90 3. Neutrosophic Set - a unifying field in sets: 125 4. Neutrosophic Probability - a generalization of classical and imprecise probabilities - and Neutrosophic Statistics: 129 5. Addenda: Definitions derived from Neutrosophics: 133 2 Preface to Neutrosophy and Neutrosophic Logic by C. -
Three New Genuine Five-Valued Logics
Three new genuine five-valued logics Mauricio Osorio1 and Claudia Zepeda2 1 Universidad de las Am´ericas-Puebla, 2 Benem´eritaUniversidad At´onomade Puebla fosoriomauri,[email protected] Abstract. We introduce three 5-valued paraconsistent logics that we name FiveASP1, FiveASP2 and FiveASP3. Each of these logics is genuine and paracomplete. FiveASP3 was constructed with the help of Answer Sets Programming. The new value is called e attempting to model the notion of ineffability. If one drops e from any of these logics one obtains a well known 4-valued logic introduced by Avron. If, on the other hand one drops the \implication" connective from any of these logics, one obtains Priest logic FDEe. We present some properties of these logics. Keywords: many-valued logics, genuine paraconsistent logic, ineffabil- ity. 1 Introduction Belnap [16] claims that a 4-valued logic is a suitable framework for computer- ized reasoning. Avron in [3,2,4,1] supports this thesis. He shows that a 4-valued logic naturally express true, false, inconsistent or uncertain information. Each of these concepts is represented by a particular logical value. Furthermore in [3] he presents a sound and complete axiomatization of a family of 4-valued logics. On the other hand, Priest argues in [22] that a 4-valued logic models very well the four possibilities explained before, but here in the context of Buddhist meta-physics, see for instance [26]. This logic is called FDE, but such logic fails to satisfy the well known Modus Ponens inference rule. If one removes the im- plication connective in this logic, it corresponds to the corresponding fragment of any of the logics studied by Avron. -
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. -
Linear Logic
App eared in SIGACT Linear Logic Patrick Lincoln lincolncslsricom SRI and Stanford University Linear Logic Linear logic was intro duced by Girard in Since then many results have supp orted Girards claims such as Linear logic is a resource conscious logic Increasingly computer scientists have recognized linear logic as an expressive and p owerful logic with deep connec tions to concepts from computer science The expressive p ower of linear logic is evidenced by some very natural enco dings of computational mo dels such as Petri nets counter machines Turing machines and others This note presents an intuitive overview of linear logic some recent theoretical results and some interesting applications of linear logic to computer science Other intro ductions to linear logic may b e found in Linear Logic vs Classical and Intuitionistic Logics Linear logic diers from classical and intuitionistic logic in several fundamental ways Clas sical logic may b e viewed as if it deals with static prop ositions ab out the world where each prop osition is either true or false Because of the static nature of prop ositions in classical logic one may duplicate prop ositions P implies P and P Implicitly we learn that one P is as go o d as two Also one may discard prop ositions P and Q implies P Here the prop osition Q has b een thrown away Both of these sentences are valid in classical logic for any P and Q In linear logic these sentences are not valid A linear logician might ask Where did the second P come from and Where did the Q go Of course these -
13 QUESTIONS ABOUT UNIVERSAL LOGIC 13 Questions to Jean-Yves B´Eziau, by Linda Eastwood
Bulletin of the Section of Logic Volume 35:2/3 (2006), pp. 133–150 Jean-Yves B´eziau 13 QUESTIONS ABOUT UNIVERSAL LOGIC 13 questions to Jean-Yves B´eziau, by Linda Eastwood The expression “universal logic” prompts a number of misunderstandings pressing up against to the confusion prevailing nowadays around the very notion of logic. In order to clear up such equivocations, I prepared a series of questions to Jean-Yves B´eziau,who has been working for many years on his project of universal logic, recently in the University of Neuchˆatel, Switzerland. 1. Although your proposal to develop a universal logic is very appealing, isn’t it a utopian one? Isn’t it an absurd, or even dangerous thing to believe that it would be possible to develop a unique logic accounting for everything? Let us immediately reject some misunderstanding; universal logic, as I understand it, is not one universal logic. In fact, from the viewpoint of universal logic the existence of one universal logic is not even possible, and this is a result that can easily be shown. One might thus say somehow ironically the following: according to universal logic there is no universal logic. Some people in some countries have always tried to elaborate a uni- versal system that would account for any sort of reasoning, or reasoning as a whole. Aristotelian logic was depicted itself as a universal one. More recently, first-order classical logic appeared to some as a universal system accounting for mathematical reasoning as well as current one, that is, the one used to buy your bread at the bakery. -
Consistency, Contradiction and Negation. Logic, Epistemology, and the Unity of Science Series
BOOK REVIEW: CARNIELLI, W., CONIGLIO, M. Paraconsistent Logic: Consistency, Contradiction and Negation. Logic, Epistemology, and the Unity of Science Series. (New York: Springer, 2016. ISSN: 2214-9775.) Henrique Antunes Vincenzo Ciccarelli State University of Campinas State University of Campinas Department of Philosophy Department of Philosophy Campinas, SP Campinas, SP Brazil Brazil [email protected] [email protected] Article info CDD: 160 Received: 01.12.2017; Accepted: 30.12.2017 DOI: http://dx.doi.org/10.1590/0100-6045.2018.V41N2.HV Keywords: Paraconsistent Logic LFIs ABSTRACT Review of the book 'Paraconsistent Logic: Consistency, Contradiction and Negation' (2016), by Walter Carnielli and Marcelo Coniglio The principle of explosion (also known as ex contradictione sequitur quodlibet) states that a pair of contradictory formulas entails any formula whatsoever of the relevant language and, accordingly, any theory regimented on the basis of a logic for which this principle holds (such as classical and intuitionistic logic) will turn out to be trivial if it contains a pair of theorems of the form A and ¬A (where ¬ is a negation operator). A logic is paraconsistent if it rejects the principle of explosion, allowing thus for the possibility of contradictory and yet non-trivial theories. Among the several paraconsistent logics that have been proposed in the literature, there is a particular family of (propositional and quantified) systems known as Logics of Formal Inconsistency (LFIs), developed and thoroughly studied Manuscrito – Rev. Int. Fil. Campinas, v. 41, n. 2, pp. 111-122, abr.-jun. 2018. Henrique Antunes & Vincenzo Ciccarelli 112 within the Brazilian tradition on paraconsistency. A distinguishing feature of the LFIs is that although they reject the general validity of the principle of explosion, as all other paraconsistent logics do, they admit a a restrcited version of it known as principle of gentle explosion. -
Linear Logic Lecture Notes for CIS 670
Linear Logic Lecture Notes for CIS 670 Steve Zdancewic University of Pennsylvania February 25, 2014 Linear Logic Lecture Notes Draft of: February 25, 2014 Contents 1 Overview 5 1.1 Introduction . .5 2 Intuitionistic Linear Logic 7 2.1 The Multiplicative Fragment . .8 2.1.1 Multiplicative Conjunction . 10 2.1.2 Multiplicative Conjunction Unit . 11 2.1.3 Linear Implication . 11 2.1.4 Summary . 12 2.2 The Additive Fragment . 13 2.2.1 Additive Products . 13 2.2.2 Additive Product Unit . 15 2.2.3 Additive Sums . 15 2.2.4 Additive Sum Unit . 16 2.3 Persistence and the Exponential Modality . 16 3 Terms for ILL 21 3.1 Evaluations . 21 3.2 Call-by-Name Translation of Intuitionistic Logic . 27 3.3 Call-by-Value Translation of Intuitionistic Logic . 27 4 Proof Search and ILL 29 4.1 Normal Proofs . 29 4.2 Sequent Calculus . 30 Linear Logic Lecture Notes Draft of: February 25, 2014 Linear Logic Lecture Notes Draft of: February 25, 2014 Chapter 1 Overview 1.1 Introduction • Linear logic was introduced in 1987 by Jean-Yves Girard [62]. – Spawned hundreds of subsequent papers, with many(!) variants (substructural logics) – Very influential paper: cited > 4250 times according to Google Scholar. Why? – Linear logic is a generalization of “ordinary” logic in such a way that it becomes “resource conscious”. * Key idea: a resource is a “hypothesis” that can be used only once (hence it is used up) * Weakening and Contraction rules of ordinary propositional logic * Also possible to ephasize the “communication” behavior: parts of the proof that can “interact” -
Efficient Paraconsistent Reasoning with Ontologies and Rules
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI 2015) Efficient Paraconsistent Reasoning with Ontologies and Rules∗ Tobias Kaminski and Matthias Knorr and Joao˜ Leite NOVA LINCS Departamento de Informatica´ Universidade NOVA de Lisboa 2829-516 Caparica, Portugal Abstract Krotzsch¨ et al., 2011], others follow a hybrid combination of ontologies with nonmonotonic rules, either providing a Description Logic (DL) based ontologies and non- modular approach where rules and ontologies use their own monotonic rules provide complementary features semantics, and allowing limited interaction between them whose combination is crucial in many applications. [Eiter et al., 2008], or defining a unifying framework for both In hybrid knowledge bases (KBs), which combine components [Motik and Rosati, 2010; Knorr et al., 2011]. both formalisms, for large real-world applications, Equipped with semantics that are faithful to their constituting often integrating knowledge originating from dif- parts, these proposals allow for the specification of so-called ferent sources, inconsistencies can easily occur. hybrid knowledge bases (hybrid KBs) either from scratch, These commonly trivialize standard reasoning and benefiting from the added expressivity, or by combining ex- prevent us from drawing any meaningful conclu- isting ontologies and rule bases. sions. When restoring consistency by changing the The complex interactions between the ontology component KB is not possible, paraconsistent reasoning offers and the rule component of these hybrid KBs – even more so an alternative by allowing us to obtain meaningful when they result from combining existing ontologies and rule conclusions from its consistent part. bases independently developed – can easily lead to contra- In this paper, we address the problem of efficiently dictions, which, under classical semantics, trivialize standard obtaining meaningful conclusions from (possibly reasoning and prevent us from drawing any meaningful con- inconsistent) hybrid KBs.