Results 1  10
of
30
Focusing and Polarization in Linear, Intuitionistic, and Classical Logics
, 2009
"... A focused proof system provides a normal form to cutfree proofs in which the application of invertible and noninvertible inference rules is structured. Within linear logic, the focused proof system of Andreoli provides an elegant and comprehensive normal form for cutfree proofs. Within intuitioni ..."
Abstract

Cited by 44 (19 self)
 Add to MetaCart
A focused proof system provides a normal form to cutfree proofs in which the application of invertible and noninvertible inference rules is structured. Within linear logic, the focused proof system of Andreoli provides an elegant and comprehensive normal form for cutfree proofs. Within intuitionistic and classical logics, there are various different proof systems in the literature that exhibit focusing behavior. These focused proof systems have been applied to both the proof search and the proof normalization approaches to computation. We present a new, focused proof system for intuitionistic logic, called LJF, and show how other intuitionistic proof systems can be mapped into the new system by inserting logical connectives that prematurely stop focusing. We also use LJF to design a focused proof system LKF for classical logic. Our approach to the design and analysis of these systems is based on the completeness of focusing in linear logic and on the notion of polarity that appears in Girard’s LC and LU proof systems.
Least and greatest fixed points in linear logic Extended Version
, 2007
"... david.baelde at enslyon.org dale.miller at inria.fr Abstract. The firstorder theory of MALL (multiplicative, additive linear logic) over only equalities is an interesting but weak logic since it cannot capture unbounded (infinite) behavior. Instead of accounting for unbounded behavior via the addi ..."
Abstract

Cited by 35 (12 self)
 Add to MetaCart
david.baelde at enslyon.org dale.miller at inria.fr Abstract. The firstorder theory of MALL (multiplicative, additive linear logic) over only equalities is an interesting but weak logic since it cannot capture unbounded (infinite) behavior. Instead of accounting for unbounded behavior via the addition of the exponentials (! and?), we add least and greatest fixed point operators. The resulting logic, which we call µMALL = , satisfies two fundamental proof theoretic properties. In particular, µMALL = satisfies cutelimination, which implies consistency, and has a complete focused proof system. This second result about focused proofs provides a strong normal form for cutfree proof structures that can be used, for example, to help automate proof search. We then consider applying these two results about µMALL = to derive a focused proof system for an intuitionistic logic extended with induction and coinduction. The traditional approach to encoding intuitionistic logic into linear logic relies heavily on using the exponentials, which unfortunately weaken the focusing discipline. We get a better focused proof system by observing that certain fixed points satisfy the structural rules of weakening and contraction (without using exponentials). The resulting focused proof system for intuitionistic logic is closely related to the one implemented in Bedwyr, a recent model checker based on logic programming. We discuss how our proof theory might be used to build a computational system that can partially automate induction and coinduction. 1
Focusing on binding and computation
 In IEEE Symposium on Logic in Computer Science
, 2008
"... Variable binding is a prevalent feature of the syntax and proof theory of many logical systems. In this paper, we define a programming language that provides intrinsic support for both representing and computing with binding. This language is extracted as the CurryHoward interpretation of a focused ..."
Abstract

Cited by 21 (6 self)
 Add to MetaCart
Variable binding is a prevalent feature of the syntax and proof theory of many logical systems. In this paper, we define a programming language that provides intrinsic support for both representing and computing with binding. This language is extracted as the CurryHoward interpretation of a focused sequent calculus with two kinds of implication, of opposite polarity. The representational arrow extends systems of definitional reflection with a notion of scoped inference rules, which are used to represent binding. On the other hand, the usual computational arrow classifies recursive functions defined by patternmatching. Unlike many previous approaches, both kinds of implication are connectives in a single logic, which serves as a rich logical framework capable of representing inference rules that mix binding and computation. 1
A unified sequent calculus for focused proofs
 In LICS: 24th Symp. on Logic in Computer Science
, 2009
"... Abstract—We present a compact sequent calculus LKU for classical logic organized around the concept of polarization. Focused sequent calculi for classical logic, intuitionistic logic, and multiplicativeadditive linear logic are derived as fragments of LKU by increasing the sensitivity of specialize ..."
Abstract

Cited by 13 (7 self)
 Add to MetaCart
Abstract—We present a compact sequent calculus LKU for classical logic organized around the concept of polarization. Focused sequent calculi for classical logic, intuitionistic logic, and multiplicativeadditive linear logic are derived as fragments of LKU by increasing the sensitivity of specialized structural rules to polarity information. We develop a unified, streamlined framework for proving cutelimination in the various fragments. Furthermore, each sublogic can interact with other fragments through cut. We also consider the possibility of introducing classicallinear hybrid logics. KeywordsProof theory; focused proof systems; linear logic I.
Incorporating tables into proofs
"... nigam at lix.inria.fr dale.miller at inria.fr Abstract. We consider the problem of automating and checking the use of previously proved lemmas in the proof of some main theorem. In particular, we call the collection of such previously proved results a table and use a partial order on the table’s ent ..."
Abstract

Cited by 13 (5 self)
 Add to MetaCart
nigam at lix.inria.fr dale.miller at inria.fr Abstract. We consider the problem of automating and checking the use of previously proved lemmas in the proof of some main theorem. In particular, we call the collection of such previously proved results a table and use a partial order on the table’s entries to denote the (provability) dependency relationship between tabled items. Tables can be used in automated deduction to store previously proved subgoals and in interactive theorem proving to store a sequence of lemmas introduced by a user to direct the proof system towards some final theorem. Tables of literals can be incorporated into sequent calculus proofs using two ideas. First, cuts are used to incorporate tabled items into a proof: one premise of the cut requires a proof of the lemma and the other branch of the cut inserts the lemma into the set of assumptions. Second, to ensure that lemma is not reproved, we exploit the fact that in focused proofs, atoms can have different polarity. Using these ideas, simple logic engines that do focused proof search (such as logic programming interpreters) are able to check proofs for correctness with guarantees that previous work is not redone. We also discuss how a table can be seen as a proof object and discuss some possible uses of tablesasproofs. 1
Algorithmic specifications in linear logic with subexponentials
 In ACM SIGPLAN Conference on Principles and Practice of Declarative Programming (PPDP
, 2009
"... nigam at lix.polytechnique.fr, dale.miller at inria.fr The linear logic exponentials!, ? are not canonical: one can add to linear logic other such operators, say! l, ? l, which may or may not allow contraction and weakening, and where l is from some preordered set of labels. We shall call these add ..."
Abstract

Cited by 10 (6 self)
 Add to MetaCart
nigam at lix.polytechnique.fr, dale.miller at inria.fr The linear logic exponentials!, ? are not canonical: one can add to linear logic other such operators, say! l, ? l, which may or may not allow contraction and weakening, and where l is from some preordered set of labels. We shall call these additional operators subexponentials and use them to assign locations to multisets of formulas within a linear logic programming setting. Treating locations as subexponentials greatly increases the algorithmic expressiveness of logic. To illustrate this new expressiveness, we show that focused proof search can be precisely linked to a simple algorithmic specification language that contains whileloops, conditionals, and insertion into and deletion from multisets. We also give some general conditions for when a focused proof step can be executed in constant time. In addition, we propose a new logical connective that allows for the creation of new subexponentials, thereby further augmenting the algorithmic expressiveness of logic.
Focusing in linear metalogic
 In Proceedings of IJCAR: International Joint Conference on Automated Reasoning, volume 5195 of LNAI
, 2008
"... nigam at lix.polytechnique.fr dale.miller at inria.fr Abstract. It is well known how to use an intuitionistic metalogic to specify natural deduction systems. It is also possible to use linear logic as a metalogic for the specification of a variety of sequent calculus proof systems. Here, we show t ..."
Abstract

Cited by 9 (5 self)
 Add to MetaCart
nigam at lix.polytechnique.fr dale.miller at inria.fr Abstract. It is well known how to use an intuitionistic metalogic to specify natural deduction systems. It is also possible to use linear logic as a metalogic for the specification of a variety of sequent calculus proof systems. Here, we show that if we adopt different focusing annotations for such linear logic specifications, a range of other proof systems can also be specified. In particular, we show that natural deduction (normal and nonnormal), sequent proofs (with and without cut), tableaux, and proof systems using general elimination and general introduction rules can all be derived from essentially the same linear logic specification by altering focusing annotations. By using elementary linear logic equivalences and the completeness of focused proofs, we are able to derive new and modular proofs of the soundness and completeness of these various proofs systems for intuitionistic and classical logics. 1
Proof search specifications of bisimulation and modal logics for the πcalculus
 ACM Trans. on Computational Logic
"... We specify the operational semantics and bisimulation relations for the finite πcalculus within a logic that contains the ∇ quantifier for encoding generic judgments and definitions for encoding fixed points. Since we restrict to the finite case, the ability of the logic to unfold fixed points allo ..."
Abstract

Cited by 8 (6 self)
 Add to MetaCart
We specify the operational semantics and bisimulation relations for the finite πcalculus within a logic that contains the ∇ quantifier for encoding generic judgments and definitions for encoding fixed points. Since we restrict to the finite case, the ability of the logic to unfold fixed points allows this logic to be complete for both the inductive nature of operational semantics and the coinductive nature of bisimulation. The ∇ quantifier helps with the delicate issues surrounding the scope of variables within πcalculus expressions and their executions (proofs). We shall illustrate several merits of the logical specifications permitted by this logic: they are natural and declarative; they contain no sideconditions concerning names of variables while maintaining a completely formal treatment of such variables; differences between late and open bisimulation relations arise from familar logic distinctions; the interplay between the three quantifiers (∀, ∃, and ∇) and their scopes can explain the differences between early and late bisimulation and between various modal operators based on bound input and output actions; and proof search involving the application of inference rules, unification, and backtracking can provide complete proof systems for onestep transitions, bisimulation, and satisfaction in modal logic. We also illustrate how one can encode the πcalculus with replications, in an extended logic with induction and coinduction.
A Focused Approach to Combining Logics
, 2010
"... We present a compact sequent calculus LKU for classical logic organized around the concept of polarization. Focused sequent calculi for classical, intuitionistic, and multiplicativeadditive linear logics are derived as fragments of the host system by varying the sensitivity of specialized structura ..."
Abstract

Cited by 8 (5 self)
 Add to MetaCart
We present a compact sequent calculus LKU for classical logic organized around the concept of polarization. Focused sequent calculi for classical, intuitionistic, and multiplicativeadditive linear logics are derived as fragments of the host system by varying the sensitivity of specialized structural rules to polarity information. We identify a general set of criteria under which cut elimination holds in such fragments. From cut elimination we derive a unified proof of the completeness of focusing. Furthermore, each sublogic can interact with other fragments through cut. We examine certain circumstances, for example, in which a classical lemma can be used in an intuitionistic proof while preserving intuitionistic provability. We also examine the possibility of defining classicallinear hybrid logics.
Focused Inductive Theorem Proving
"... Abstract. Focused proof systems provide means for reducing and structuring the nondeterminism involved in searching for sequent calculus proofs. We present a focused proof system for a firstorder logic with inductive and coinductive definitions in which the introduction rules are partitioned into ..."
Abstract

Cited by 7 (3 self)
 Add to MetaCart
Abstract. Focused proof systems provide means for reducing and structuring the nondeterminism involved in searching for sequent calculus proofs. We present a focused proof system for a firstorder logic with inductive and coinductive definitions in which the introduction rules are partitioned into an asynchronous phase and a synchronous phase. These focused proofs allows us to naturally see proof search as being organized around interleaving intervals of computation and more general deduction. For example, entire Prologlike computations can be captured using a single synchronous phase and many modelchecking queries can be captured using an asynchronous phase followed by a synchronous phase. Leveraging these ideas, we have developed an interactive proof assistant, called Tac, for this logic. We describe its highlevel design and illustrate how it is capable of automatically proving many theorems using induction and coinduction. Since the automatic proof procedure is structured using focused proofs, its behavior is often rather easy to anticipate and modify. We illustrate the strength of Tac with several examples of proof developments, some achieved entirely automatically and others achieved with user guidance. 1