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Uniform proofs as a foundation for logic programming
 ANNALS OF PURE AND APPLIED LOGIC
, 1991
"... A prooftheoretic characterization of logical languages that form suitable bases for Prologlike programming languages is provided. This characterization is based on the principle that the declarative meaning of a logic program, provided by provability in a logical system, should coincide with its ..."
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Cited by 375 (109 self)
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A prooftheoretic characterization of logical languages that form suitable bases for Prologlike programming languages is provided. This characterization is based on the principle that the declarative meaning of a logic program, provided by provability in a logical system, should coincide with its operational meaning, provided by interpreting logical connectives as simple and fixed search instructions. The operational semantics is formalized by the identification of a class of cutfree sequent proofs called uniform proofs. A uniform proof is one that can be found by a goaldirected search that respects the interpretation of the logical connectives as search instructions. The concept of a uniform proof is used to define the notion of an abstract logic programming language, and it is shown that firstorder and higherorder Horn clauses with classical provability are examples of such a language. Horn clauses are then generalized to hereditary Harrop formulas and it is shown that firstorder and higherorder versions of this new class of formulas are also abstract logic programming languages if the inference rules are those of either intuitionistic or minimal logic. The programming language significance of the various generalizations to firstorder Horn clauses is briefly discussed.
Logic Programming in a Fragment of Intuitionistic Linear Logic
"... 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 ..."
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Cited by 303 (40 self)
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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 ∪ {D}. Thus during the bottomup search for a cutfree proof contexts, represented as the lefthand 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 goaldirected 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. Since there is an exponential number of such splits, it is important to delay the choice of a split as much as possible. A mechanism for the lazy splitting of contexts is presented based on viewing proof search as a process that takes a context, consumes part of it, and returns the rest (to be consumed elsewhere). In addition, we use collections of Kripke interpretations indexed by a commutative monoid to provide models for this logic programming language and show that logic programs admit a canonical model.
Higherorder logic programming
 HANDBOOK OF LOGIC IN AI AND LOGIC PROGRAMMING, VOLUME 5: LOGIC PROGRAMMING. OXFORD (1998
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Unification under a mixed prefix
 Journal of Symbolic Computation
, 1992
"... Unification problems are identified with conjunctions of equations between simply typed λterms where free variables in the equations can be universally or existentially quantified. Two schemes for simplifying quantifier alternation, called Skolemization and raising (a dual of Skolemization), are pr ..."
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Cited by 124 (13 self)
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Unification problems are identified with conjunctions of equations between simply typed λterms where free variables in the equations can be universally or existentially quantified. Two schemes for simplifying quantifier alternation, called Skolemization and raising (a dual of Skolemization), are presented. In this setting where variables of functional type can be quantified and not all types contain closed terms, the naive generalization of firstorder Skolemization has several technical problems that are addressed. The method of searching for preunifiers described by Huet is easily extended to the mixed prefix setting, although solving flexibleflexible unification problems is undecidable since types may be empty. Unification problems may have numerous incomparable unifiers. Occasionally, unifiers share common factors and several of these are presented. Various optimizations on the general unification search problem are as discussed. 1.
The πcalculus as a theory in linear logic: Preliminary results
 3rd Workshop on Extensions to Logic Programming, LNCS 660
, 1993
"... The agent expressions of the πcalculus can be translated into a theory of linear logic in such a way that the reflective and transitive closure of πcalculus (unlabeled) reduction is identified with “entailedby”. Under this translation, parallel composition is mapped to the multiplicative disjunct ..."
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Cited by 102 (17 self)
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The agent expressions of the πcalculus can be translated into a theory of linear logic in such a way that the reflective and transitive closure of πcalculus (unlabeled) reduction is identified with “entailedby”. Under this translation, parallel composition is mapped to the multiplicative disjunct (“par”) and restriction is mapped to universal quantification. Prefixing, nondeterministic choice (+), replication (!), and the match guard are all represented using nonlogical constants, which are specified using a simple form of axiom, called here a process clause. These process clauses resemble Horn clauses except that they may have multiple conclusions; that is, their heads may be the par of atomic formulas. Such multiple conclusion clauses are used to axiomatize communications among agents. Given this translation, it is nature to ask to what extent proof theory can be used to understand the metatheory of the πcalculus. We present some preliminary results along this line for π0, the “propositional ” fragment of the πcalculus, which lacks restriction and value passing (π0 is a subset of CCS). Using ideas from prooftheory, we introduce coagents and show that they can specify some testing equivalences for π0. If negationasfailuretoprove is permitted as a coagent combinator, then testing equivalence based on coagents yields observational equivalence for π0. This latter result follows from observing that coagents directly represent formulas in the HennessyMilner modal logic. 1
Cutelimination for a logic with definitions and induction
 Theoretical Computer Science
, 1997
"... In order to reason about specifications of computations that are given via the proof search or logic programming paradigm one needs to have at least some forms of induction and some principle for reasoning about the ways in which terms are built and the ways in which computations can progress. The l ..."
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Cited by 61 (19 self)
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In order to reason about specifications of computations that are given via the proof search or logic programming paradigm one needs to have at least some forms of induction and some principle for reasoning about the ways in which terms are built and the ways in which computations can progress. The literature contains many approaches to formally adding these reasoning principles with logic specifications. We choose an approach based on the sequent calculus and design an intuitionistic logic F Oλ ∆IN that includes natural number induction and a notion of definition. We have detailed elsewhere that this logic has a number of applications. In this paper we prove the cutelimination theorem for F Oλ ∆IN, adapting a technique due to Tait and MartinLöf. This cutelimination proof is technically interesting and significantly extends previous results of this kind. 1
Proof Search in the Intuitionistic Sequent Calculus
 11th International Conference on Automated Deduction
, 1991
"... The use of Herbrand functions (more popularly known as Skolemization) plays an important role in classical theorem proving and logic programming. We define a notion of Herbrand functions for the full intuitionistic predicate calculus. The definition is based on the view that the prooftheoretic role ..."
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Cited by 42 (1 self)
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The use of Herbrand functions (more popularly known as Skolemization) plays an important role in classical theorem proving and logic programming. We define a notion of Herbrand functions for the full intuitionistic predicate calculus. The definition is based on the view that the prooftheoretic role of Herbrand functions (to replace universal quantifiers), and of unification (to find instances corresponding to existential quantifiers), is to ensure that the eigenvariable conditions on a sequent proof are respected. The propositional impermutabilities that arise in the intuitionistic but not the classical sequent calculus motivate a generalization of the classical notion of Herbrand functions. Proof search using generalized Herbrand functions also provides a framework for generalizing logic programming to subsets of intuitionistic logic that are larger than Horn clauses. The search procedure described here has been implemented and observed to work effectively in practice. The generaliza...
HigherOrder, Linear, Concurrent Constraint Programming
, 1992
"... We present a very simple and powerful framework for indeterminate, asynchronous, higherorder computation based on the formulaasagent and proofascomputation interpretation of (higherorder) linear logic [Gir87]. The framework significantly refines and extends the scope of the concurrent constrai ..."
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Cited by 30 (5 self)
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We present a very simple and powerful framework for indeterminate, asynchronous, higherorder computation based on the formulaasagent and proofascomputation interpretation of (higherorder) linear logic [Gir87]. The framework significantly refines and extends the scope of the concurrent constraint programming paradigm [Sar89] in two fundamental ways: (1) by allowing for the consumption of information by agents it permits a direct modelling of (indeterminate) state change in a logical framework, and (2) by admitting simplytyped terms as dataobjects, it permits the construction, transmission and application of (abstractions of) programs at runtime. Much more dramatically, however, the framework can be seen as presenting higherorder (and if desired, constraintenriched) versions of a variety of other asynchronous concurrent systems, including the asynchronous ("input guarded") fragment of the (firstorder) ßcalculus, Hewitt's actors formalism, (abstract forms of) Gelernter's Lin...
HigherOrder Concurrent Linear Logic Programming
 In Theory and Practice of Parallel Programming
, 1995
"... . We propose a typed, higherorder, concurrent linear logic programming called higherorder ACL, which uniformly integrates a variety of mechanisms for concurrent computation based on asynchronous message passing. Higherorder ACL is based on a proof search paradigm according to the principle, p ..."
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Cited by 30 (8 self)
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. We propose a typed, higherorder, concurrent linear logic programming called higherorder ACL, which uniformly integrates a variety of mechanisms for concurrent computation based on asynchronous message passing. Higherorder ACL is based on a proof search paradigm according to the principle, proofs as computations, formulas as processes in linear logic. In higherorder ACL, processes as well as functions, and other values can be communicated via messages, which provides high modularity of concurrent programs. Higherorder ACL can be viewed as an asynchronous counterpart of Milner's higherorder, polyadic  calculus. Moreover, higherorder ACL is equipped with an elegant MLstyle type system that ensures (1) well typed programs can never cause type mismatch errors, and (2) there is a type inference algorithm which computes a most general typing for an untyped term. We also demonstrate a power of higherorder ACL by showing several examples of "higherorder concurrent prog...
A Proof Procedure for the Logic of Hereditary Harrop Formulas
 JOURNAL OF AUTOMATED REASONING
, 1993
"... A proof procedure is presented for a class of formulas in intuitionistic logic. These formulas are the socalled goal formulas in the theory of hereditary Harrop formulas. Proof search inintuitionistic logic is complicated by the nonexistence of a Herbrandlike theorem for this logic: formulas cann ..."
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Cited by 30 (12 self)
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A proof procedure is presented for a class of formulas in intuitionistic logic. These formulas are the socalled goal formulas in the theory of hereditary Harrop formulas. Proof search inintuitionistic logic is complicated by the nonexistence of a Herbrandlike theorem for this logic: formulas cannot in general be preprocessed into a form such as the clausal form and the construction of a proof is often sensitive to the order in which the connectives and quantifiers are analyzed. An interesting aspect of the formulas we consider here is that this analysis can be carried out in a relatively controlled manner in their context. In particular, the task of finding a proof can be reduced to one of demonstrating that a formula follows from a set of assumptions with the next step in this process being determined by the structure of the conclusion formula. An acceptable implementation of this observation must utilize unification. However, since our formulas may contain universal and existential quantifiers in mixed order, care must be exercised to ensure the correctness of unification. One way of realizing this requirement involves labelling constants and variables and then using these labels to constrain unification. This form of unification is presented and used in a proof procedure for goal formulas in a firstorder version of hereditary Harrop formulas. Modifications to this procedure for the relevant formulas in a higherorder logic are also described. The proof procedure that we present has a practical value in that it provides the basis for an implementation of the logic programming language lambdaProlog.