Higher-order lazy narrowing is a general method for solving E-unification problems in theories presented as sets of rewrite rules. In this paper we study the possibility to improve the search for normalized solutions of a higher-order lazy narrowing calculus LN. We introduce a new calculus, LNff, obtained by extending LN and define an equation selection strategy Sn such that LNff with strategy Sn is complete. The main advantages of using LNff with strategy Sn instead of LN include the possibility to restrict the application of outermost narrowing at variable position, and the computation of more specific solutions because of additional inference rules for solving ex-ex equations. We also show that for orthogonal pattern rewrite systems we can adopt an eager variable elimination strategy that makes the calculus LNff with strategy Sn even more deterministic.

In this paper we describe the architecture and implementation of a system that aims at extending in a consistent way a functional logic programming language with solving techniques of various constraint solving systems. The system is called CFLP (Constrained Functional Logic Programming language), and consists of a lazy functional logic interpreter extended in two directions: the possibility to specify constraints, and the possibility to specify AND- and OR-parallelism. For solving the constraints, a distributed constraint solving system was implemented.

Training people on science and engineering as well as providing scientific and engineering solutions are key abilities in the technology-driven development of our society. Recent innovations in global networking and, in particular, the creation of the World-Wide Web and the widespread use of mobile-code technology, put a new generation of software systems within our reach, which promise a new quality of knowledge dissemination and absorption. Herein we document our design of a combined software technology basis and content creation methodology (tentatively named KnowledgeWeb) that addresses both modern education methods and distributed solution providers in the area of science and engineering. In accordance with the twofold goal, we propose two main technologies: active books and knowledge on demand. The first component, active books, blurs the distinction between traditional textbooks and educational software by integrating content-dependent software into the static text...

Higher-order lazy narrowing (HOLN for short) is a computational model for higher-order functional logic programming. It can be viewed as an extension of first-order lazy narrowing with inference rules to solve equations involving lambda-abstractions and higher-order variables. A common feature of the HOLN calculi proposed so far is the high nondeterminism between the inference rules designed to solve equations which involve higher-order variables. In this paper we present various refinements of HOLN towards more deterministic versions. The refinements are defined for classes of higher-order functional logic programs which are useful for programming purposes. Our work draws on two sources: the calculus LN for pattern rewrite systems [Pre98] and the first-order lazy narrowing calculus LNC and its deterministic refinements [MO98].

Abstract — This paper presents a theoretical framework for the integration of the cooperative constraint solving of several algebraic domains into higher-order functional and logic programming on λ-abstractions, using the instance CFLP(C) of the generic Constraint Functional Logic Programming (CFLP) scheme [7] over a so-called higher-order coordination domain C. We provide this framework as a powerful computational model for the higher-order cooperation of algebraic constraint domains over real numbers R and integers FD, which has been useful in practical applications involving the hybrid combination of its components, so that more declarative and efficient solutions can be promoted. Our proposal of computational model has been proved sound and complete with respect to the declarative semantics provided by the CFLP scheme, and enriched with new mechanisms for modeling the intended cooperation among the algebraic domains and a higher-order constraint domain ⋋ equipped with a sound and complete constraint solver for solving higher-order equations.