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Logical Loops
, 2002
"... We present a concrete proposal for enhancing Prolog and Prolog based Constraint Logic Programming languages with a new language construct, the logical loop. This is a shorthand notation for the most commonly used recursive control structure: the iteration or tail recursion. ..."
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We present a concrete proposal for enhancing Prolog and Prolog based Constraint Logic Programming languages with a new language construct, the logical loop. This is a shorthand notation for the most commonly used recursive control structure: the iteration or tail recursion.
Partial Deduction System
 In Proc. of the ILPS'97 Workshop on Tools and Environments for (Constraint) Logic Programming, U.P
, 1997
"... We present the fully automatic partial deduction system ecce, which can be used to specialise and optimise logic programs. We describe the underlying principles of ecce and illustrate some of the potential application areas. Interesting possibilites of crossfertilisation with other fields such as r ..."
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Cited by 5 (1 self)
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We present the fully automatic partial deduction system ecce, which can be used to specialise and optimise logic programs. We describe the underlying principles of ecce and illustrate some of the potential application areas. Interesting possibilites of crossfertilisation with other fields such as reachability analysis of concurrent systems and inductive theorem proving are highlighted and substantiated. 1 Introduction Program specialisation, also called partial evaluation or partial deduction, is an automatic technique for program optimisation. The central idea is to specialise a given source program for a particular application domain. Program specialisation encompasses traditional compiler optimisation techniques, such as constant folding and inlining, but uses more aggressive transformations, yielding both the possibility of obtaining (much) greater speedups and more difficulty in controlling the transformation process. In addition to achieving important speedups, program special...
Equational Reasoning for Prolog
"... Abstract. Equational Reasoning is a feature of Functional Programming much envied by Logic Programmers. We argue that logic programmers should not shy away from adopting equational reasoning because of perceived pitfalls, but rather embrace it to indulge in its many benefits. We propose and illustra ..."
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Abstract. Equational Reasoning is a feature of Functional Programming much envied by Logic Programmers. We argue that logic programmers should not shy away from adopting equational reasoning because of perceived pitfalls, but rather embrace it to indulge in its many benefits. We propose and illustrate two approaches: a cumbersome indirection via Haskell and a more insightful approach directly in Prolog. 1
difficult problems. Root Isolation of Zerodimensional Polynomial Systems with Linear Univariate Representation(Abstract) ∗
"... Methods for computing triangular decompositions of polynomial systems can be classified into two groups. First, those computing a series of regular chains C1...,Ce such that for each irreducible component V of the variety of the input system, one of the Ci’s encodes a generic zero of V. An example i ..."
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Methods for computing triangular decompositions of polynomial systems can be classified into two groups. First, those computing a series of regular chains C1...,Ce such that for each irreducible component V of the variety of the input system, one of the Ci’s encodes a generic zero of V. An example is the algorithm of Michael Kalkbrener in his PhD thesis. Secondly are those methods computing a series of characteristic sets C1...,Cf (in the sense of Wu Wen Tsün) such that the variety of the input system is the union of the quasicomponents of the Ci’s. A large variety of methods fall in the second family, in particular the one proposed in 1987 by Wu Wen Tsün in the 1st volume of the MM Research Preprints. Some methods belong to both families, this is the case for those proceeding in an incremental manner, that is, solving one equation after another. These latter methods rely on an operation for computing the intersection of an hypersurface and the quasicomponent of a regular chain. This is an attractive operation since its input can be regarded as wellbehaved geometrical objects. However, known algorithms (the one of Daniel Lazard in 1991 and the one of the second author in 2000) are quite involved and difficult to analyze. We revisit this intersection operation. We show that under “genericity assumptions” a simple algorithm can be stated and analyzed. In this context, it follows a classical projectionextension scheme. However, we shall see that the cost of the extension step can be neglected in comparison to that of the projection, which itself “essentially” reduces to a cost that all such intersection algorithms have to pay. In our experimental results, realized with the RegularChains library in Maple, our new intersection outperforms the one of the second author by several orders of magnitude on sufficiently
Knowledge Induction from Medical Databases with HigherOrder Programming
"... Abstract: Medical data mining is an emerging area of computational intelligence applied to automatically analyze patients ’ records aiming at the discovery of new knowledge potentially useful for medical decision making. Induced knowledge is anticipated not only to increase accurate diagnosis and s ..."
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Abstract: Medical data mining is an emerging area of computational intelligence applied to automatically analyze patients ’ records aiming at the discovery of new knowledge potentially useful for medical decision making. Induced knowledge is anticipated not only to increase accurate diagnosis and successful disease treatment, but also to enhance safety by reducing medicationrelated errors. Modern healthcare organizations regularly generate huge amount of electronic data that could be used as a valuable resource for knowledge induction to support decisionmaking of medical practitioners. Unfortunately, a domainspecific decision support system that provides a suite of customized and flexible tools to efficiently induce knowledge from medical databases with representational heterogeneity does not currently exist. We, thus, design and develop a medical decision support system based on a powerful logic programming framework. The proposed system includes a knowledge induction component to induce knowledge from clinical data repositories and the induced knowledge can also be deployed to pretreatment data from other sources. The implementation of knowledge induction engine has been presented to express the power of higherorder programming of logicbased language. The flexibility of our mining engine is obtained through the pattern matching and metaprogramming facilities provided by logicbased language.