Open AccessProceedings Article
Explanation based program transformation
Maurice Bruynooghe,Luc De Raedt,Danny De Schreye +2 more
- pp 407-412
TLDR
In the context of logic programming, a technique where the folding is driven by an example is presented, aimed at programs suffering from inefficiencies due to the repetition of identical subcomputations.Abstract:
Fold-unfold is a well known program transformation technique. Its major drawback is that folding requires an Eureka step to invent new procedures.
In the context of logic programming, we present a technique where the folding is driven by an example. The transformation is aimed at programs suffering from inefficiencies due to the repetition of identical subcomputations. The execution of an example is analysed to locate repeated subcomputations. Then the structure of the example is used to control a fold-unfold-transformation of the program. The transformation can be automated. The method can be regarded as an extension of explanation based learning.read more
Citations
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Book ChapterDOI
Synthesis of Eureka Predicates for Developing Logic Programs
TL;DR: Two strategies are introduced, the Loop Absorption Strategy and the Generalization Strategy, which in many cases determine the new predicates to be defined during program transformation and some classes of programs in which they are successful are presented.
Journal ArticleDOI
Induction of logic programs by example-guided unfolding
TL;DR: The theoretical analysis shows that the hypothesis space is larger for Covering, and thus more compact hypotheses may be found by this technique than by Divide-and-Conquer, and there is an equivalent hypothesis for each non-recursive hypothesis that can be produced by Covering.
Proceedings Article
Learning by Refining Algorithm Sketches
Pavel Brazdil,Alípio Mário Jorge +1 more
TL;DR: A mechanism that improves significantly the performance of a top-down inductive logic programming (ILP) learning system at the cost of giving to the system extra information that is not difficult to formulate is suggested.
Proceedings Article
How to specialize by theory refinement
TL;DR: This paper presents an interactive incremental learning method with a "smallest generalization steps" strategy such that whenever a learned concept is overgeneral, the method specializes it and efficiently helps a user to identify the insufficiencies of the concept language and in improving it if necessary.
Book ChapterDOI
Eliminating redundancy in explanation-based learning
TL;DR: An EBL algorithm for Horn clause theories, called EGU (Example-Guided Unfolding), that does not introduce search state redundancy is presented, based upon the observation made by several researchers that EBL bears strong resemblance to partial evaluation in the area of logic programming.
References
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Book
Logic for problem solving
Robert A. Kowalski,Steve Smoliar +1 more
TL;DR: This book investigates the application of logic to problem-solving and computer programming and assumes no previous knowledge of these fields, and may be Karl duncker in addition to make difficult fill one of productive.
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A Transformation System for Developing Recursive Programs
Rod M. Burstall,John Darlington +1 more
TL;DR: A system of rules for transforming programs, with the programs in the form of recursion equations, are described, with an initially very simple, lucid, and hopefully correct program transformed into a more efficient one by altering the recursion structure.
Journal ArticleDOI
Explanation-based generalization: a unifying view
TL;DR: This paper proposed a general, domain-independent mechanism, called EBG, that unifies previous approaches to explanation-based generalization, which is illustrated in the context of several example problems, and used to contrast several existing systems for explanation based generalization.
Journal ArticleDOI
Explanation-Based Learning: An Alternative View
Gerald DeJong,Raymond J. Mooney +1 more
TL;DR: Six specific problems with the previously proposed framework for the explanation-based approach to machine learning are outlined and an alternative generalization method to perform explanation- based learning of new concepts is presented.
A specification of an abstract Prolog machine and its application to partial evaluation
TL;DR: This work investigates partial evalution of Prolog programs as a part of a theory of interactive, incremental programming, and outlines how meta-rules that control the execution of the Prolog program can be incorporated into the system in a clean way.