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Electronic Notes in Theoretical Computer Science
Article . 2005 . Peer-reviewed
License: CC BY NC ND
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Unfolding-based Improvements on Fuzzy Logic Programs

Authors: Jaime Penabad; Pascual Julián; Ginés Moreno;

Unfolding-based Improvements on Fuzzy Logic Programs

Abstract

AbstractUnfolding is a semantics-preserving program transformation technique that consists in the expansion of subexpressions of a program using their own definitions. In this paper we define two unfolding-based transformation rules that extend the classical definition of the unfolding rule (for pure logic programs) to a fuzzy logic setting. We use a fuzzy variant of Prolog where each program clause can be interpreted under a different (fuzzy) logic. We adapt the concept of a computation rule, a mapping that selects the subexpression of a goal involved in a computation step, and we prove the independence of the computation rule. We also define a basic transformation system and we demonstrate its strong correctness, that is, original and transformed programs compute the same fuzzy computed answers. Finally, we prove that our transformation rules always produce an improvement in the efficiency of the residual program, by reducing the length of successful Fuzzy SLD-derivations.

Keywords

Program Transformation, Fuzzy Logic Programming, Theoretical Computer Science, Computer Science(all)

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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