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Preservation of stronger equivalence in unfold/fold logic program transformation
Theoretical Computer Science - Special issue on the international conference on fifth generation computer systems. Tokyo, 1988
A fuzzy Prolog database system
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ACM Computing Surveys (CSUR)
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FLOPS '99 Proceedings of the 4th Fuji International Symposium on Functional and Logic Programming
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ALP '97-HOA '97 Proceedings of the 6th International Joint Conference on Algebraic and Logic Programming
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AI Communications - CASC
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IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
On fuzzy unfolding: A multi-adjoint approach
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RuleML'10 Proceedings of the 2010 international conference on Semantic web rules
Fuzzy computed answers collecting proof information
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Declarative traces into fuzzy computed answers
RuleML'2011 Proceedings of the 5th international conference on Rule-based reasoning, programming, and applications
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Multi-adjoint logic programming represents a very recent, extremely flexible attempt for introducing fuzzy logic into logic programming. Inspired by our previous experiences in the field of (declarative) program transformation, in this paper we propose the development of a fold/unfold based transformation system for optimizing such kind of fuzzy logic programs. The starting point is a set of unfolding-based transformations together with a reversible kind of fuzzy folding, that we have designed in the past. The present work substantially improves this last transformation operation by allowing the possibility of using rules belonging to different programs in a transformation sequence when performing a folding step, which is crucial to obtain better, recursive and elegant definitions of fuzzy predicates. In contrast with other declarative paradigms, in the fuzzy setting it is mandatory to pack sets of fuzzy predicates in tuples, if we really want the folding operation to proceed. This implies the need for re-defining the classical ''definition introduction'' transformation rule and introducing a completely new operation, that we call ''aggregation'', which is especially tailored for the new framework. Finally, we illustrate how the effects of appropriately applying our set of transformation rules (definition introduction, aggregation, folding, unfolding and facting) to a given program, are able to improve the execution of goals against transformed programs.