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On fuzzy unfolding: A multi-adjoint approach

机译:关于模糊展开:多伴随方法

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In the context of (fuzzy) logic programs, 'unfolding' means to transform a program rule by replacing an atom call of the body (of that rule) by its definition. Unfolding is a semantics-preserving program transformation technique that is able to improve programs, generating more efficient code, since it anticipates computation steps. Unfolding is the basis for developing sophisticated and powerful programming tools, such as fold/unfold transformation systems or partial evaluators. In this paper we address the problem of extending the classical definition of the unfolding rule (for pure logic programs) to the setting of multi-adjoint logic programming, where a fuzzy computed answer is a pair (truth degree; substitution) computed by a fuzzy generalization of the modus ponens inference rule. Our main contributions can be summarized as follows: 1. We proved the independence of the computation rule for multi-adjoint admissible computations. 2. Moreover, we defined a fuzzy unfolding rule and we demonstrated its strong correctness properties, that is, original and unfolded programs compute the same fuzzy computed answers for a given goal. 3. We also proved that unfolding transformations increase the efficiency of the residual programs, by reducing the length of fuzzy admissible derivations when solving goals.
机译:在(模糊)逻辑程序的上下文中,“展开”是指通过用其定义替换(该规则的)主体的原子调用来变换程序规则。展开是一种保留语义的程序转换技术,它可以改进程序,生成更有效的代码,因为它可以预测计算步骤。展开是开发复杂而强大的编程工具(例如,折叠/展开转换系统或局部评估器)的基础。在本文中,我们解决了将展开规则的经典定义(对于纯逻辑程序)扩展到多伴随逻辑编程设置的问题,其中模糊计算的答案是由模糊计算的对(真实度;替换)方式推理规则的一般化。我们的主要贡献可归纳如下:1.我们证明了多伴随可容许计算的计算规则的独立性。 2.此外,我们定义了模糊展开规则,并展示了其强大的正确性,即原始程序和展开程序针对给定目标计算相同的模糊计算答案。 3.我们还证明了展开变换可以通过减少求解目标时模糊可容许导数的长度来提高残差程序的效率。

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