Characterizations of polynomial complexity classes with a better intensionality

J. Marion, Romain Péchoux
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引用次数: 14

Abstract

In this paper, we study characterizations of polynomial complexity classes using first order functional programs and we try to improve their intensionality, that is the number of natural algorithms captured. We use polynomial assignments over the reals. The polynomial assignments used are inspired by the notions of quasiinterpretation and sup-interpretation, and are decidable when considering polynomials of bounded degree ranging over real numbers. Contrarily to quasi-interpretations, the considered assignments are not required to have the subterm property. Consequently, they capture a strictly larger number of natural algorithms (including quotient, gcd, duplicate elimination from a list) than previous characterizations using quasi-interpretations
具有较好强度的多项式复杂度类的表征
在本文中,我们用一阶函数程序研究多项式复杂度类的特征,并试图提高它们的密集性,即捕获的自然算法的数量。我们在实数上使用多项式赋值。所使用的多项式赋值受到拟解释和超解释概念的启发,并且在考虑实数上有界次多项式时是可确定的。与准解释相反,所考虑的赋值不需要具有子项属性。因此,它们捕获的自然算法(包括商、gcd、从列表中消除重复)比以前使用准解释的表征要多得多
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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