在 P 系统的进化规则中引入变量

IF 0.8 4区计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS Information and Computation Pub Date : 2024-10-16 DOI:10.1016/j.ic.2024.105231

Bogdan Aman

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引用次数: 0

摘要

在膜系统中，进化规则仅使用有限字母表中的对象来构建。本文将研究使用变量的规则。也就是说，我们定义了可变 P 系统，在该系统中，包含变量的规则需要在每个计算步骤开始时用一些预定义的对象集中的值实例化。可变 P 系统的建模能力通过模拟正数（多）集的一些基本算术运算（加法、乘法或它们的组合）来描述。使用变量 P 系统的主要优势在于，无论运算涉及多少个数字，所使用的规则数量都很少：例如，加法运算只需 3 条规则，而乘法运算只需 27 条规则。

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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Introducing variables in the evolution rules of P systems

In membrane systems evolution rules are constructed using only objects from a finite alphabet. In this paper we investigate rules in which variables are used. Namely, we define Variable P systems in which the rules containing variables need to be instantiated at the start of each computational step with values from some predefined sets of sets of objects.

The modelling power of variable P systems is described by simulating some basic arithmetic operations over a (multi)set of positive numbers (addition, multiplication, or a combination of them). The main advantage of using variable P systems consists in the small number of used rules regardless how many numbers are involved in the operation: e.g., the addition requires only 3 rules, while the multiplication only 27 rules.

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来源期刊

Information and Computation 工程技术-计算机：理论方法

CiteScore

2.30

自引率

0.00%

发文量

119

审稿时长

140 days

期刊介绍： Information and Computation welcomes original papers in all areas of theoretical computer science and computational applications of information theory. Survey articles of exceptional quality will also be considered. Particularly welcome are papers contributing new results in active theoretical areas such as -Biological computation and computational biology- Computational complexity- Computer theorem-proving- Concurrency and distributed process theory- Cryptographic theory- Data base theory- Decision problems in logic- Design and analysis of algorithms- Discrete optimization and mathematical programming- Inductive inference and learning theory- Logic & constraint programming- Program verification & model checking- Probabilistic & Quantum computation- Semantics of programming languages- Symbolic computation, lambda calculus, and rewriting systems- Types and typechecking

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