A Gentle Introduction to Membrane Systems and Their Computational Properties

A. Leporati, L. Manzoni, G. Mauri, A. Porreca, C. Zandron
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Abstract

The theory of computation investigates the nature and properties of algorithmic procedures. This field emerged in the 20s and 30s of the 20th century from the work on the philosophy and the foundations of mathematics. Of great importance and inspiration was David Hilbert’s ambitious program to “dispose of the foundational questions in mathematics once and for all” [34], that led to fundamental results in logic such as Gdel’s incompleteness theorems [6], and ultimately to the birth of recursion theory (nowadays mostly referred to as computability theory) and computer science itself. The formal notion of computability that is almost universally adopted today is due to Alan Turing, who introduced in his ground-breaking paper On computable numbers, with an application to the Entscheidungsproblem [32] a simple, elegant and convincing mathematical formalisation of the notion of computation, as it is carried out by a human executor equipped with enough scratch paper. Turing’s work showed that, as long as we accept his notion of computation, there exist well-formed mathematical questions whose answer cannot be computed. In particular, one of the main challenges of Hilbert’s program, the Entscheidungsproblem (finding a decision procedure for the validity of statements in first-order logic) was proved to be unsolvable. This formalisation, that rapidly became known as the Turing machine, is still the reference model for computing devices in theoretical computer science, as it also enjoys the property of being a good model of actual electronic computers; this is also due to the fact that it was itself an inspiration for the design of automatic computing machinery [5]. With the development of computers as a technology, being able to solve a particular problem proved not to be satisfying: fast, efficient solutions are needed. This led to the development of computational complexity theory, pioneered [9] by Hartmanis and Stearns in the paper On the computational complexity of algorithms [12], that also gives the name to the field. Identifying
膜系统及其计算特性简介
计算理论研究算法程序的性质和属性。这一领域兴起于 20 世纪二三十年代的数学哲学和数学基础研究。戴维-希尔伯特(David Hilbert)雄心勃勃地计划 "一劳永逸地解决数学中的基础问题"[34],这一计划带来了逻辑学中的基本结果,如格德尔不完备性定理[6],并最终催生了递归理论(如今大多称为可计算性理论)和计算机科学本身。阿兰-图灵在他的开创性论文《论可计算数》中提出了一个简单、优雅和令人信服的数学形式化计算概念,并将其应用于恩赐问题[32]。图灵的工作表明,只要我们接受他的计算概念,就存在无法计算其答案的形式化数学问题。尤其是希尔伯特计划的主要挑战之一,"Entscheidungsproblem"(为一阶逻辑中语句的有效性找到一个决策程序)被证明是无法解决的。图灵机的形式化迅速被人们所熟知,至今仍是理论计算机科学中计算设备的参考模型,因为它也是实际电子计算机的良好模型;这也是因为它本身就是自动计算机械设计的灵感来源[5]。随着计算机技术的发展,能够解决某一特定问题已被证明不能令人满意:我们需要快速、高效的解决方案。哈特曼尼斯和斯特恩斯在《论算法的计算复杂性》[12] 一文中率先提出了计算复杂性理论[9],这也是该领域名称的由来。识别
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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