Membrane Computing

2011 ◽  
pp. 1-31 ◽  
Author(s):  
Gheorghe Paun
Keyword(s):  
Membrane Computing ◽  
Living Cells ◽  
Point Of View ◽  
Natural Computing ◽  
Historical Evolution ◽  
Biological Phenomena ◽  
Complete Problems ◽  
Hard Problems ◽  
Np Complete ◽  
And Mathematics

Membrane computing is a branch of natural computing whose initial goal was to abstract computing models from the structure and the functioning of living cells. The research was initiated about five years ago (at the end of 1998), and since that time the area has been developed significantly from a mathematical point of view. The basic types of results of this research concern the computability power (in comparison with the standard Turing machines and their restrictions) and the efficiency (the possibility to solve computationally hard problems, typically NP-complete problems, in a feasible time and typically polynomial). However, membrane computing has recently become attractive also as a framework for devising models of biological phenomena, with the tendency to provide tools for modelling the cell itself, not only the local processes. This chapter surveys the basic elements of membrane computing, somewhat in its “historical” evolution: from biology to computer science and mathematics and back to biology. The presentation is informal, without any technical detail, and an invitation to membrane computing intended to acquaint the nonmathematician reader with the main directions of research of the domain, the type of central results, and the possible lines of future development, including the possible interest of the biologist looking for discrete algorithmic tools for modelling cell phenomena.

scholarly journals Enhanced Membrane Computing Algorithm for SAT Problems Based on the Splitting Rule

Symmetry ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1412
Author(s):  
Hao ◽  
Liu
Keyword(s):  
Membrane Computing ◽  
Space Complexity ◽  
Natural Computing ◽  
Sat Problem ◽  
Computing Algorithm ◽  
Complete Problems ◽  
Np Complete ◽  
Splitting Rule ◽  
Np Problems ◽  
Time And Space Complexity

Boolean propositional satisfiability (SAT) problem is one of the most widely studied NP-complete problems and plays an outstanding role in many domains. Membrane computing is a branch of natural computing which has been proven to solve NP problems in polynomial time with a parallel compute mode. This paper proposes a new algorithm for SAT problem which combines the traditional membrane computing algorithm of SAT problem with a classic simplification rule, the splitting rule, which can divide a clause set into two axisymmetric subsets, deal with them respectively and simultaneously, and obtain the solution of the original clause set with the symmetry of their solutions. The new algorithm is shown to be able to reduce the space complexity by distributing clauses with the splitting rule repeatedly, and also reduce both time and space complexity by executing one-literal rule and pure-literal rule as many times as possible.

NP vs QMA_\log(2)

2010 ◽  
Vol 10 (1&2) ◽  
pp. 141-151
Author(s):  
S. Beigi
Keyword(s):  
Quantum Algorithms ◽  
Np Hard ◽  
Complete Problems ◽  
Hard Problems ◽  
Np Complete ◽  
Np Hard Problems

Although it is believed unlikely that $\NP$-hard problems admit efficient quantum algorithms, it has been shown that a quantum verifier can solve NP-complete problems given a "short" quantum proof; more precisely, NP\subseteq QMA_{\log}(2) where QMA_{\log}(2) denotes the class of quantum Merlin-Arthur games in which there are two unentangled provers who send two logarithmic size quantum witnesses to the verifier. The inclusion NP\subseteq QMA_{\log}(2) has been proved by Blier and Tapp by stating a quantum Merlin-Arthur protocol for 3-coloring with perfect completeness and gap 1/24n^6. Moreover, Aaronson et al. have shown the above inclusion with a constant gap by considering $\widetilde{O}(\sqrt{n})$ witnesses of logarithmic size. However, we still do not know if QMA_{\log}(2) with a constant gap contains NP. In this paper, we show that 3-SAT admits a QMA_{\log}(2) protocol with the gap 1/n^{3+\epsilon}} for every constant \epsilon>0.

scholarly journals Solving Vertex Cover Problem by Means of Tissue P Systems with Cell Separation

2010 ◽  
Vol 5 (4) ◽  
pp. 540 ◽  
Author(s):  
Chun Lu ◽  
Xingyi Zhang
Keyword(s):  
Cell Separation ◽  
Membrane Computing ◽  
Linear Time ◽  
Vertex Cover ◽  
P Systems ◽  
Computing Model ◽  
Vertex Cover Problem ◽  
Complete Problems ◽  
Np Complete ◽  
Cover Problem

Tissue P systems is a computing model in the framework of membrane computing inspired from intercellular communication and cooperation between neurons. Many different variants of this model have been proposed. One of the most important models is known as tissue P systems with cell separation. This model has the ability of generating an exponential amount of workspace in linear time, thus it allows us to design cellular solutions to NP-complete problems in polynomial time. In this paper, we present a solution to the Vertex Cover problem via a family of such devices. This is the first solution to this problem in the framework of tissue P systems with cell separation.

The P versus NP Problem from the Membrane Computing View

2014 ◽  
Vol 22 (1) ◽  
pp. 18-33 ◽  
Author(s):  
Mario J. Pérez-Jiménez
Keyword(s):  
Membrane Computing ◽  
Efficient Solutions ◽  
Significant Advance ◽  
Natural Computing ◽  
Complexity Classes ◽  
Membrane Systems ◽  
Hard Problems ◽  
Young Branch ◽  
Np Problem ◽  
Computing Models

In the last few decades several computing models using powerful tools from Nature have been developed (because of this, they are known as bio-inspired models). Commonly, the space-time trade-off method is used to develop efficient solutions to computationally hard problems. According to this, implementation of such models (in biological, electronic, or any other substrate) would provide a significant advance in the practical resolution of hard problems. Membrane Computing is a young branch of Natural Computing initiated by Gh. Păun at the end of 1998. It is inspired by the structure and functioning of living cells, as well as from the organization of cells in tissues, organs, and other higher order structures. The devices of this paradigm, called P systems or membrane systems, constitute models for distributed, parallel and non-deterministic computing. In this paper, a computational complexity theory within the framework of Membrane Computing is introduced. Polynomial complexity classes associated with different models of cell-like and tissue-like membrane systems are defined and the most relevant results obtained so far are presented. Different borderlines between efficiency and non-efficiency are shown, and many attractive characterizations of the P ≠ NP conjecture within the framework of this bio-inspired and non-conventional computing model are studied.

scholarly journals Time-free Solution to Independent Set Problem using P Systems with Active Membranes

2021 ◽  
Vol 182 (3) ◽  
pp. 243-255
Author(s):  
Yu Jin ◽  
Bosheng Song ◽  
Yanyan Li ◽  
Ying Zhu
Keyword(s):  
Membrane Computing ◽  
Independent Set ◽  
P Systems ◽  
Natural Computing ◽  
Free Solution ◽  
Independent Set Problem ◽  
Global Clock ◽  
Active Membranes ◽  
Biological Reality ◽  
Hard Problems

Membrane computing is a branch of natural computing aiming to abstract computing models from the structure and functioning of living cells. The computation models obtained in the field of membrane computing are usually called P systems. P systems have been used to solve computationally hard problems efficiently on the assumption that the execution of each rule is completed in exactly one time-unit (a global clock is assumed for timing and synchronizing the execution of rules). However, in biological reality, different biological processes take different times to be completed, which can also be influenced by many environmental factors. In this work, with this biological reality, we give a time-free solution to independent set problem using P systems with active membranes, which solve the problem independent of the execution time of the involved rules.

scholarly journals On the Concepts of Parallelism in Biomolecular Computing

Triangle ◽  
2018 ◽  
pp. 109
Author(s):  
Remco Loos ◽  
Bendek Nagy
Keyword(s):  
Problem Solving ◽  
Membrane Computing ◽  
Theoretical Models ◽  
Natural Computing ◽  
Biomolecular Computing ◽  
Hard Problems

In this paper we consider DNA and membrane computing, both as theoretical models and as problem solving devices. The basic motivation behind these models of natural computing is using parallelism to make hard problems tractable. In this paper we analyze the concept of parallelism. We will show that parallelism has very different meanings in these models.We introduce the terms ’or-parallelism’ and ’and-parallelism’ for these two basic types of parallelism.

scholarly journals A Survey of Nature-Inspired Computing

2021 ◽  
Vol 54 (1) ◽  
pp. 1-31
Author(s):  
Bosheng Song ◽  
Kenli Li ◽  
David Orellana-Martín ◽  
Mario J. Pérez-Jiménez ◽  
Ignacio PéRez-Hurtado
Keyword(s):  
Membrane Computing ◽  
P Systems ◽  
Natural Computing ◽  
P System ◽  
Open Problems ◽  
Membrane Function ◽  
Natural Systems ◽  
Computing Paradigm ◽  
Complete Problems ◽  
Nature Inspired Computing

Nature-inspired computing is a type of human-designed computing motivated by nature, which is based on the employ of paradigms, mechanisms, and principles underlying natural systems. In this article, a versatile and vigorous bio-inspired branch of natural computing, named membrane computing is discussed. This computing paradigm is aroused by the internal membrane function and the structure of biological cells. We first introduce some basic concepts and formalisms of membrane computing, and then some basic types or variants of P systems (also named membrane systems ) are presented. The state-of-the-art computability theory and a pioneering computational complexity theory are presented with P system frameworks and numerous solutions to hard computational problems (especially NP -complete problems) via P systems with membrane division are reported. Finally, a number of applications and open problems of P systems are briefly described.

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