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.

COMPUTING WITH MEMBRANES (P SYSTEMS): A VARIANT

2000 ◽  
Vol 11 (01) ◽  
pp. 167-181 ◽  
Author(s):  
GHEORGHE PĂUN
Keyword(s):  
Membrane Computing ◽  
P Systems ◽  
Open Problems ◽  
Recursively Enumerable ◽  
Pass Through ◽  
The One ◽  
Priority Relation ◽  
Recursively Enumerable Languages ◽  
Biochemical Features ◽  
Computing Models

Membrane Computing is a recently introduced area of Molecular Computing, where a computation takes place in a membrane structure where multisets of objects evolve according to given rules (they can also pass through membranes). The obtained computing models were called P systems. In basic variants of P systems, the use of objects evolution rules is regulated by a given priority relation; moreover, each membrane has a label and one can send objects to precise membranes, identified by their labels. We propose here a variant where we get rid of both there rather artificial (non-biochemical) features. Instead, we add to membranes and to objects an "electrical charge" and the objects are passed through membranes according to their charge. We prove that such systems are able to characterize the one-letter recursively enumerable languages (equivalently, the recursively enumerable sets of natural numbers), providing that an extra feature is considered: the membranes can be made thicker or thinner (also dissolved) and the communication through a membrane is possible only when its thickness is equal to 1. Several open problems are formulated.

SPIKING NEURAL P SYSTEMS: AN EARLY SURVEY

2007 ◽  
Vol 18 (03) ◽  
pp. 435-455 ◽  
Author(s):  
GHEORGHE PĂUN ◽  
MARIO J. PÉREZ-JIMÉNEZ ◽  
ARTO SALOMAA
Keyword(s):  
Membrane Computing ◽  
Normal Forms ◽  
P Systems ◽  
Research Topics ◽  
Open Problems ◽  
Computing Power ◽  
Spiking Neural P Systems ◽  
A Cell ◽  
Early Survey ◽  
Basic Ideas

Spiking neural P systems were introduced in the end of the year 2005, in the aim of incorporating in membrane computing the idea of working with unique objects ("spikes"), encoding the information in the time elapsed between consecutive spikes sent from a cell/neuron to another cell/neuron. More than one dozen of papers where written in the meantime, clarifying many of the basic properties of these devices, especially related to their computing power. The present paper quickly surveys the basic ideas and the basic results, presenting a complete to-date bibliography, and also giving a completing result related to the normal forms possible for spiking neural P systems: we prove that the indegree of such systems (the maximal number of incoming synapses of neurons) can be bounded by 2 without losing the computational completeness. A series of research topics and open problems are formulated.

Membrane Computing

2017 ◽  
pp. 15-34
Keyword(s):  
Robot Control ◽  
Membrane Computing ◽  
P Systems ◽  
System Model ◽  
P System ◽  
Input Output ◽  
Control Models ◽  
P Colonies ◽  
Theoretical Computing ◽  
Computing Models

The theoretical computing models that are used throughout this book are described in this chapter. These models are based on the initial P system model and include: Numerical P systems, Enzymatic Numerical P systems, P colonies and P swarms. Detailed examples and execution diagrams help the reader allow the reader to understand the functioning principle of each model and also its potential in various applications. The similarity between P systems (and their variants) and robot control models is also addressed. This analysis is presented to the reader in a side-by-side manner using a table where each row represents an analysis topic. Among others we mention: (1) Architectural structure, (2) Modularity and hierarchy, (3) Input-output relationships, (4) Parallelism.

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.

Discrete Morse Theory Based Dynamic P Systems

2018 ◽  
Vol 22 (1) ◽  
pp. 104-112
Author(s):  
Jie Xue ◽  
◽  
Xiyu Liu ◽  
Wenxing Sun ◽  
Shuo Yan
Keyword(s):  
Air Quality ◽  
Quality Evaluation ◽  
Morse Function ◽  
Membrane Computing ◽  
Linear Time ◽  
P Systems ◽  
P System ◽  
Gradient Vector ◽  
Evaluation Problem ◽  
Gradient Vector Field

This paper proposes a class of dynamic P systems with constraint of discrete Morse function (DMDP systems). Membrane structure is extended on complex. Rules control activities of membranes. New classes of rules and mechanism to change types of rules by discrete gradient vector field are provided as well.DMDP system extends P systems both in structures and rules. Solving air quality evaluation problem in linear time verifies the effectiveness ofDMDP systems. Since air quality evaluation problem has significance in many areas. The new P systems provide an alternative for traditional membrane computing.

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.

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.

scholarly journals Simulating multi-level dynamics of antimicrobial resistance in a membrane computing model

2018 ◽  
Author(s):  
Marcelino Campos ◽  
Rafael Capilla ◽  
Fernando Naya ◽  
Ricardo Futami ◽  
Teresa Coque ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Evolutionary Biology ◽  
Membrane Computing ◽  
Patient Flow ◽  
P System ◽  
Biological Organization ◽  
Computing Model ◽  
Computing Paradigm ◽  
Cross Transmission ◽  
Multi Level

AbstractMembrane Computing is a bio-inspired computing paradigm, whose devices are the so-called membrane systems or P systems. The P system designed in this work reproduces complex biological landscapes in the computer world. It uses nested “membrane-surrounded entities” able to divide, propagate and die, be transferred into other membranes, exchange informative material according to flexible rules, mutate and being selected by external agents. This allows the exploration of hierarchical interactive dynamics resulting from the probabilistic interaction of genes (phenotypes), clones, species, hosts, environments, and antibiotic challenges. Our model facilitates analysis of several aspects of the rules that govern the multi-level evolutionary biology of antibiotic resistance. We examine a number of selected landscapes where we predict the effects of different rates of patient flow from hospital to the community and viceversa, cross-transmission rates between patients with bacterial propagules of different sizes, the proportion of patients treated with antibiotics, antibiotics and dosing in opening spaces in the microbiota where resistant phenotypes multiply. We can also evaluate the selective strength of some drugs and the influence of the time-0 resistance composition of the species and bacterial clones in the evolution of resistance phenotypes. In summary, we provide case studies analyzing the hierarchical dynamics of antibiotic resistance using a novel computing model with reciprocity within and between levels of biological organization, a type of approach that may be expanded in the multi-level analysis of complex microbial landscapes.

scholarly journals Automatic Implementation of Fuzzy Reasoning Spiking Neural P Systems for Diagnosing Faults in Complex Power Systems

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Haina Rong ◽  
Kang Yi ◽  
Gexiang Zhang ◽  
Jianping Dong ◽  
Prithwineel Paul ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Power Systems ◽  
Large Scale ◽  
Membrane Computing ◽  
Good Description ◽  
Fuzzy Reasoning ◽  
P Systems ◽  
P System ◽  
Spiking Neural P Systems ◽  
Complex Power

As an important variant of membrane computing models, fuzzy reasoning spiking neural P systems (FRSN P systems) were introduced to build a link between P systems and fault diagnosis applications. An FRSN P system offers an intuitive illustration based on a strictly mathematical expression, a good fault-tolerant capacity, a good description for the relationships between protective devices and faults, and an understandable diagnosis model-building process. However, the implementation of FRSN P systems is still at a manual process, which is a time-consuming and hard labor work, especially impossible to perform on large-scale complex power systems. This manual process seriously limits the use of FRSN P systems to diagnose faults in large-scale complex power systems and has always been a challenging and ongoing task for many years. In this work we develop an automatic implementation method for automatically fulfilling the hard task, named membrane computing fault diagnosis (MCFD) method. This is a very significant attempt in the development of FRSN P systems and even of the membrane computing applications. MCFD is realized by automating input and output, and diagnosis processes consists of network topology analysis, suspicious fault component analysis, construction of FRSN P systems for suspicious fault components, and fuzzy inference. Also, the feasibility of the FRSN P system is verified on the IEEE14, IEEE 39, and IEEE 118 node systems.

LOGIC AND ARITHMETIC OPERATIONS WITH A CONSTANT NUMBER OF STEPS IN MEMBRANE COMPUTING

2011 ◽  
Vol 22 (03) ◽  
pp. 547-564 ◽  
Author(s):  
AKIHIRO FUJIWARA ◽  
TAKESHI TATEISHI
Keyword(s):  
Membrane Computing ◽  
P Systems ◽  
P System ◽  
Binary Number ◽  
Constant Number ◽  
Arithmetic Operations ◽  
Vector Addition ◽  
Multiple Input ◽  
Logic Functions

In the present paper, we propose P systems that work in a constant number of steps. We first propose two P systems for computing multiple input logic functions. An input of the logic functions is a set of n binary numbers of m bits, and an output is a binary number defined by the logic functions. The first and second P systems compute AND and EX-OR functions for the input, and both of the P systems work in a constant number of steps by using O(mn) types of objects, a constant number of membranes, and evolution rules of size O(mn). Next, we propose a P system for the addition of two binary numbers of m bits. The P system works in a constant number of steps by using O(m) types of objects, a constant number of membranes and evolution rules of size O(m2). We also introduce a P system that computes the addition of two vectors of n binary numbers of m bits by using the above P system as a sub-system. The P system for vector addition works in a constant number of steps by using O(mn) types of objects, a constant number of membranes, and evolution rules of size O(m2n).

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