Dictionary Search and Update by P Systems with String-Objects and Active Membranes

Membrane computing is a formal framework of distributed parallel com- puting. In this paper we implement the work with the prefix tree by P systems with strings and active membranes. We present the algorithms of searching in a dictionary and updating it implemented as membrane systems. The systems are constructed as reusable modules, so they are suitable for using as sub-algorithms for solving more complicated problems.

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Impact of Membrane Computing and P Systems in ISI WoS. Celebrating the 65th Birthday of Gheorghe Păun

International Journal of Computers Communications & Control ◽

10.15837/ijccc.2015.5.2024 ◽

2015 ◽

Vol 10 (5) ◽

Author(s):

Ioan DZITAC

Keyword(s):

Computer Science ◽

Membrane Computing ◽

Research Area ◽

P Systems ◽

65Th Birthday ◽

Membrane Systems ◽

Journal Paper ◽

Technical Report ◽

The Impact

Membrane Computing is a branch of Computer Science initiated by Gheorghe Păun in 1998, in a technical report of Turku Centre for Computer Science published as a journal paper ("Computing with Membranes" in Journal of Computer and System Sciences) in 2000. Membrane systems, as Gheorghe Păun called the models he has introduced, are known nowadays as "P Systems" (with the letter P coming from the initial of the name of this research area "father"). This note is an overview of the impact in ISI WoS of Gheorghe Păun’s works, focused on Membrane Computing and P Systems field, on the occasion of his 65th birthday anniversary.

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COMPUTATION OF RAMSEY NUMBERS BY P SYSTEMS WITH ACTIVE MEMBRANES

International Journal of Foundations of Computer Science ◽

10.1142/s0129054111007800 ◽

2011 ◽

Vol 22 (01) ◽

pp. 29-38 ◽

Cited By ~ 14

Author(s):

LINQIANG PAN ◽

DANIEL DÍAZ-PERNIL ◽

MARIO J. PÉREZ-JIMÉNEZ

Keyword(s):

Membrane Computing ◽

P Systems ◽

Ramsey Number ◽

Ramsey Numbers ◽

Combinatorial Object ◽

Active Membranes ◽

Number Problem ◽

Decision Version

Ramsey numbers deal with conditions when a combinatorial object necessarily contains some smaller given objects. It is well known that it is very difficult to obtain the values of Ramsey numbers. In this work, a theoretical chemical/biological solution is presented in terms of membrane computing for the decision version of Ramsey number problem, that is, to decide whether an integer n is the value of Ramsey number R(k, l), where k and l are integers.

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Implementation on CUDA of the Smoothing Problem with Tissue-Like P Systems

International Journal of Natural Computing Research ◽

10.4018/jncr.2011070103 ◽

2011 ◽

Vol 2 (3) ◽

pp. 25-34 ◽

Cited By ~ 10

Author(s):

Francisco Peña-Cantillana ◽

Daniel Díaz-Pernil ◽

Hepzibah A. Christinal ◽

Miguel A. Gutiérrez-Naranjo

Keyword(s):

Membrane Computing ◽

Parallel Implementation ◽

P Systems ◽

Compute Unified Device Architecture ◽

Digital Imagery ◽

Graphics Processors ◽

Novel Device ◽

Device Architecture ◽

Formal Framework

Smoothing is often used in Digital Imagery for improving the quality of an image by reducing its level of noise. This paper presents a parallel implementation of an algorithm for smoothing 2D images in the framework of Membrane Computing. The chosen formal framework has been tissue-like P systems. The algorithm has been implemented by using a novel device architecture called CUDA (Compute Unified Device Architecture) which allows the parallel NVIDIA Graphics Processors Units (GPUs) to solve many complex computational problems. Some examples are presented and compared; research lines for the future are also discussed.

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Simple Neural-Like P Systems for Maximal Independent Set Selection

Neural Computation ◽

10.1162/neco_a_00443 ◽

2013 ◽

Vol 25 (6) ◽

pp. 1642-1659 ◽

Cited By ~ 7

Author(s):

Lei Xu ◽

Peter Jeavons

Keyword(s):

Distributed Computing ◽

Membrane Computing ◽

Independent Set ◽

Living Cells ◽

P Systems ◽

Maximal Independent Set ◽

Membrane Systems ◽

New Class ◽

The Individual ◽

Computing Models

Membrane systems (P systems) are distributed computing models inspired by living cells where a collection of processors jointly achieves a computing task. The problem of maximal independent set (MIS) selection in a graph is to choose a set of nonadjacent nodes to which no further nodes can be added. In this letter, we design a class of simple neural-like P systems to solve the MIS selection problem efficiently in a distributed way. This new class of systems possesses two features that are attractive for both distributed computing and membrane computing: first, the individual processors do not need any information about the overall size of the graph; second, they communicate using only one-bit messages.

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P Systems with Evolutional Communication and Division Rules

Axioms ◽

10.3390/axioms10040327 ◽

2021 ◽

Vol 10 (4) ◽

pp. 327

Author(s):

David Orellana-Martín ◽

Luis Valencia-Cabrera ◽

Mario J. Pérez-Jiménez

Keyword(s):

Computational Complexity ◽

Complexity Theory ◽

Membrane Computing ◽

P Systems ◽

Membrane Systems ◽

Sat Problem ◽

Complete Problem ◽

Intractable Problems ◽

Np Complete ◽

The One

A widely studied field in the framework of membrane computing is computational complexity theory. While some types of P systems are only capable of efficiently solving problems from the class P, adding one or more syntactic or semantic ingredients to these membrane systems can give them the ability to efficiently solve presumably intractable problems. These ingredients are called to form a frontier of efficiency, in the sense that passing from the first type of P systems to the second type leads to passing from non-efficiency to the presumed efficiency. In this work, a solution to the SAT problem, a well-known NP-complete problem, is obtained by means of a family of recognizer P systems with evolutional symport/antiport rules of length at most (2,1) and division rules where the environment plays a passive role; that is, P systems from CDEC^(2,1). This result is comparable to the one obtained in the tissue-like counterpart, and gives a glance of a parallelism and the non-evolutionary membrane systems with symport/antiport rules.

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

Fundamenta Informaticae ◽

10.3233/fi-2021-2072 ◽

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.

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When catalytic P systems with one catalyst can be computationally complete

Journal of Membrane Computing ◽

10.1007/s41965-021-00079-x ◽

2021 ◽

Author(s):

Artiom Alhazov ◽

Rudolf Freund ◽

Sergiu Ivanov

Keyword(s):

Computational Complexity ◽

P Systems ◽

Membrane Systems ◽

Computational Completeness ◽

Recursively Enumerable ◽

Recursively Enumerable Sets

AbstractCatalytic P systems are among the first variants of membrane systems ever considered in this area. This variant of systems also features some prominent computational complexity questions, and in particular the problem of using only one catalyst in the whole system: is one catalyst enough to allow for generating all recursively enumerable sets of multisets? Several additional ingredients have been shown to be sufficient for obtaining computational completeness even with only one catalyst. In this paper, we show that one catalyst is sufficient for obtaining computational completeness if either catalytic rules have weak priority over non-catalytic rules or else instead of the standard maximally parallel derivation mode, we use the derivation mode maxobjects, i.e., we only take those multisets of rules which affect the maximal number of objects in the underlying configuration.

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