P systems with evolutional symport and membrane creation rules solving QSAT

P systems are computing devices based on sets of rules that dictate how they work. While some of these rules can change the objects within the system, other rules can even change the own structure, like creation rules. They have been used in cell-like membrane systems with active membranes to efficiently solve NP-complete problems. In this work, we improve a previous result where a uniform family of P systems with evolutional communication rules whose left-hand side (respectively, right-hand side) have most 2 objects (resp., 2 objects) and membrane creation solved SAT efficiently, and we obtain an efficient solution to solve QBF-SAT or QSAT (a PSPACE-complete problem) having at most 1 object (respectively, 1 object) in their left-hand side (resp., right-hand side) and not making use of the environmentMinisterio de Ciencia e Innovación TIN2017-89842-

On the efficiency of cell-like and tissue-like recognizing membrane systems

Cell-like recognizing membrane systems are computational devices in the framework of membrane computing inspired from the structure of living cells, where biological membranes are arranged hierarchically. In this paper tissue-like recognizing membrane systems are presented. The idea is to consider that membranes are placed in the nodes of a graph, mimicking the cell intercommunication in tissues. In this context, polynomial complexity classes associated with recognizing membrane systems can be defined. We recall the definition for cell-like systems, and we introduce the corresponding complexity classes for the tissue-like case. Moreover, in this paper two efficient solutions to the satisfiability problem are analyzed and compared from a complexity point of view.Ministerio de Educación y Ciencia TIN2005-09345-C04-01Junta de Andalucía TIC-58

Space complexity equivalence of P systems with active membranes and Turing machines

We prove that arbitrary single-tape Turing machines can be simulated by uniform families of P systems with active membranes with a cubic slowdown and quadratic space overhead. This result is the culmination of a series of previous partial results, finally establishing the equivalence (up to a polynomial) of many space complexity classes defined in terms of P systems and Turing machines. The equivalence we obtained also allows a number of classic computational complexity theorems, such as Savitch's theorem and the space hierarchy theorem, to be directly translated into statements about membrane systems

P Systems with Active Membranes and Two Polarizations

P systems with active membranes using only two electrical charges and only rules of types (a) and (c) assigned to at most two membranes are shown to be computationally complete { thus improving the previous result of this type from the point of view of the number of polarizations as well as with respect to the number of membranes. Allowing a special variant of rules of type (c) to delete symbols by sending them out, even only one membrane is needed. Moreover, we present an algorithm for deterministically deciding SAT in linear time using only two polarizations and global rules of types (a) ; (c), and (e)

P Systems with Active Membranes and Separation Rules

The P systems are a class of distributed parallel computing devices of a biochemical type. In this paper, a new de¯nition of separation rules in P systems with active membranes is given. Under the new de¯nition, the e±ciency and universality of P systems with active membranes and separation rules instead of division are investigated

Evaluating space measures in P systems

P systems with active membranes are a variant of P systems where membranes can be created by division of existing membranes, thus creating an exponential amount of resources in a polynomial number of steps. Time and space complexity classes for active membrane systems have been introduced, to characterize classes of problems that can be solved by different membrane systems making use of different resources. In particular, space complexity classes introduced initially considered a hypothetical real implementation by means of biochemical materials, assuming that every single object or membrane requires some constant physical space (corresponding to unary notation). A different approach considered implementation of P systems in silico, allowing to store the multiplicity of each object in each membrane using binary numbers. In both cases, the elements contributing to the definition of the space required by a system (namely, the total number of membranes, the total number of objects, the types of different membranes, and the types of different objects) was considered as a whole. In this paper, we consider a different definition for space complexity classes in the framework of P systems, where each of the previous elements is considered independently. We review the principal results related to the solution of different computationally hard problems presented in the literature, highlighting the requirement of every single resource in each solution. A discussion concerning possible alternative solutions requiring different resources is presented

Non-confluence in divisionless P systems with active membranes

AbstractWe describe a solution to the SAT problem via non-confluent P systems with active membranes, without using membrane division rules. Furthermore, we provide an algorithm for simulating such devices on a nondeterministic Turing machine with a polynomial slowdown. Together, these results prove that the complexity class of problems solvable non-confluently and in polynomial time by this kind of P system is exactly the class NP

A Novel Clustering Algorithm Inspired by Membrane Computing

P systems are a class of distributed parallel computing models; this paper presents a novel clustering algorithm, which is inspired from mechanism of a tissue-like P system with a loop structure of cells, called membrane clustering algorithm. The objects of the cells express the candidate centers of clusters and are evolved by the evolution rules. Based on the loop membrane structure, the communication rules realize a local neighborhood topology, which helps the coevolution of the objects and improves the diversity of objects in the system. The tissue-like P system can effectively search for the optimal partitioning with the help of its parallel computing advantage. The proposed clustering algorithm is evaluated on four artificial data sets and six real-life data sets. Experimental results show that the proposed clustering algorithm is superior or competitive to k-means algorithm and several evolutionary clustering algorithms recently reported in the literature

Frontiers of Membrane Computing: Open Problems and Research Topics

This is a list of open problems and research topics collected after the Twelfth Conference on Membrane Computing, CMC 2012 (Fontainebleau, France (23 - 26 August 2011), meant initially to be a working material for Tenth Brainstorming Week on Membrane Computing, Sevilla, Spain (January 30 - February 3, 2012). The result was circulated in several versions before the brainstorming and then modified according to the discussions held in Sevilla and according to the progresses made during the meeting. In the present form, the list gives an image about key research directions currently active in membrane computing