Computing Backwards with P Systems

Searching all the configurations C′ such that produce a given configuration C, or, in other words, computing backwards in Membrane Computing is an extremely hard task. The current approximations are based in heavy hand-made calculus by considering the specific features of the given configuration. In this paper we present a general method for characterizing all the configurations C′ such that produce a given configuration C in transition P systems without cooperation and without dissolution.Ministerio de Educación y Ciencia TIN2006-13425Junta de Andalucía P08-TIC-0420

Spiking Neural P Systems with Addition/Subtraction Computing on Synapses

Spiking neural P systems (SN P systems, for short) are a class of distributed and parallel computing models inspired from biological spiking neurons. In this paper, we introduce a variant called SN P systems with addition/subtraction computing on synapses (CSSN P systems). CSSN P systems are inspired and motivated by the shunting inhibition of biological synapses, while incorporating ideas from dynamic graphs and networks. We consider addition and subtraction operations on synapses, and prove that CSSN P systems are computationally universal as number generators, under a normal form (i.e. a simplifying set of restrictions)

Computing with Spiking Neural P Systems: Traces and Small Universal Systems

Recently, the idea of spiking neurons and thus of computing by spiking was incorporated into membrane computing, and so-called spiking neural P systems (abbreviated SN P systems) were introduced. Very shortly, in these systems neurons linked by synapses communicate by exchanging identical signals (spikes), with the information encoded in the distance between consecutive spikes. Several ways of using such devices for computing were considered in a series of papers, with universality results obtained in the case of computing numbers, both in the generating and the accepting mode; generating, accepting, or processing strings or infinite sequences was also proved to be of interest. In the present paper, after a short survey of central notions and results related to spiking neural P systems (including the case when SN P systems are used as string generators), we contribute to this area with two (types of) results: (i) we produce small universal spiking neural P systems (84 neurons are sufficient in the basic definition, but this number is decreased to 49 neurons if a slight generalization of spiking rules is adopted), and (ii) we investigate the possibility of generating a language by following the trace of a designated spike in its way through the neurons.Ministerio de Educación y Ciencia TIN2005-09345-C03-0

Simulation of Rapidly-Exploring Random Trees in Membrane Computing with P-Lingua and Automatic Programming

Methods based on Rapidly-exploring Random Trees (RRTs) have been widely used in robotics to solve motion planning problems. On the other hand, in the membrane computing framework, models based on Enzymatic Numerical P systems (ENPS) have been applied to robot controllers, but today there is a lack of planning algorithms based on membrane computing for robotics. With this motivation, we provide a variant of ENPS called Random Enzymatic Numerical P systems with Proteins and Shared Memory (RENPSM) addressed to implement RRT algorithms and we illustrate it by simulating the bidirectional RRT algorithm. This paper is an extension of [21]a. The software presented in [21] was an ad-hoc simulator, i.e, a tool for simulating computations of one and only one model that has been hard-coded. The main contribution of this paper with respect to [21] is the introduction of a novel solution for membrane computing simulators based on automatic programming. First, we have extended the P-Lingua syntax –a language to define membrane computing models– to write RENPSM models. Second, we have implemented a new parser based on Flex and Bison to read RENPSM models and produce source code in C language for multicore processors with OpenMP. Finally, additional experiments are presented.Ministerio de Economía, Industria y Competitividad TIN2017-89842-

Computing by Carving with P Systems. A First Approach

In this work, we propose a P system which carries out computing by carving. Computing by carving was proposed by Gh. P˘aun as a technique to generate formal languages which can even be non recursively enumerable. Hence, it can be considered a hypercomputational technique. Here, we propose a first scheme based on P systems in order to perform computing by carving any formal language. So, the paper shows indirectly that these systems, under certain assumptions, can be considered a model for hypercomputation

Simulating Spiking Neural P systems without delays using GPUs

We present in this paper our work regarding simulating a type of P system known as a spiking neural P system (SNP system) using graphics processing units (GPUs). GPUs, because of their architectural optimization for parallel computations, are well-suited for highly parallelizable problems. Due to the advent of general purpose GPU computing in recent years, GPUs are not limited to graphics and video processing alone, but include computationally intensive scientific and mathematical applications as well. Moreover P systems, including SNP systems, are inherently and maximally parallel computing models whose inspirations are taken from the functioning and dynamics of a living cell. In particular, SNP systems try to give a modest but formal representation of a special type of cell known as the neuron and their interactions with one another. The nature of SNP systems allowed their representation as matrices, which is a crucial step in simulating them on highly parallel devices such as GPUs. The highly parallel nature of SNP systems necessitate the use of hardware intended for parallel computations. The simulation algorithms, design considerations, and implementation are presented. Finally, simulation results, observations, and analyses using an SNP system that generates all numbers in $\mathbb N$ - {1} are discussed, as well as recommendations for future work.Comment: 19 pages in total, 4 figures, listings/algorithms, submitted at the 9th Brainstorming Week in Membrane Computing, University of Seville, Spai

Drip and Mate Operations Acting in Test Tube Systems and Tissue-like P systems

The operations drip and mate considered in (mem)brane computing resemble the operations cut and recombination well known from DNA computing. We here consider sets of vesicles with multisets of objects on their outside membrane interacting by drip and mate in two different setups: in test tube systems, the vesicles may pass from one tube to another one provided they fulfill specific constraints; in tissue-like P systems, the vesicles are immediately passed to specified cells after having undergone a drip or mate operation. In both variants, computational completeness can be obtained, yet with different constraints for the drip and mate operations

Fuzzy reasoning spiking neural P systems revisited: A formalization

Research interest within membrane computing is becoming increasingly interdisciplinary.In particular, one of the latest applications is fault diagnosis. The underlying mechanismwas conceived by bridging spiking neural P systems with fuzzy rule-based reasoning systems. Despite having a number of publications associated with it, this research line stilllacks a proper formalization of the foundations.National Natural Science Foundation of China No 61320106005National Natural Science Foundation of China No 6147232