128 research outputs found

    P Systems with Active Cells

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    P systems with active membranes is a widely studied framework within the field of Membrane Computing since the creation of the discipline. The abstraction of the structure and behavior of living cells is reflected in the tree-like hierarchy and the kinds of rules that can be used in these kinds of systems. Resembling the organization and communication between cells within tissues that form organs, tissue-like P systems were defined as their abstractions, using symport/antiport rules, that is, moving and exchanging elements from one cell to another one. All the cells are located in an environment where there exist an arbitrary number of some elements. Lately, symport/antiport rules have been used in the framework of cell-like membrane systems in order to study their computational power. Interesting results have been reached, since they act similarly to their counterparts in the framework of tissue P systems. Here, the use of the former defined rules (that is, evolution, communication, dissolution and division/separation rules) is considered, but not working with a tree-like structure. Some remarks about choosing good semantics are given

    Contour Approximation with P Systems

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    We model the problem of contour approximation using Hilbert's space lling curve, with a novel type of parallel array rewriting rules. We further use their pattern to introduce a special type of tissue P system, with novel features, among which is controlling their behavior with input. We propose some further developments.Ministerio de Economía, Industria y Competitividad TIN2017-89842-

    Limits on P Systems with Proteins and Without Division

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    In the field of Membrane Computing, computational complexity theory has been widely studied trying to nd frontiers of efficiency by means of syntactic or semantical ingredients. The objective of this is to nd two kinds of systems, one non-efficient and another one, at least, presumably efficient, that is, that can solve NP-complete prob- lems in polynomial time, and adapt a solution of such a problem in the former. If it is possible, then P = NP. Several borderlines have been defi ned, and new characterizations of different types of membrane systems have been published. In this work, a certain type of P system, where proteins act as a supporting element for a rule to be red, is studied. In particular, while division rules, the abstraction of cellular mitosis is forbidden, only problems from class P can be solved, in contrast to the result obtained allowing them.Ministerio de Economía y Competitividad TIN2017-89842-PNational Natural Science Foundation of China No 6132010600

    Narrowing Frontiers of Efficiency with Evolutional Communication Rules and Cell Separation

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    In the framework of Membrane Computing, several efficient solutions to computationally hard problems have been given. To find new borderlines between families of P systems that can solve them and the ones that cannot is an important way to tackle the P versus NP problem. Adding syntactic and/or semantic ingredients can mean passing from non-efficiency to presumably efficiency. Here, we try to get narrow frontiers, setting the stage to adapt efficient solutions from a family of P systems to another one. In order to do that, a solution to the SAT problem is given by means of a family of tissue P systems with evolutional symport/antiport rules and cell separation with the restriction that both the left-hand side and the right-hand side of the rules have at most two objects.Ministerio de Economía y Competitividad TIN2017-89842-PNational Natural Science Foundation of China No 6132010600

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

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    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-

    P systems with evolutional symport and membrane creation rules solving QSAT

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    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-

    An optimal solution to the SAT problem with tissue P systems

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    In the framework of membrane computing, several frontiers of e ciency have been found with respect to the resources that di erent families of P systems take to solve a decision problem. Each of these frontiers provides a new way to tackle the P versus NP problem. In this sense, optimal frontiers are needed in order to separate close variants of P systems. In a previous work, an e cient solution to SAT was given in the framework of P systems from T DC(3). In this work, we will provide an optimal solution to the SAT problem in terms of length of the rules.Ministerio de Industria, Economía y Competitividad TIN2017-89842-

    P systems with evolutional communication and division rules

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    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 CDECˆ(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 rulesMinisterio de Ciencia e Innovación TIN2017-89842-

    Fuzzy reasoning spiking neural P systems revisited: A formalization

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    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
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