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

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

On Modeling Signal Transduction Networks

Signal transduction networks are very complex processes employed by the living cell to suitably react to environmental stimuli. Qualitative and quantitative computational models play an increasingly important role in the representation of these networks and in the search of new insights about these phenomena. In this work we analyze some graph-based models used to discover qualitative properties of such networks. In turn, we show that MP systems can naturally extend these graph-based models by adding some qualitative elements. The case study of integrins activation during the lymphocyte recruitment, a crucial phenomenon in inflammatory processes, is described, and a first MP graph for this network is designed. Finally, we discuss some open problems related to the qualitative modeling of signaling networks

Filtered Networks of Evolutionary Processors

* Supported by INTAS 00-626 and TIC 2003-09319-c03-03.This paper presents some connectionist models that are widely used to solve NP-problems. Most well known numeric models are Neural Networks that are able to approximate any function or classify any pattern set provided numeric information is injected into the net. Neural Nets usually have a supervised or unsupervised learning stage in order to perform desired response. Concerning symbolic information new research area has been developed, inspired by George Paun, called Membrane Systems. A step forward, in a similar Neural Network architecture, was done to obtain Networks of Evolutionary Processors (NEP). A NEP is a set of processors connected by a graph, each processor only deals with symbolic information using rules. In short, objects in processors can evolve and pass through processors until a stable configuration is reach. This paper just shows some ideas about these two models

Solving 3-COL with Tissue P Systems

In the literature, several examples of the efficiency of cell-like P systems in order to solve NP-complete problems in polynomial time can be found. Recently, various new models of tissue-like P systems have received important attention from the scientific community. In this paper we present a linear-time solution to an NP-complete problem, the 3-COL problem, and discuss the possibilities of tissue-like P systems to solve hard problems.Ministerio de Educación y Ciencia TIN2005-09345-C04-0

Solving the 3-COL Problem by Using Tissue P Systems without Environment and Proteins on Cells

The 3-COL problem consists on deciding if the regions of a map can be coloured with only three colors bearing in mind that two adjacent regions must be coloured with di erent colors. It is a NP problem and it has been previously used in complexity studies in membrane computing to check the ability of a model for solving problems of such complexity class. Recently, tissue P systems with proteins on cells have been presented and its ability to solve NP-problems has been proved, but it remained as an open question to know if such model was still able to solve such problems if the environment was removed. In this paper we provide an a rmative answer to this question by showing a uniform family of tissue P systems without environment and with proteins on cells which solves the 3-COL problem in linear time

Solving the Bin-Packing Problem by Means of Tissue P System with 2-Division

The ability of tissue P systems with 2-division for solving NP problems in polynomial time is well-known and many solutions can be found in the literature to several of such problems. Nonetheless, there are very few papers devoted to the Bin-packing problem. The reason may be the difficulties for dealing with different number of bins, capacity and number of objects by using exclusively division rules that produce two offsprings in each application. In this paper we present the design of a family of tissue P systems with 2 division which solves the Bin-packing problem in polynomial time by combining design techniques which can be useful for further research

Designing Tissue-like P Systems for Image Segmentation on Parallel Architectures

Problems associated with the treatment of digital images have several interesting features from a bio-inspired point of view. One of them is that they can be suitable for parallel processing, since the same sequential algorithm is usually applied in different regions of the image. In this paper we report a work-in-progress of a hardware implementation in Field Programmable Gate Arrays (FPGAs) of a family of tissue-like P systems which solves the segmentation problem in digital images.Ministerio de Ciencia e Innovación TIN-2009-13192Junta de Andalucía P08-TIC-04200Junta de Andalucía PO6-TIC-02268Ministerio de Educación y Ciencia MTM2009-1271

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

Parsing languages of P colony automata

In this paper a subclass of generalized P colony automata is defined that satisfies a property which resembles the LL(k) property of context-free grammars The possibility of parsing the characterized languages using a k symbol lookahead, as in the LL(k) parsing method for context-free languages, is examined

Networks of Cells and Petri Nets

We introduce a new class of P systems, called networks of cells, with rules allowing several cells to simultaneously interact with each other in order to produce some new objects inside some other output cells. We define different types of behavior for networks of cells by considering alternative strategies for the application of the rules: sequential application, free parallelism, maximal parallelism, locally-maximal parallelism and minimal parallelism. We devise a way for translating network of cells into place- transition nets with localities (PTL-nets, for short) - a specific class of Petri nets. Then, for such a construction, we show a behavioral equivalence between network of cells and corresponding PTL-nets only in the case maximal parallelism, sequential execution, and free parallelism, whereas we observe that, in the case of locally-maximal parallelism and minimal parallelism, the corresponding PTL-nets are not always able to mimic the behavior of network of cells. Also, we address the reverse problem of finding a corresponding network of cells for a given PTL-net by obtaining similar results concerning the relation- ships between their semantics. Finally, we present network-of-cells-based models of two classical synchronization problems: producer/consumer and dining philosophers