Cell-like and Tissue-like Membrane Systems as Recognizer Devices

Most of the variants of membrane systems found in the literature are generally thought as generating devices. In this paper recognizer computational devices (cell–like and tissue–like) are presented in the framework of Membrane Computing, using the biological membranes arranged hierarchically, inspired from the structure of the cell, and using the biological membranes placed in the nodes of a graph, inspired from the cell inter–communication in tissues. In this context, polynomial complexity classes of recognizer membrane systems are introduced. The paper also addresses the P versus NP problem, and the (efficient) solvability of computationally hard problems, in the framework of these new complexity classes.Ministerio de Educación y Ciencia TIN2005-09345-C04-0

A Computational Complexity Theory in Membrane Computing

In this paper, a computational complexity theory within the framework of Membrane Computing is introduced. Polynomial complexity classes associated with di erent models of cell-like and tissue-like membrane systems are de ned and the most relevant results obtained so far are presented. Many attractive characterizations of P 6= NP conjecture within the framework of a bio-inspired and non-conventional computing model are deduced.Ministerio de Educación y Ciencia TIN2006-13425Junta de Andalucía P08–TIC-0420

Revisiting Sevilla Carpets: A New Tool for the P-Lingua Era

Sevilla Carpets have already been used to compare di erent solutions of the Subset Sum problem: either designed in the framework of P systems with active membranes (both in the case of membrane division and membrane creation), and also another one in the framework of tissue-like P systems with cell division. Recently, the degree of parallelism and other descriptive complexity details have been found to be relevant when designing parallel simulators running on GPUs. We present here a new way to use the information provided by Sevilla carpets, and a script that allows to generate them automatically from P-Lingua les.Ministerio de Economía y Competitividad TIN2012-3743

Solving Multidimensional 0-1 Knapsack Problem with Time-Free Tissue P Systems

Tissue P system is a class of parallel and distributed model; a feature of traditional tissue P system is that the execution time of certain biological processes is very sensitive to environmental factors that might be hard to control. In this work, we construct a family of tissue P systems that works independently from the values associated with the execution times of the rules. Furthermore, we present a time-free efficient solution to multidimensional 0-1 knapsack problem by timed recognizer tissue P systems

A Cellular Solution to Subset Sum Using Division of Non-elementary Membranes and Dissolution, with Time and Initial Resources Bounded by log k

The aim of our paper is twofold. On one hand we prove the ability of polar- izationless P systems with dissolution and with division rules for non-elementary mem- branes to solve NP-complete problems in a polynomial number of steps, and we do this by presenting a solution to the Subset Sum problem. On the other hand, we improve some similar results obtained for di®erent models of P systems by reducing the number of steps and the necessary resources to be of a logarithmic order with respect to k (recall that n and k are the two parameters used to indicate the size of an instance of the Subset Sum problem). As the model we work with does not allow cooperative rules and does not consider the membranes to have an associated polarization, the strategy that we will follow consists on using objects to represent the weights of the subsets through their multiplicities, and comparing the number of objects against a ¯xed number of membranes. More precisely, we will generate k membranes in log k steps.Ministerio de Educación y Ciencia TIN2006-13425Junta de Andalucía TIC-58

Computational Efficiency of Cellular Division in Tissue-like Membrane Systems

Tissue-like P systems with cell division are computing models in the framework of membrane computing. They are inspired by the intercellular communication and neuronal synaptics, their structures being formalized by underlying graphs. As usual in membrane computing, division rules allow the construction of an exponential workspace (described by the number of cells) in a linear time. In this paper this ability is used for presenting a uniform linear-time solution for the (NP{complete) Vertex Cover problem via a uniform family of such systems. This solution is compared to other ones obtained in the framework of cell-like membrane systems.Ministerio de Educación y Ciencia TIN2006-13425Junta de Andalucía TIC-58

2014 Summer Research Symposium Abstract Book

2014 Summer volume of abstracts for science research projects conducted by students at Trinity College