Computing Partial Recursive Functions by Transition P Systems

In this paper a variant of transition P systems with external output designed to compute partial functions on natural numbers is presented. These P systems are stable under composition, iteration and unbounded minimization (μ–recursion) of functions. We prove that every partial recursive function can be computed by such P systems, from which the computational completeness of this model can be deduced.Ministerio de Ciencia y Tecnología TIC2002-04220-C03-0

Computing Partial Recursive Functions by Virus Machines

Virus Machines are a computational paradigm inspired by the manner in which viruses replicate and transmit from one host cell to another. This paradigm provides non-deterministic sequential devices. Non-restricted Virus Machines are unbounded Virus Machines, in the sense that no restriction on the number of hosts, the number of instructions and the number of viruses contained in any host along any computation is placed on them. The computational completeness of these machines has been obtained by simulating register machines. In this paper, Virus Machines as function computing devices are considered. Then, the universality of non-restricted virus machines is proved by showing that they can compute all partial recursive functions.Ministerio de Economía y Competitividad TIN2012- 3743

Complexity Classes in Cellular Computing with Membranes

In this paper we introduce the complexity class PMC∗ F of all decision problems solvable in polynomial time by a family of P systems belonging to a prefixed class of recognizer membrane systems, F.Ministerio de Ciencia y Tecnología TIC2002-04220-C03-0

Computationally Hard Problems Addressed Through P Systems

In this chapter we present a general framework to provide efficient solutions to decision problems through families of cell-like membrane systems constructed in a semi-uniform way (associating with each instance of the problem one P system solving it) or a uniform way (all instances of a decision problem having the same size are processed by the same system). We also show a brief compendium of efficient semi-uniform and uniform solutions to hard problems in these systems, and we explicitly describe some of these solutions.Ministerio de Ciencia y Tecnología TIC2002-04220-C03-0

The P Versus NP Problem Through Cellular Computing with Membranes

We study the P versus NP problem through membrane systems. Language accepting P systems are introduced as a framework allowing us to obtain a characterization of the P = NP relation by the polynomial time unsolvability of an NP–complete problem by means of a P system.Ministerio de Ciencia y Tecnología TIC2002-04220-C03-0

Efficient simulation of tissue-like P systems by transition cell-like P systems

In the framework of P systems, it is known that the construction of exponential number of objects in polynomial time is not enough to efficiently solve NP-complete problems. Nonetheless, it could be sufficient to create an exponential number of membranes in polynomial time. Working with P systems whose membrane structure does not increase in size, it is known that it is not possible to solve computationally hard problems (unless P = NP), basically due to the impossibility of constructing exponential number of membranes, in polynomial time, using only evolution, communication and dissolution rules. In this paper we show how a family of recognizer tissue P systems with symport/ antiport rules which solves a decision problem can be efficiently simulated by a family of basic recognizer P systems solving the same problem. This simulation allows us to transfer the result about the limitations in computational power, from the model of basic cell-like P systems to this kind of tissue-like P systems.Ministerio de Educación y Ciencia TIN2006-13425Junta de Andalucía TIC-58

Graphical Modeling of Higher Plants Using P Systems

L systems have been widely used to model and graphically represent the growth of higher plants [20]. In this paper we continue developing the framework introduced in [21], which make use of the topology of membrane structures to model the morphology of branching structures.Ministerio de Educación y Ciencia TIN2005-09345-C03-01Junta de Andalucía TIC-58

The Growth of Branching Structures with P Systems

L-systems have been widely used to model and graphically represent the growth of plants. In, the use of membrane computing for such tasks has been proposed. In this paper we present a di®erent approach, which makes use of the topology of membrane structures to model the morphology of branching structures. We also keep closer to reality by simulating their growth from buds, instead of rewriting existing structures, as L-systems do.Ministerio de Educación y Ciencia TIN2005-09345-C03-0

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