102,833 research outputs found
On the efficiency of cell-like and tissue-like recognizing membrane systems
Cell-like recognizing membrane systems are computational devices in the framework of membrane
computing inspired from the structure of living cells, where biological membranes are arranged
hierarchically. In this paper tissue-like recognizing membrane systems are presented. The idea is to
consider that membranes are placed in the nodes of a graph, mimicking the cell intercommunication in
tissues.
In this context, polynomial complexity classes associated with recognizing membrane systems can be
defined. We recall the definition for cell-like systems, and we introduce the corresponding complexity
classes for the tissue-like case. Moreover, in this paper two efficient solutions to the satisfiability
problem are analyzed and compared from a complexity point of view.Ministerio de Educación y Ciencia TIN2005-09345-C04-01Junta de Andalucía TIC-58
An apparently innocent problem in Membrane Computing
The search for effcient solutions of computationally hard problems by means
of families of membrane systems has lead to a wide and prosperous eld of research. The
study of computational complexity theory in Membrane Computing is mainly based on
the look for frontiers of effciency between different classes of membrane systems. Every
frontier provides a powerful tool for tackling the P versus NP problem in the following
way. Given two classes of recognizer membrane systems R1 and R2, being systems from
R1 non-effcient (that is, capable of solving only problems from the class P) and systems
from R2 presumably e cient (that is, capable of solving NP-complete problems), and
R2 the same class that R1 with some ingredients added, passing from R1 to R2 is
comparable to passing from the non effciency to the presumed effciency. In order to
prove that P = NP, it would be enough to, given a solution of an NP-complete problem
by means of a family of recognizer membrane systems from R2, try to remove the added
ingredients to R2 from R1. In this paper, we study if it is possible to solve SAT by
means of a family of recognizer P systems from AM0(�����d;+n), whose non-effciency was
demonstrated already
Evaluating space measures in P systems
P systems with active membranes are a variant of P systems where membranes can be created by division of existing membranes, thus creating an exponential amount of resources in a polynomial number of steps. Time and space complexity classes for active membrane systems have been introduced, to characterize classes of problems that can be solved by different membrane systems making use of different resources. In particular, space complexity classes introduced initially considered a hypothetical real implementation by means of biochemical materials, assuming that every single object or membrane requires some constant physical space (corresponding to unary notation). A different approach considered implementation of P systems in silico, allowing to store the multiplicity of each object in each membrane using binary numbers. In both cases, the elements contributing to the definition of the space required by a system (namely, the total number of membranes, the total number of objects, the types of different membranes, and the types of different objects) was considered as a whole. In this paper, we consider a different definition for space complexity classes in the framework of P systems, where each of the previous elements is considered independently. We review the principal results related to the solution of different computationally hard problems presented in the literature, highlighting the requirement of every single resource in each solution. A discussion concerning possible alternative solutions requiring different resources is presented
Computing with cells: membrane systems - some complexity issues.
Membrane computing is a branch of natural computing which abstracts computing models from the structure and the functioning of the living cell. The main ingredients of membrane systems, called P systems, are (i) the membrane structure, which consists of a hierarchical arrangements of membranes which delimit compartments where (ii) multisets of symbols, called objects, evolve according to (iii) sets of rules which are localised and associated with compartments. By using the rules in a nondeterministic/deterministic maximally parallel manner, transitions between the system configurations can be obtained. A sequence of transitions is a computation of how the system is evolving. Various ways of controlling the transfer of objects from one membrane to another and applying the rules, as well as possibilities to dissolve, divide or create membranes have been studied. Membrane systems have a great potential for implementing massively concurrent systems in an efficient way that would allow us to solve currently intractable problems once future biotechnology gives way to a practical bio-realization. In this paper we survey some interesting and fundamental complexity issues such as universality vs. nonuniversality, determinism vs. nondeterminism, membrane and alphabet size hierarchies, characterizations of context-sensitive languages and other language classes and various notions of parallelism
Modelling of Multi-Agent Systems: Experiences with Membrane Computing and Future Challenges
Formal modelling of Multi-Agent Systems (MAS) is a challenging task due to
high complexity, interaction, parallelism and continuous change of roles and
organisation between agents. In this paper we record our research experience on
formal modelling of MAS. We review our research throughout the last decade, by
describing the problems we have encountered and the decisions we have made
towards resolving them and providing solutions. Much of this work involved
membrane computing and classes of P Systems, such as Tissue and Population P
Systems, targeted to the modelling of MAS whose dynamic structure is a
prominent characteristic. More particularly, social insects (such as colonies
of ants, bees, etc.), biology inspired swarms and systems with emergent
behaviour are indicative examples for which we developed formal MAS models.
Here, we aim to review our work and disseminate our findings to fellow
researchers who might face similar challenges and, furthermore, to discuss
important issues for advancing research on the application of membrane
computing in MAS modelling.Comment: In Proceedings AMCA-POP 2010, arXiv:1008.314
Uniformity is weaker than semi-uniformity for some membrane systems
We investigate computing models that are presented as families of finite
computing devices with a uniformity condition on the entire family. Examples of
such models include Boolean circuits, membrane systems, DNA computers, chemical
reaction networks and tile assembly systems, and there are many others.
However, in such models there are actually two distinct kinds of uniformity
condition. The first is the most common and well-understood, where each input
length is mapped to a single computing device (e.g. a Boolean circuit) that
computes on the finite set of inputs of that length. The second, called
semi-uniformity, is where each input is mapped to a computing device for that
input (e.g. a circuit with the input encoded as constants). The former notion
is well-known and used in Boolean circuit complexity, while the latter notion
is frequently found in literature on nature-inspired computation from the past
20 years or so.
Are these two notions distinct? For many models it has been found that these
notions are in fact the same, in the sense that the choice of uniformity or
semi-uniformity leads to characterisations of the same complexity classes. In
other related work, we showed that these notions are actually distinct for
certain classes of Boolean circuits. Here, we give analogous results for
membrane systems by showing that certain classes of uniform membrane systems
are strictly weaker than the analogous semi-uniform classes. This solves a
known open problem in the theory of membrane systems. We then go on to present
results towards characterising the power of these semi-uniform and uniform
membrane models in terms of NL and languages reducible to the unary languages
in NL, respectively.Comment: 28 pages, 1 figur
Subroutines in P Systems and Closure Properties of Their Complexity Classes
The literature on membrane computing describes several variants of P systems
whose complexity classes C are "closed under exponentiation", that is, they satisfy
the inclusion PC C, where PC is the class of problems solved by polynomial-time
Turing machines with oracles for problems in C. This closure automatically implies closure
under many other operations, such as regular operations (union, concatenation,
Kleene star), intersection, complement, and polynomial-time mappings, which are inherited
from P. Such results are typically proved by showing how elements of a family of
P systems can be embedded into P systems simulating Turing machines, which exploit
the elements of as subroutines. Here we focus on the latter construction, abstracting
from the technical details which depend on the speci c variant of P system, in order to
describe a general strategy for proving closure under exponentiation
On acceptance conditions for membrane systems: characterisations of L and NL
In this paper we investigate the affect of various acceptance conditions on
recogniser membrane systems without dissolution. We demonstrate that two
particular acceptance conditions (one easier to program, the other easier to
prove correctness) both characterise the same complexity class, NL. We also
find that by restricting the acceptance conditions we obtain a characterisation
of L. We obtain these results by investigating the connectivity properties of
dependency graphs that model membrane system computations
A Framework for Complexity Classes in Membrane Computing
The purpose of the present work is to give a general idea about the existing results and open problems
concerning the study of complexity classes within the membrane computing framework. To this aim,
membrane systems (seen as computing devices) are briefly introduced, providing the basic definition and
summarizing the key ideas, trying to cover the various approaches that are under investigation in this area
– of course, special attention is paid to the study of complexity classes. The paper concludes with some
final remarks that hint the reasons why this field (as well as other unconventional models of computation)
is attracting the attention of a growing community.Ministerio de Educación y Ciencia TIN2005-09345-C04-01Junta de Andalucía TIC-58
Simulating counting oracles with cooperation
We prove that monodirectional shallow chargeless P systems with active
membranes and minimal cooperation working in polynomial time precisely characterise
P#P
k , the complexity class of problems solved in polynomial time by deterministic
Turing machines with a polynomial number of parallel queries to an oracle for a counting
problem
- …