Structures and Bio-language to Simulate Transition P Systems on Digital Computers

Arroyo, Fernando; Baranda, Angel V.; Castellanos, Juan; Luengo, Carmen; López, Luis Fernando de Mingo

doi:10.1007/3-540-45523-x_1

Cited by 5 publications

(6 citation statements)

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“…and [18], in Prolog. They were followed closely by [19] (in Scheme, based on the formalization presented in [20]) and [21] (in Haskell, based on the previous works analysing algorithmic aspects, the framework, and the data structures used, see [22][23][24][25][26]). After these ones, a new simulator for transition P systems using Java was presented in [27].…”

Section: First Steps Of Simulation In Membrane Computingmentioning

confidence: 99%

An interactive timeline of simulators in membrane computing

et al. 2019

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As with any fast-emerging research front in computer science, the proliferation of theoretical and practical results within Membrane computing since its appearance in 1998 was astonishing. As a consequence, it became necessary during the subsequent years to produce several surveys collecting the main achievements from a theoretical point of view, along with some specific surveys about simulation tools for this paradigm. As the discipline has reached a certain degree of maturity, more practical applications have arisen, and new collective works are summarising the new software products appeared. However, while these recapitulation efforts remain useful for details about new simulators, they cannot act as exhaustive updated listings, as they become obsolete as soon as new tools are developed. Thus, we considered that it was necessary to provide an interactive tool showing an updated timeline (https ://www.gcn.us.es/Simul ation MC) about the simulation of the computational devices of membrane computing (a.k.a P systems), aiming to stay updated whenever any new practical work comes out in the discipline. This paper recalls the main stages and milestones within the evolution of simulation tools for different types and variants of P systems, along with their main related applications. In addition, it describes the interactive web tool with the timeline mentioned, where all the references related here have been incorporated. Unlike other survey papers, it is the intent of this work to reinforce this initial collective effort with the web endpoint kept alive and updated.

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Section: First Steps Of Simulation In Membrane Computingmentioning

confidence: 99%

An interactive timeline of simulators in membrane computing

et al. 2019

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“…In particular, the proposed simulation framework is able to exploit, differently from other existing membrane computing simulation system [1] [2][3] [4][5] [6], the distributed and parallel nature of membrane computing devices by using the multi-agent system concept. The integration of multi-agent systems and membrane computing methodologies allows to achieve different attractive features derived from classical multi-agent system properties: autonomy, distribution, parallelism, mobility [7].…”

Section: Introductionmentioning

confidence: 99%

A proposal of multi-agent simulation system for membrane computing devices

Loia

2007

2007 IEEE Congress on Evolutionary Computation

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Membrane Computing (or P-System theory) is a recent area of Natural Computing, the field of computer science that works with computational techniques inspired by nature and natural systems. Particularly, Membrane computing investigates models of computation inspired by the structure and functioning of biological cells focusing attention on their distributed and parallel transformations. Different software applications which have been developed in imperative languages, like Java, or in declaratives languages, as Prolog, work in the framework of Membrane Computing systems. These applications simulate the behavior of P-System focusing on details about computational power of different Membrane devices without exploiting the distributed nature of simulated cellular structures. This paper presents a parallel and distributed application, based on Multi-Agent System technology, able to simulate Membrane Computing devices. The aim is to show how the theoretical distributed nature of P-Systems can be mapped into a real distributed Multi-Agent System in order to achieve two important goals: 1) to define a theoretical computational model for Multi-Agent System architectures; 2) to design a software application able to simulate Membrane Computing devices in a real fashion by exploiting the distributed nature of Multi-Agent System technology. © 2007 IEEE

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“…Here is a list of some work related to this area: [Arroyo, 2003] y show the model and the design but it does not go further for a p-system's implementation. These distribute the information about p-system structure into the processors that implement the transition Psystem.…”

Section: Non Conventional Hardwarementioning

confidence: 99%

“…There will be two evolution steps (the initial one and the final one) in the P-systems can be transformed into MAS. To understand P-systems in detail, refer to [Arroyo, 2001].…”

Section: 13example and Codementioning

confidence: 99%

“…The intentions were not meant to give an in-depth explanation of the Psystem technology nor the Multi-agent system technology. There are many papers that have been published with these intentions [Păun 1998], [Arroyo, 2001] [Arroyo, 2003, The P-system described here is generic; aspects such as rules election, priorities between rules, etc. have not been fully detailed.…”

Section: Chapter Conclusionmentioning

confidence: 99%

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New techniques for implementing membrane systems

Arteta¹

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Biomolecular computing is the focus of this thesis. In particular, the area of computing with the membranes of the living cells commonly referred as 'membrane computing' or 'transition P-systems'. It introduces the concept of 'adaptability'.The new idea of "adaptability "appears in this work. Adaptability means the ability for the membrane computing model to interact with other technologies in order to obtain optimal results when dealing with complex problems. In fact, new scenarios containing P-systems are shown. These scenarios have the transition P-systems working together with other technologies.Furthermore, methodologies and new software are introduced to implement the evolution rules application phase within membrane computing. These methodologies and software improve P-system's functionality by processing the information in a faster way. This is especially useful to obtain optimal results when dealing with complex problems such as NP-complete problems. In particular this thesis reveals: Transition P-systems as an adaptable technology as they can interact with Multi-agent Systems and with robots to acquire an optimal performance.A random function to implement the evolution rules application phase is defined to make the model less deterministic. Moreover, introduced here are new techniques for evolution rules application that improve the current performance of the P-systems when solving problems that have a high computational complexity. The techniques described in this thesis use solutions of linear system Diophantine equations, data structures (virtual or physical) and probabilistic and statistical patterns.

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Structures and Bio-language to Simulate Transition P Systems on Digital Computers

Cited by 5 publications

References 4 publications

An interactive timeline of simulators in membrane computing

An interactive timeline of simulators in membrane computing

A proposal of multi-agent simulation system for membrane computing devices

New techniques for implementing membrane systems

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