A syntax for semantics in P-Lingua

P-Lingua is a software framework for Membrane Computing, it includes a programming language, also called P-Lingua, for writting P system de nitions using a syntax close to standard scienti c notation. The rst line of a P-Lingua le is an unique identi er de ning the variant or model of P system to be used, i.e, the semantics of the P system. Software tools based on P-Lingua use this identi er to select a simulation algorithm implementing the corresponding derivation mode. Derivation modes de ne how to obtain a con guration Ct+1 from a con guration Ct. This information is usually hard-coded in the simulation algorithm. The P system model also de nes what types or rules can be used, the P-Lingua compiler uses the identi er to select an speci c parser for the le. In this case, a set of parsers is codi ed within the compiler tool. One for each unique identi er. P-Lingua has grown during the last 12 years, including more and more P system models. From a software engineering point of view, this approximation implies a continous development of the framework, leading to a monolithic software which is hard to debug and maintain. In this paper, we propose a new software approximation for the framework, including a new syntax for de ning rule patterns and derivation modes. The P-Lingua users can now de ne custom P system models instead of hard-coding them in the software. This approximation leads to a more exible solution which is easier to maintain and debug. Moreover, users could de ne and play with new/experimental P system models

A Note on the Probabilistic Evolution for P Systems

In this note we propose a method that permits to describe in a uniform man- ner variants of probabilistic/stochastic P systems. We give examples of such a description for existing models of P systems using probabilities

Lifted Bayesian filtering in multi-entity systems

This thesis focuses on Bayesian filtering for systems that consist of multiple, interacting entites (e.g. agents or objects), which can naturally be described by Multiset Rewriting Systems (MRSs). The main insight is that the state space that is underling an MRS exhibits a certain symmetry, which can be exploited to increase inference efficiency. We provide an efficient, lifted filtering algorithm, which is able to achieve a factorial reduction in space and time complexity, compared to conventional, ground filtering.Diese Arbeit betrachtet Bayes'sche Filter in Systemen, die aus mehreren, interagierenden Entitäten (z.B. Agenten oder Objekten) bestehen. Die Systemdynamik solcher Systeme kann auf natürliche Art durch Multiset Rewriting Systems (MRS) spezifiziert werden. Die wesentliche Erkenntnis ist, dass der Zustandraum Symmetrien aufweist, die ausgenutzt werden können, um die Effizienz der Inferenz zu erhöhen. Wir führen einen effizienten, gelifteten Filter-Algorithmus ein, dessen Zeit- und Platzkomplexität gegenüber dem grundierten Algorithmus um einen faktoriellen Faktor reduziert ist

An Overview of P-Lingua 2.0

P–Lingua is a programming language for membrane computing which aims to be a standard to define P systems. In order to implement this idea, a Java library called pLinguaCore has been developed as a software framework for cell–like P systems. It is able to handle input files (either in XML or in P–Lingua format) defining P systems from a number of different cell–like P system models. Moreover, the library includes several built–in simulators for each supported model. For the sake of software portability, pLinguaCore can export a P system definition to any convenient output format (currently XML and binary formats are available). This software is not a closed product, but it can be extended to accept new input or output formats and also new models or simulators. The term P–Lingua 2.0 refers to the software package consisting of the above mentioned library together with a user interface called pLinguaPlugin (more details can be found at http://www.p-lingua.org). Finally, in order to illustrate the software, this paper includes an application using pLinguaCore for describing and simulating ecosystems by means of P systems.Ministerio de Educación y Ciencia TIN2006-13425Junta de Andalucía TIC04200

P-Lingua 2.0: New Features and First Applications

P-Lingua is a programming language for membrane computing. It was rst presented in Edinburgh, during the Ninth Workshop on Membrane Computing (WMC9). In this paper, the models, simulators and formats included in P-Lingua in version 2.0 are explained. We focus on the stochastic model, associated simulators and updated features. Finally, we present two new applications based on P-Lingua 2.0: a tool for describing and simulating ecosystems and a framework (currently under development) for P systems design.Ministerio de Educación y Ciencia TIN2006–13425Junta de Andalucía P08-TIC-0420

Formal Verification of P Systems

Membrane systems, also known as P systems, constitute an innovative computational paradigm inspired by the structure and dynamics of the living cell. A P system consists of a hierarchical arrangement of compartments and a finite set of multiset rewriting and communication rules, which operate in a maximally parallel manner. The organic vision of concurrent dynamics captured by membrane systems stands in antithesis with conventional formal modelling methods which focus on algebraic descriptions of distributed systems. As a consequence, verifying such models in a mathematically rigorous way is often elusive and indeed counter-intuitive when considering established approaches, which generally require sequential process representations or highly abstract theoretical frameworks. The prevalent investigations with this objective in the field of membrane computing are ambivalent and inconclusive in the wider application scope of P systems. In this thesis we directly address the formal verification of membrane systems by means of model checking. A fundamental distinction between the agnostic perspective on parallelism, advocated by process calculi, and P systems' emblematic maximally parallel execution strategy is identified. On this basis, we establish that an intuitional translation to traditional process models is inadequate for the purpose of formal verification, due to a state space growth disparity. The observation is essential for this research project: on one hand it implies the feasibility of model checking P systems, and on the other hand it underlines the suitability of this formal verification technique in the context of membrane computing. Model checking entails an exhaustive state space exploration and does not derive inferences based on the independent instructions comprising a state transition. In this respect, we define a new sequential modelling strategy which is optimal for membrane systems and targets the SPIN formal verification tool. We introduce elementary P systems, a distributed computational model which subsumes the feature diversity of the membrane computing paradigm and distils its functional vocabulary. A suite of supporting software tools which gravitate around this formalism has also been developed, comprising of 1. the eps modelling language for elementary P systems; 2. a parser for the eps specification; 3. a model simulator and 4. a translation tool which targets the Promela specification of the SPIN model checker. The formal verification approach proposed in this thesis is progressively demonstrated in four heterogeneous case studies, featuring 1. a parallel algorithm applicable to a structured model; 2. a linear time solution to an NP-complete problem; 3. an innovative implementation of the Dining Philosophers scenario (a synchronisation problem) using an elementary P system and 4. a quantitative analysis of a simple random process implemented without the support of a probabilistic model

Membrane Computing as a Modelling Tool: Looking Back and Forward from Sevilla

This paper is a tribute to Prof. Mario de Jesús Pérez- Jiménez. An overview of modelling applications in membrane computing has been compiled, trying to narrate it from a historical perspective and including numerous bibliographical references. Since being exhaustive was obviously out of scope, this quick tour on almost two decades of applications is biased, paying special attention to the contributions in which Prof. Pérez-Jiménez and members of his research group were involved.Ministerio de Economía y Competitividad TIN2017-89842-

Methodologies & formalisms for modeling macroscopic biological problems

This work presents a new computational approach, based on the formalism of P systems, for modelling and running simulations of animal population dynamics phenomena. The three formalisms proposed are: MPP systems (Minimal Probabilistic P systems), APP systems (Attributed Probabilistic P systems) and MAPP systems (Multilevel Attributed Probabilistic P systems). All of them are formally defined by providing their syntax notations and formal semantics as inference rules. Case study are provided with examples for all three formalism