13th International Conference on Membrane Computing - MTA Sztaki

<strong>13th</strong> <strong>International</strong> <strong>Conference</strong> on Membrane Computing, CMC13,
Budapest, Hungary, August 28 - 31, 2012. Proceedings, pages 291 - 309.
DCBA: Simulating Population Dynamics
P Systems with Proportional Object
Distribution
M.A. Martínez-del-Amor 1 , I. Pérez-Hurtado 1 , M. García-Quismondo 1 ,
L.F. Macías-Ramos 1 , L. Valencia-Cabrera 1 , A. Romero-Jiménez 1 , C. Graciani 1 ,
A. Riscos-Núñez 1 , M.A. Colomer 2 , and M.J. Pérez-Jiménez 1
1 Research Group on Natural Computing
Department of Computer Science and Artificial Intelligence
University of Seville
Avda. Reina Mercedes s/n, 41012 Sevilla, Spain
{mdelamor, perezh, mgarciaquismondo, lfmaciasr, lvalencia,
romero.alvaro, cgdiaz, ariscosn, marper}@us.es
2 Department of Mathematics
University of Lleida
Avda. Alcalde Rovira Roure, 191, 25198 Lleida, Spain
colomer@matematica.udl.es
Abstract. Population Dynamics P systems (PDP systems, in short)
refer to a formal framework for ecological modelling. The semantics
of the model associates probabilities with rules, but inasmuch as
the model is based on P systems, the rules are also applied in a
maximally parallel way. Following the success of the first model using
this framework, initially called multienvironment probabilistic P systems,
several simulation algorithms have been developed in order to better
reproduce the behaviour of the ecosystems being modelled.
It is natural for those algorithms to classify the rules from the model
into blocks, comprising rules that share identical left-hand side. Previous
algorithms, such as the Binomial Block Based (BBB) or the Direct Non
Deterministic distribution with Probabilities (DNDP), do not define
a deterministic behaviour for blocks of rules competing for the same
resources. In this paper we introduce the Direct distribution based on
Consistent Blocks Algorithm (DCBA), a simulation algorithm which
address that inherent non-determinism of the model by distributing
proportionally the resources.
Keywords: Membrane Computing, Population Dynamics P systems, Simulation
Algorithm, Probabilistic P systems, DCBA, P-Lingua, pLinguaCore
1 Introduction
Since the devising of the field of Membrane Computing [12,14], it has established
as a feasible background for the modelling of biochemical phenomena. Within
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