<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miguel A. Martínez-del-Amor</style></author><author><style face="normal" font="default" size="100%">Ignacio Pérez-Hurtado</style></author><author><style face="normal" font="default" size="100%">Manuel García-Quismondo</style></author><author><style face="normal" font="default" size="100%">Luis F. Macías-Ramos</style></author><author><style face="normal" font="default" size="100%">Luis Valencia-Cabrera</style></author><author><style face="normal" font="default" size="100%">Álvaro Romero-Jiménez</style></author><author><style face="normal" font="default" size="100%">Carmen Graciani-Díaz</style></author><author><style face="normal" font="default" size="100%">Agustín Riscos-Núñez</style></author><author><style face="normal" font="default" size="100%">M. Angels Colomer</style></author><author><style face="normal" font="default" size="100%">Mario J. Pérez-Jiménez</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">DCBA: Simulating population dynamics P systems with proportional object distribution</style></title><secondary-title><style face="normal" font="default" size="100%">13th International Conference on Membrane Computing (CMC13)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">DCBA</style></keyword><keyword><style  face="normal" font="default" size="100%">Membrane computing</style></keyword><keyword><style  face="normal" font="default" size="100%">P-Lingua</style></keyword><keyword><style  face="normal" font="default" size="100%">pLinguaCore</style></keyword><keyword><style  face="normal" font="default" size="100%">Population Dynamics P systems</style></keyword><keyword><style  face="normal" font="default" size="100%">Probabilistic P systems</style></keyword><keyword><style  face="normal" font="default" size="100%">Simulation Algorithm</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.sztaki.hu/tcs/proba/cmc13/CMC13-proceedings.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Budapest, Hungary</style></pub-location><pages><style face="normal" font="default" size="100%">291-310</style></pages><isbn><style face="normal" font="default" size="100%">978-963-311-372-1 </style></isbn><abstract><style face="normal" font="default" size="100%">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.
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