DCBA: simulating population dynamics p systems with proportional object distribution

Authors:
Miguel A. Martínez-del-Amor;Ignacio Pérez-Hurtado;Manuel García-Quismondo;Luis F. Macías-Ramos;Luis Valencia-Cabrera;Álvaro Romero-Jiménez;Carmen Graciani;Agustín Riscos-Núñez;Mari A. Colomer;Mario J. Pérez-Jiménez
Affiliations:
Research Group on Natural Computing Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla, Spain;Research Group on Natural Computing Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla, Spain;Research Group on Natural Computing Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla, Spain;Research Group on Natural Computing Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla, Spain;Research Group on Natural Computing Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla, Spain;Research Group on Natural Computing Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla, Spain;Research Group on Natural Computing Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla, Spain;Research Group on Natural Computing Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla, Spain;Department of Mathematics, University of Lleida, Lleida, Spain;Research Group on Natural Computing Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla, Spain
Venue:
CMC'12 Proceedings of the 13th international conference on Membrane Computing
Year:
2012

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Abstract

Population Dynamics P systems provide a formal framework for ecological modelling having a probabilistic (while keeping the maximal parallelism). Several simulation algorithms have been developed always trying to reach higher reliability in the way they reproduce the behaviour of the ecosystems being modelled. It is natural for those algorithms to classify the rules 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 addresses that inherent non-determinism of the model by distributing proportionally the resources.